Update overlays/additional directory for the upcoming Release (Python 3.12, Improved Naming)
#1359
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
WalkthroughThis change introduces new environment variable entries and parameter references for multiple Python 3.12-based notebook images, including minimal, datascience, PyTorch, TensorFlow, TrustyAI, and code-server variants for CPU, CUDA, and ROCm. It adds corresponding OpenShift ImageStream resources, updates the overlay README, and expands kustomization to dynamically inject image references and commit hashes. Changes
Possibly related PRs
Suggested labels
Suggested reviewers
📜 Recent review detailsConfiguration used: .coderabbit.yaml 📒 Files selected for processing (9)
🚧 Files skipped from review as they are similar to previous changes (9)
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. 🪧 TipsChatThere are 3 ways to chat with CodeRabbit:
SupportNeed help? Create a ticket on our support page for assistance with any issues or questions. Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. CodeRabbit Commands (Invoked using PR comments)
Other keywords and placeholders
Documentation and Community
|
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 9
🧹 Nitpick comments (12)
manifests/overlays/additional/README.md (1)
9-20: Bullet list ok, but spacing before “Note” trips markdown renderThe double-space between the last bullet and
**Note:**causes some Markdown renderers to continue the bullet list and treat the note as part of it. Delete the trailing spaces or insert a blank line.- - jupyter-trustyai-notebook-imagestream-beta - - **Note:** These images are the beta version ... + - jupyter-trustyai-notebook-imagestream-beta + +**Note:** These images are the beta version ...manifests/base/commit-latest.env (1)
19-28: Hard-coding identical commit hash blocks future patch promotionEvery new py312 image is pinned to
f083142. If a single component needs to be rebuilt, you’ll have to touch half a dozen env vars manually. Consider a singleODH_WORKBENCH_COMMIT_PY312=f083142and derive the lines withenvsubstin kustomize or CI.This avoids copy-paste drift and speeds up hot-fix promotion.
manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml (1)
20-24: Keep version strings consistent (“v3.12” → “3.12”)Every other manifest historically reports the raw version (
"3.12"). Mixing thevprefix will break simple consumers that do equality checks or sort versions lexicographically.- {"name": "Python", "version": "v3.12"} + {"name": "Python", "version": "3.12"}manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml (1)
8-12: Remove the self-questioning inline commentThe
# Not sure if suits …remark should not land in released manifests.- # Not sure if suits to add 'Data Science' on the name or notmanifests/overlays/additional/kustomization.yaml (1)
140-257: Duplication explosion – consider generating replacementsThirty-plus near-identical replacement stanzas hurt maintainability and are error-prone (see mismatches above). Kustomize’s
varsor a shortkustomize edit add varscript could generate these programmatically, reducing this section to <10 lines.manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml (1)
48-52: Same registry placeholder concern as other manifestsInclude the registry hostname in
from.nameor ensure the injected value always contains it.manifests/overlays/additional/jupyter-pytorch-notebook-imagestream-beta.yaml (3)
8-13: Clarify accelerator scope & name lengthWith a 64-character limit on
metadata.name, the current value is safe but very close. Shortening (e.g. drop “Jupyter ” prefix) leaves head-room for future variants while still being descriptive.
27-48: Too many pinned libraries risk frequent churnHard-coding 20+ dependency versions means the imagestream metadata will drift with every upstream release. Consider pinning only headline packages (CUDA, PyTorch, JupyterLab) and moving the long tail to generated docs.
51-55: Registry placeholder againSee previous comments – default registry fallback is undesirable.
manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml (1)
8-8: Fix double slash in GitHub URL.Using
https://github.com//opendatahub-io/...introduces an unnecessary empty path component and may break link-resolving logic in UIs.
Change to a single slash.- opendatahub.io/notebook-image-url: "https://github.com//opendatahub-io/notebooks/tree/main/jupyter/trustyai" + opendatahub.io/notebook-image-url: "https://github.com/opendatahub-io/notebooks/tree/main/jupyter/trustyai"manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml (2)
8-8: Remove extra slash in GitHub URL.The URL currently contains
github.com//. Replace with a single slash for a valid link.- opendatahub.io/notebook-image-url: "https://github.com//opendatahub-io/notebooks/tree/main/jupyter/datascience" + opendatahub.io/notebook-image-url: "https://github.com/opendatahub-io/notebooks/tree/main/jupyter/datascience"
10-10: Typo in description.
avialable→available.- ... a standard for libraries avialable in all notebooks + ... a standard for libraries available in all notebooks
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (13)
manifests/base/commit-latest.env(1 hunks)manifests/base/params-latest.env(1 hunks)manifests/overlays/additional/README.md(1 hunks)manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-pytorch-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/kustomization.yaml(1 hunks)
🧰 Additional context used
🧠 Learnings (14)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.898Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:135-136
Timestamp: 2025-07-04T05:52:49.464Z
Learning: jiridanek requested GitHub issue creation for improving fragile sed-based Jupyter kernel display_name modification in jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu during PR #1306 review. Issue #1321 was created with comprehensive problem description covering JSON corruption risks, greedy regex patterns, maintenance burden, and proposed Python-based JSON parsing solution with detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
manifests/overlays/additional/README.md (15)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-88
Timestamp: 2025-07-04T06:05:30.580Z
Learning: jiridanek requested GitHub issue creation for TrustyAI test notebook URL configurability and network error handling improvements during PR #1306 review. Issue #1323 was created with ⚠️ emoji in title for visibility, comprehensive problem description covering incorrect hardcoded URLs (pointing to Python 3.11 instead of 3.12), missing network error handling, maintenance burden, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1127
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:20-20
Timestamp: 2025-06-27T07:49:01.198Z
Learning: jiridanek reviewed the transformers v4.50.0 release notes and assessed that the changes are minimal and unlikely to cause TrustyAI integration problems, indicating the actual changelog contained mostly bug fixes and minor additions rather than breaking changes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T14:04:05.280Z
Learning: In opendatahub-io/notebooks, shell scripting robustness and efficiency issues in extension management loops (such as unquoted globs, word-splitting, and unnecessary repeated copies in run-code-server.sh) are systematically tracked and fixed by quoting variables, using `cp -a --`, and toggling `nullglob`, following the established pattern of operational correctness improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
manifests/base/commit-latest.env (18)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/run-nginx.sh:22-22
Timestamp: 2025-07-03T16:19:19.763Z
Learning: jiridanek requested GitHub issue creation for envsubst variable delimiter syntax error in codeserver/ubi9-python-3.12/run-nginx.sh during PR #1269 review. Issue #1316 was created with comprehensive problem description covering the comma vs. space delimiter issue in envsubst command, impact analysis including silent failures and security risks, proposed solutions with validation, acceptance criteria, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/utils/pip.conf:3-4
Timestamp: 2025-07-08T19:21:11.512Z
Learning: jiridanek requested GitHub issue creation for PYTHONPATH configuration investigation in runtime images during PR #1333 review. Issue #1339 was created with comprehensive problem description covering pip.conf target directory configuration, missing PYTHONPATH exports, potential runtime import failures, multiple investigation areas (PYTHONPATH auditing, pip configuration consistency, runtime testing), solution options with implementation guidance, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm:34-37
Timestamp: 2025-07-02T18:19:23.024Z
Learning: In the opendatahub-io/notebooks repository, issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" covers the security concern about verifying downloaded binaries including the oc client. Red Hat does not provide signed RPM packages for the OpenShift CLI (oc) in UBI9 official repositories, making manual binary download with checksum verification the recommended approach.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:05:33.329Z
Learning: tensorflow_rocm package has no Python 3.12 or 3.13 wheel support as of July 2025, with the latest version 2.14.0.600 only supporting Python 3.9, 3.10, and 3.11. The tensorflow-rocm upstream project appears abandoned with the last release in 2019. For Python 3.12+ ROCm TensorFlow environments, regular TensorFlow 2.18+ with runtime ROCm configuration is the recommended and industry-standard approach, as modern TensorFlow automatically detects and utilizes ROCm when properly installed.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:24-30
Timestamp: 2025-07-01T06:57:26.974Z
Learning: In the opendatahub-io/notebooks repository, jiridanek's team relies on strict CI process enforcement to handle potentially fragile code patterns like hard-coded relative paths. They accept some code fragility when it's mitigated through reliable CI setup and process controls, rather than always requiring code-level fixes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1197
File: runtimes/minimal/ubi9-python-3.11/requirements.txt:395-405
Timestamp: 2025-06-26T15:28:35.416Z
Learning: psutil version 7.x is compatible with UBI9, CentOS Stream 9, and RHEL 9 platforms in the opendatahub-io/notebooks repository. The upgrade from psutil 5.x to 7.x has been validated for these environments.
manifests/base/params-latest.env (16)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm:34-37
Timestamp: 2025-07-02T18:19:23.024Z
Learning: In the opendatahub-io/notebooks repository, issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" covers the security concern about verifying downloaded binaries including the oc client. Red Hat does not provide signed RPM packages for the OpenShift CLI (oc) in UBI9 official repositories, making manual binary download with checksum verification the recommended approach.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-26T16:19:31.295Z
Learning: In the opendatahub-io/notebooks repository, the Playwright Docker image version in `.github/workflows/build-notebooks-TEMPLATE.yaml` (format: `mcr.microsoft.com/playwright:v1.53.1-noble`) must always match the `@playwright/test` version specified in the `tests/browser/package.json` file. Both versions need to be updated together to maintain consistency between CI/CD pipeline and project dependencies.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-26T16:19:31.295Z
Learning: In the opendatahub-io/notebooks repository, the Playwright Docker image version in `.github/workflows/build-notebooks-TEMPLATE.yaml` (format: `mcr.microsoft.com/playwright:v1.53.1-noble`) must always match the `@playwright/test` version specified in the `tests/browser/package.json` file. Both versions need to be updated together to maintain consistency between CI/CD pipeline and project dependencies.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.898Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml (11)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1327
File: ci/cached-builds/kubeadm.yaml:70-74
Timestamp: 2025-07-06T21:46:40.050Z
Learning: In the opendatahub-io/notebooks CI environment, minimal eviction thresholds like nodefs.available: "1Mi" and imagefs.available: "1Mi" are set as required positive values to satisfy kubelet configuration requirements when the primary goal is disabling image garbage collection. These settings are contextually appropriate for the ephemeral CI environment and don't cause practical issues since the main objective is achieved through imageGC settings (imageGCHighThresholdPercent: 100, imageGCLowThresholdPercent: 99).
manifests/overlays/additional/jupyter-pytorch-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml (11)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1327
File: ci/cached-builds/kubeadm.yaml:70-74
Timestamp: 2025-07-06T21:46:40.050Z
Learning: In the opendatahub-io/notebooks CI environment, minimal eviction thresholds like nodefs.available: "1Mi" and imagefs.available: "1Mi" are set as required positive values to satisfy kubelet configuration requirements when the primary goal is disabling image garbage collection. These settings are contextually appropriate for the ephemeral CI environment and don't cause practical issues since the main objective is achieved through imageGC settings (imageGCHighThresholdPercent: 100, imageGCLowThresholdPercent: 99).
manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml (5)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
manifests/overlays/additional/kustomization.yaml (15)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by `ci/kustomize.sh`, which is invoked from `.github/workflows/code-quality.yaml` (lines 112–116). No additional pytest is needed for this purpose.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-26T16:19:31.295Z
Learning: In the opendatahub-io/notebooks repository, the Playwright Docker image version in `.github/workflows/build-notebooks-TEMPLATE.yaml` (format: `mcr.microsoft.com/playwright:v1.53.1-noble`) must always match the `@playwright/test` version specified in the `tests/browser/package.json` file. Both versions need to be updated together to maintain consistency between CI/CD pipeline and project dependencies.
manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:21:09.429Z
Learning: TrustyAI 0.6.1 (latest version as of June 2025) has a hard dependency constraint on jupyter-bokeh~=3.0.5, preventing upgrades to jupyter-bokeh 4.x in notebook images that include TrustyAI. This requires either waiting for TrustyAI to update their dependency or excluding TrustyAI from jupyter-bokeh upgrades.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-88
Timestamp: 2025-07-04T06:05:30.580Z
Learning: jiridanek requested GitHub issue creation for TrustyAI test notebook URL configurability and network error handling improvements during PR #1306 review. Issue #1323 was created with ⚠️ emoji in title for visibility, comprehensive problem description covering incorrect hardcoded URLs (pointing to Python 3.11 instead of 3.12), missing network error handling, maintenance burden, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:21:09.429Z
Learning: TrustyAI explicitly declares jupyter-bokeh~=3.0.5 as a hard dependency in both their requirements.txt and pyproject.toml files, with no open issues tracking jupyter-bokeh 4.x compatibility. This creates an unresolvable pip dependency conflict when trying to upgrade jupyter-bokeh to 4.x in notebook images that include TrustyAI.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.898Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml (10)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
🪛 LanguageTool
manifests/overlays/additional/README.md
[grammar] ~18-~18: Use correct spacing
Context: ...-tensorflow-notebook-imagestream-beta - jupyter-trustyai-notebook-imagestream-beta Note: These images are the beta versi...
(QB_NEW_EN_OTHER_ERROR_IDS_5)
🔇 Additional comments (7)
manifests/base/params-latest.env (1)
19-24: In-tree TODO indicates incomplete release artefactsLines 19-24 explicitly call out missing final builds. Shipping beta overlay with TODOs guarantees future hindsight bugs.
Block merge until:
- the TODO is resolved, or
- a tracking issue is linked and the TODO text references it.
manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml (1)
26-38: Sanity-check dependency versions against real PyPI releasesA few versions listed (e.g.
Matplotlib 3.10,Scikit-learn 1.6) are beyond the current upstream roadmap. Please verify that wheels actually exist for Python 3.12 or pin to realistic versions; otherwise the “included-software” metadata will be misleading.manifests/overlays/additional/kustomization.yaml (1)
7-15: Resource list is missing the ROCm PyTorch file & shows mixed naming
jupyter-rocm-pytorch-notebook-imagestream-beta.yamlis referenced later in replacements but is not present in theresources:block, which will makekustomize buildfail. Please add the file and keep the*-notebook-*naming consistent across all entries.⛔ Skipped due to learnings
Learnt from: jiridanek PR: opendatahub-io/notebooks#0 File: :0-0 Timestamp: 2025-06-16T11:32:09.203Z Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.Learnt from: jiridanek PR: opendatahub-io/notebooks#1306 File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50 Timestamp: 2025-07-03T16:18:59.234Z Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".Learnt from: jiridanek PR: opendatahub-io/notebooks#1230 File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22 Timestamp: 2025-06-30T14:36:53.890Z Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.Learnt from: jiridanek PR: opendatahub-io/notebooks#1306 File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50 Timestamp: 2025-07-03T16:18:59.234Z Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue.Learnt from: jiridanek PR: opendatahub-io/notebooks#1218 File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989 Timestamp: 2025-06-28T15:06:03.344Z Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by `ci/kustomize.sh`, which is invoked from `.github/workflows/code-quality.yaml` (lines 112–116). No additional pytest is needed for this purpose.Learnt from: jiridanek PR: opendatahub-io/notebooks#1259 File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15 Timestamp: 2025-07-03T07:03:45.020Z Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.Learnt from: jiridanek PR: opendatahub-io/notebooks#1259 File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15 Timestamp: 2025-07-03T07:03:45.020Z Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.Learnt from: jiridanek PR: opendatahub-io/notebooks#1333 File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50 Timestamp: 2025-07-08T19:30:01.738Z Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.Learnt from: grdryn PR: opendatahub-io/notebooks#1320 File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35 Timestamp: 2025-07-04T10:41:13.061Z Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.Learnt from: jiridanek PR: opendatahub-io/notebooks#1333 File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769 Timestamp: 2025-07-08T19:35:49.482Z Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.Learnt from: jiridanek PR: opendatahub-io/notebooks#1154 File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0 Timestamp: 2025-06-16T11:06:33.139Z Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.Learnt from: jiridanek PR: opendatahub-io/notebooks#1218 File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36 Timestamp: 2025-06-28T14:13:27.890Z Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.Learnt from: jiridanek PR: opendatahub-io/notebooks#1151 File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17 Timestamp: 2025-07-01T06:50:37.115Z Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.Learnt from: jiridanek PR: opendatahub-io/notebooks#1327 File: ci/cached-builds/kubeadm.yaml:70-74 Timestamp: 2025-07-06T21:46:40.050Z Learning: In the opendatahub-io/notebooks CI environment, minimal eviction thresholds like nodefs.available: "1Mi" and imagefs.available: "1Mi" are set as required positive values to satisfy kubelet configuration requirements when the primary goal is disabling image garbage collection. These settings are contextually appropriate for the ephemeral CI environment and don't cause practical issues since the main objective is achieved through imageGC settings (imageGCHighThresholdPercent: 100, imageGCLowThresholdPercent: 99).manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml (1)
9-13: ImageStream name format deviates from other CUDA/CPU variantsMost ImageStreams end with
-notebook-beta; this one ends with-pytorch-beta. Align naming to avoid surprise in automation that expects the*-notebook-*pattern.manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml (1)
51-55: Confirm that _n_PLACEHOLDER tokens are replaced at build time.Both the image reference (
from.name) and build-commit annotation keep then_PLACEHOLDERsentinel.
If thekustomizereplacements you added inoverlays/additional/kustomization.yamldo not match these exact strings, the final ImageStream will point to a non-existent image and the Workbench catalog tile will fail to pull.Please double-check the replacement rules or add them if missing.
manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml (1)
51-55: Verify placeholder substitution for TensorFlow image reference.Same concern as in the TrustyAI file:
odh-workbench-jupyter-tensorflow-cuda-py312-ubi9-n_PLACEHOLDERmust be resolved during the overlay build.If the replacement isn’t wired, the catalog tile will surface but deployments will ImagePullBackOff.
manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml (1)
46-50: Ensure placeholder image name is replaced.
odh-workbench-jupyter-datascience-cpu-py312-ubi9-n_PLACEHOLDERmust be substituted by the build pipeline.
Please validate the correspondingkustomizereplacement.
manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml
Outdated
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml
Outdated
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml
Outdated
Show resolved
Hide resolved
manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml
Show resolved
Hide resolved
|
CI fails due to unauthorized access, these images will be updated once the builds are in place. |
….2-beta version Update files add placeholders to all
|
Don't see what's the advantage of using /lgtm |
There was a problem hiding this comment.
Actionable comments posted: 1
♻️ Duplicate comments (1)
manifests/overlays/additional/kustomization.yaml (1)
121-132: Selector name does not match ImageStream resource
name: jupyter-rocm-minimal-betais referenced, but the resource file added above isjupyter-rocm-minimal-notebook-imagestream-beta.yaml, whosemetadata.nameis expected to bejupyter-rocm-minimal-notebook-beta.Because the names differ, the replacement for
spec.tags[0].from.nameand commit hash will never be applied, leaving placeholders in the resulting manifest.- name: jupyter-rocm-minimal-beta + name: jupyter-rocm-minimal-notebook-beta
🧹 Nitpick comments (5)
manifests/overlays/additional/README.md (1)
20-20: Typo & spacing around release noteMissing space after the period (“beta version of the 2025.b release based”) triggers the LanguageTool hint.
-**Note:** These images are the beta version of the 2025.b release based on Python 3.12. +**Note:** These images are the beta version of the 2025.b release, based on Python 3.12.manifests/overlays/additional/runtime-pytorch-imagestream-beta.yaml (1)
8-10: Fix double “//” in GitHub URLThe annotation value contains
https://github.com//opendatahub-io/.... The extra slash breaks GitHub’s automatic link rendering.-opendatahub.io/runtime-image-url: "https://github.com//opendatahub-io/notebooks/tree/main/runtimes" +opendatahub.io/runtime-image-url: "https://github.com/opendatahub-io/notebooks/tree/main/runtimes"manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml (1)
8-10: Duplicate “//” in runtime-image URLSame issue as in the PyTorch runtime – remove the second slash.
manifests/overlays/additional/runtime-tensorflow-imagestream-beta.yaml (2)
8-12: TODO comment contains typo & obsolete wording
# TODO: once the restraction takes a final shape need to update that url
- “restraction” → “restructuring” (or “refactoring”).
- Replace the placeholder URL with the final one now, or open an issue if this cannot be fixed before merge.
Clean up before the beta freeze to avoid lingering TODOs in shipped manifests.
8-10: Remove double slash in repository URLSame URL issue as the other runtime manifests.
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (19)
manifests/base/commit-latest.env(1 hunks)manifests/base/params-latest.env(1 hunks)manifests/overlays/additional/README.md(1 hunks)manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-pytorch-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/kustomization.yaml(1 hunks)manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/runtime-minimal-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/runtime-pytorch-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/runtime-rocm-pytorch-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/runtime-rocm-tensorflow-imagestream-beta.yaml(1 hunks)manifests/overlays/additional/runtime-tensorflow-imagestream-beta.yaml(1 hunks)
✅ Files skipped from review due to trivial changes (3)
- manifests/overlays/additional/runtime-rocm-tensorflow-imagestream-beta.yaml
- manifests/overlays/additional/runtime-rocm-pytorch-imagestream-beta.yaml
- manifests/overlays/additional/runtime-minimal-imagestream-beta.yaml
🚧 Files skipped from review as they are similar to previous changes (11)
- manifests/base/commit-latest.env
- manifests/overlays/additional/code-server-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-minimal-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-rocm-minimal-notebook-imagestream-beta.yaml
- manifests/base/params-latest.env
- manifests/overlays/additional/jupyter-rocm-pytorch-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-trustyai-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-pytorch-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-minimal-gpu-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-datascience-notebook-imagestream-beta.yaml
- manifests/overlays/additional/jupyter-tensorflow-notebook-imagestream-beta.yaml
🧰 Additional context used
🧠 Learnings (6)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/Dockerfile.cuda:17-25
Timestamp: 2025-07-09T08:07:30.628Z
Learning: jiridanek requested GitHub issue creation for oc client installation permission problem in PyTorch CUDA runtime Dockerfile during PR #1333 review. Issue #1356 was created with comprehensive problem description covering USER 1001 permission conflicts with root-owned /opt/app-root/bin directory, detailed impact analysis of build failures and non-executable binaries, current problematic code snippet, complete solution with user switching approach, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: atheo89
PR: opendatahub-io/notebooks#1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:32-32
Timestamp: 2025-07-07T11:08:48.524Z
Learning: atheo89 requested GitHub issue creation for multi-architecture Dockerfile improvements during PR #1258 review, specifically for enhancing structural consistency across Docker stages, replacing $(uname -m) with ${TARGETARCH} for cross-architecture builds, and adding OCI-compliant metadata labels. Issue #1332 was created with comprehensive problem description, phased implementation approach, detailed acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
manifests/overlays/additional/runtime-pytorch-imagestream-beta.yaml (9)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Dockerfile.cuda:38-38
Timestamp: 2025-07-08T19:30:20.513Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in TensorFlow CUDA runtime image during PR #1333 review. Issue was created with comprehensive problem description covering hardcoded NVARCH limitation, multiple solution options using TARGETARCH build argument with architecture mapping, acceptance criteria for multi-architecture builds, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml (4)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
manifests/overlays/additional/runtime-tensorflow-imagestream-beta.yaml (7)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Dockerfile.cuda:38-38
Timestamp: 2025-07-08T19:30:20.513Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in TensorFlow CUDA runtime image during PR #1333 review. Issue was created with comprehensive problem description covering hardcoded NVARCH limitation, multiple solution options using TARGETARCH build argument with architecture mapping, acceptance criteria for multi-architecture builds, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
manifests/overlays/additional/kustomization.yaml (20)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by `ci/kustomize.sh`, which is invoked from `.github/workflows/code-quality.yaml` (lines 112–116). No additional pytest is needed for this purpose.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty `spec.selector: {}` is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-26T16:19:31.295Z
Learning: In the opendatahub-io/notebooks repository, the Playwright Docker image version in `.github/workflows/build-notebooks-TEMPLATE.yaml` (format: `mcr.microsoft.com/playwright:v1.53.1-noble`) must always match the `@playwright/test` version specified in the `tests/browser/package.json` file. Both versions need to be updated together to maintain consistency between CI/CD pipeline and project dependencies.
manifests/overlays/additional/README.md (15)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-tensorflow-notebook-imagestream.yaml:45-45
Timestamp: 2025-06-13T08:34:01.300Z
Learning: When updating dependency versions in `manifests/base/*-imagestream.yaml`, the project convention is to modify only the newest tag (e.g., "2025.1") and intentionally leave earlier tags (e.g., "2024.2") unchanged.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-88
Timestamp: 2025-07-04T06:05:30.580Z
Learning: jiridanek requested GitHub issue creation for TrustyAI test notebook URL configurability and network error handling improvements during PR #1306 review. Issue #1323 was created with ⚠️ emoji in title for visibility, comprehensive problem description covering incorrect hardcoded URLs (pointing to Python 3.11 instead of 3.12), missing network error handling, maintenance burden, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1127
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:20-20
Timestamp: 2025-06-27T07:49:01.198Z
Learning: jiridanek reviewed the transformers v4.50.0 release notes and assessed that the changes are minimal and unlikely to cause TrustyAI integration problems, indicating the actual changelog contained mostly bug fixes and minor additions rather than breaking changes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T14:04:05.280Z
Learning: In opendatahub-io/notebooks, shell scripting robustness and efficiency issues in extension management loops (such as unquoted globs, word-splitting, and unnecessary repeated copies in run-code-server.sh) are systematically tracked and fixed by quoting variables, using `cp -a --`, and toggling `nullglob`, following the established pattern of operational correctness improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
🪛 LanguageTool
manifests/overlays/additional/README.md
[grammar] ~18-~18: Use correct spacing
Context: ...-tensorflow-notebook-imagestream-beta - jupyter-trustyai-notebook-imagestream-beta Note: These images are the beta versi...
(QB_NEW_EN_OTHER_ERROR_IDS_5)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: validation-of-sw-versions-in-imagestreams
🔇 Additional comments (2)
manifests/overlays/additional/runtime-pytorch-imagestream-beta.yaml (1)
35-36: Placeholder image name may leak to cluster
odh-pipeline-runtime-pytorch-cuda-py312-ubi9-n_PLACEHOLDERis expected to be replaced by kustomize, but only if thenotebook-image-paramsConfigMap key matches exactly. A mismatch will leave the placeholder un-resolved and the ImageStream import will fail.Double-check that:
- the key
odh-pipeline-runtime-pytorch-cuda-py312-ubi9-nexists in the ConfigMap, and- the
replacementssection targets this ImageStream (runtime-pytorch-beta).Otherwise, update either the key or the placeholder string so they match.
manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml (1)
35-36: Verify ConfigMap replacement for placeholderEnsure the
odh-pipeline-runtime-datascience-cpu-py312-ubi9-nkey exists; otherwise the placeholder will persist.
6 tasks
atheo89
changed the title
overlays/additional directory for 2025.b Beta Release (Python 3.12, Improved Naming)overlays/additional directory for the upcoming Release (Python 3.12, Improved Naming)
|
I liked it, looks really good to me! /lgtm |
|
Thanks for the you review folks, i will approve this in order to start checking the builds (hopefully tommrow) |
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: atheo89 The full list of commands accepted by this bot can be found here. The pull request process is described here
Needs approval from an approver in each of these files:
Approvers can indicate their approval by writing |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Related to: https://issues.redhat.com/browse/RHOAIENG-28585
Description
This PR updates the ODH Tier 1 notebook imagestreams in the
overlays/additionaldirectory to prepare for the upcoming release, based on Python 3.12. The changes include:Almost all the workbenches and Runtimes except ROCm TensorFlow
Standardize the naming pattern on the UI for example the cuda minimal in the past had the name:
CUDAand now it isJupyter Minimal CUDA Python 3.12the same pattern follow to the rest.This is a small porpotion of how they look like on the UI:
This how the new set of runtime images look on UI:
Screen recording: https://drive.google.com/file/d/1T8LOBa6x8hAptcZ7re5YZP4dapqtHNoW/view?usp=drive_link
NOTEs:
params-latest.envfile includes image builds fromghrclink, this should change once this or this is in place. Will follow up PR maybe on the code freeze.How Has This Been Tested?
kustomize build manifests/overlays/additional > output.yamlit should be executed without errors/issues.Merge criteria:
Summary by CodeRabbit
Summary by CodeRabbit
New Features
Documentation
Chores