Add Data Storage in Cloud Native AI whitepaper#2124
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Pull request overview
Adds a new “Data on Kubernetes - Data Analytics and AI/ML Workloads” document set under the Infrastructure tag, introducing topic pages that describe storage patterns and related infrastructure considerations across the AI lifecycle.
Changes:
- Added a top-level overview page that frames the whitepaper section and links to topic pages.
- Added topic pages covering storage patterns for training, inference, and AI agents.
- Added topic pages describing related data infrastructure areas (pipelines, databases, caching/locality, storage types, network management, data mesh/fabric, and HW/SW co-design).
Reviewed changes
Copilot reviewed 12 out of 12 changed files in this pull request and generated 17 comments.
Show a summary per file
| File | Description |
|---|---|
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/overview.md | Introduces the section overview and links out to topic pages. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/training.md | Describes training storage usage patterns and references. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/inference.md | Describes inference storage usage patterns and references. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/ai-agent.md | Describes AI agent workflow storage patterns. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/block-file-object.md | Summarizes block/file/object storage and FUSE CSI drivers. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/data-cache-locality.md | Discusses caching and data locality strategies for AI/data workloads. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/data-lake-houses.md | Summarizes warehouses, lakes, and lakehouses. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/data-mesh-and-fabric.md | Introduces data mesh and data fabric concepts and references. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/data-pipelines.md | Introduces modern data pipeline patterns and example infrastructure. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/databases.md | Summarizes analytic, federated, and vector database categories. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/network-management.md | Highlights networking considerations for storage and caches in Kubernetes. |
| tags/tag-infrastructure/data-storage-in-cloud-native-ai/topics/hardware-software-co-design.md | Discusses HW/SW co-design trends and a reference link. |
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angellk
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Hi @xing-yang -- Overall, looks fantastic. Please update the missing reference links and acronym first use spell out for DAG.
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Hi @angellk, thanks for reviewing! I've addressed your comments. |
Signed-off-by: xing-yang <xingyang105@gmail.com>
Added comprehensive reference links to both inference.md and training.md files in the AI storage documentation. The references include relevant tools, frameworks, and platforms for model inference and training workflows in cloud-native environments. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> Signed-off-by: alexagriffith <agriffith96@gmail.com> Signed-off-by: xing-yang <xingyang105@gmail.com>
Added comprehensive reference links to both inference.md and training.md files in the AI storage documentation. The references include relevant tools, frameworks, and platforms for model inference and training workflows in cloud-native environments. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> Signed-off-by: alexagriffith <agriffith96@gmail.com> Signed-off-by: xing-yang <xingyang105@gmail.com>
Signed-off-by: xing-yang <xingyang105@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Signed-off-by: Karena Angell <kangell@redhat.com> Signed-off-by: xing-yang <xingyang105@gmail.com>
Signed-off-by: xing-yang <xingyang105@gmail.com>
Co-authored-by: Karena Angell <kangell@redhat.com> Signed-off-by: Xing Yang <xingyang105@gmail.com> Signed-off-by: xing-yang <xingyang105@gmail.com>
Signed-off-by: xing-yang <xingyang105@gmail.com>
angellk
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minor additional nits that I missed. looks great @xing-yang !
Co-authored-by: Karena Angell <kangell@redhat.com> Signed-off-by: Xing Yang <xingyang105@gmail.com>
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Thanks @angellk! |
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