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AWS adds Seekable OCI indexing to speed up SageMaker AI jobs
AWS launched Seekable OCI indexing for Amazon SageMaker AI training and processing jobs to lazy-load container images and start jobs in seconds.
Summary
AWS introduced Seekable OCI (SOCI) indexing for Amazon SageMaker AI training and processing jobs, allowing containers to lazy-load and start in seconds instead of minutes. The system fetches only necessary files to launch the container immediately and streams the rest in the background. Users can adopt the feature by pointing to pre-indexed AWS Deep Learning Containers or creating an index for custom images without changing job definitions.
What changed
- AWS added Seekable OCI indexing for Amazon SageMaker AI Training and Amazon SageMaker AI processing jobs.
- SageMaker AI now fetches only needed files to start containers and streams the rest in the background.
- Pre-indexed AWS Deep Learning Containers are available for PyTorch Training, TensorFlow Training, vLLM, and SGLang using the -soci tag suffix.
- Custom images can be indexed using tools like containerd, the SOCI snapshotter, and Finch or nerdctl.
Availability
Available now“- SOCI indexing for SageMaker AI jobs is available across all AWS Regions.”
Founder takeaway
Small teams running SageMaker AI jobs should update their image tags to the -soci variants or build indexes for custom images to reduce startup times and cut job costs.
Source
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