> For clean Markdown content of this page, append .md to this URL. For the complete documentation index, see https://docs.nvidia.com/dynamo/latest/llms.txt. For section-specific indexes, append /llms.txt to any section URL.

# NVIDIA Dynamo Snapshot: Fast Startup for Inference Workloads on Kubernetes

> NVIDIA Dynamo Snapshot combines CUDA and host checkpointing to restore warm inference workers quickly on Kubernetes.

![Kubernetes checkpoint and restore lifecycle with NVIDIA Dynamo Snapshot.](https://fdr-prod-docs-files-public.s3.us-east-1.amazonaws.com/dynamo.docs.buildwithfern.com/d4167d87ad413eab02b80d20dec1ac3a3b2382ba6e37695f4430b8e65c735b69/digest/snapshot/dynamo-snapshot-lifecycle.webp?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6KXJSKKNFOCF7G4B%2F20260726%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20260726T002941Z&X-Amz-Expires=604800&X-Amz-Signature=2a49bb603980569cbee1aec7a00eb43e9e1f5cb722226c54be5a7b71a0e8cbc9&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)

Cold-starting inference replicas on Kubernetes can take minutes while engines load weights, warm kernels, and compile graphs. In our blog post, [NVIDIA Dynamo Snapshot: Fast Startup for Inference Workloads on Kubernetes](https://developer.nvidia.com/blog/nvidia-dynamo-snapshot-fast-startup-for-inference-workloads-on-kubernetes/), we introduce Dynamo Snapshot, a checkpoint/restore approach that combines `cuda-checkpoint`, CRIU, and a privileged `snapshot-agent` DaemonSet to restore warm workers from shared storage. We also walk through KV cache unmapping, CRIU restore optimizations, and GPU Memory Service (GMS), which bring the `gpt-oss-120b` prototype below five seconds and reduce startup time by 21x.