ใช้ Spot Instances สำหรับการฝึก

Cloud providers rent out spare capacity at a deep discount. These spot instances can cost up to ninety percent less than on-demand machines.

The catch is the provider can reclaim a spot instance with little warning. This interruption is why spot is cheap, and why you must plan for it.

Training is a great fit for spot because it runs in the background, not in front of users. A paused job hurts far less than a dropped live request.

The key habit is saving progress before an interruption strikes. Checkpointing writes model weights and optimizer state to durable storage as you go.

When a new spot instance starts, load the last checkpoint and keep going. Resuming turns a reclaimed machine into a brief pause, not lost work.

Save checkpoints to durable storage like S3, never the local disk. When the instance dies, your progress must survive outside it.

Most clouds send a short warning before reclaiming a machine. Catch that termination notice and flush a final checkpoint while you still can.

If one machine type runs out, your job stalls. Requesting several types and zones lifts your odds of grabbing cheap capacity.

Spot fits training, but not always low-latency serving users depend on. Keep inference on on-demand or reserved capacity for reliability.

Managed services like SageMaker Managed Spot or Kubernetes can auto-resume jobs for you, hiding most of the interruption pain.

Spot trades cost for occasional delays. For a deadline-critical run, the safer on-demand price can be worth paying.

Let us make sure spot training stays safe.

You learned why spot is cheap, checkpointed often to durable storage, resumed after interruptions, and kept serving on stable compute. 💰