skypilot-multi-cloud-orchestration

Multi-cloud orchestration allows you to run distributed training jobs across AWS, GCP, and Azure by managing instance provisioning and execution automatically. This skill uses SkyPilot to deploy multi-node setups seamlessly across different cloud providers.

To reduce GPU training costs on cloud providers, this skill automatically selects the cheapest available instances and leverages spot instances with automatic recovery. This approach can cut training costs by up to 70% while maintaining fault tolerance.

Yes, you can use Kubernetes for machine learning workloads alongside AWS, GCP, and Azure. This multi-cloud orchestration skill supports Kubernetes as a platform for deploying and managing your ML jobs.

Spot instance recovery for distributed ML training works by automatically detecting preemptions and restoring the job. This managed orchestration skill ensures fault tolerance so your training continues without manual intervention if an instance is lost.

Yes, SkyPilot handles model serving and scaling after training using the integrated Sky Serve feature. It deploys and scales your trained ML models to make them accessible for inference.