How to Migrate from AWS to Harch Corp GPU Cloud
Complete migration guide: move AI workloads from AWS to Harch Corp. Save 30-50% and reduce carbon by 85%.
Assess your AWS workloads
Identify GPU workloads to migrate: EC2 P4/G5 instances, SageMaker training jobs, ECS/EKS GPU tasks. Document instance types, AMIs, storage volumes, and networking requirements.
Create Harch Corp account
Sign up at harchcorp.com. Verify your account. Create API keys. Familiarize yourself with the dashboard and CLI tools.
Provision equivalent resources
Map AWS instances to Harch Corp: p4d.24xlarge (8x A100) → Harch 8x A100, p5.48xlarge (8x H100) → Harch 8x H100. Provision storage (equivalent to EBS), networking (equivalent to VPC).
Transfer your data
Use rsync or AWS S3 sync to transfer data. For large datasets, Harch Corp provides direct transfer from S3. Estimate transfer time: 1TB over 1Gbps = ~2.5 hours.
Update your code
Update endpoints, IAM roles, and SDK calls. Harch Corp uses OpenStack-compatible API (similar to AWS). Most code changes are minimal: update instance IDs, regions, and API endpoints.
Test your workloads
Run test jobs on Harch Corp before switching production. Verify: training convergence, inference latency, data pipeline, auto-scaling. Benchmark performance vs AWS.
Switch production traffic
Use DNS (Route 53) to gradually switch traffic: 10% → 50% → 100% over 1-2 weeks. Monitor for issues. Keep AWS as fallback for 30 days.
Decommission AWS resources
After 30 days of stable operation on Harch Corp, terminate AWS instances, delete EBS volumes, clean up S3 buckets. Save 30-50% on GPU costs and reduce carbon by 85%.