Eks To Agentcore

Phase 2: Scaffold

1. Install AgentCore CLI: npm install -g @aws/agentcore
2. Create project: agentcore create --name <AgentName> --defaults
3. Use generate_agentcore_project MCP tool for customized scaffold commands
4. Choose build type:
   • CodeZip (default, recommended) — no Dockerfile needed
   • Container — only if agent has heavy system-level dependencies (CUDA, custom native libs)

Phase 3: Migrate Code

1. Copy agent source to app/<AgentName>/
2. Create main.py with AgentCore Runtime wrapper — use generate_main_py MCP tool
3. The wrapper pattern for Strands agents:

   from strands import Agent
   from bedrock_agentcore.runtime import BedrockAgentCoreApp
   
   agent = Agent(model="...", system_prompt="...", tools=[...])
   app = BedrockAgentCoreApp()
   
   @app.entrypoint
   def invoke(payload):
       response = agent(payload.get("prompt", ""))
       return response.message["content"][0]["text"]
   
   if __name__ == "__main__":
       app.run()
   

4. Update pyproject.toml — remove K8s-specific deps (gunicorn, uvicorn, kubernetes client)
5. Remove web framework serving code (Flask/FastAPI) — AgentCore handles HTTP natively

Phase 4: Migrate Configuration

1. Secrets → agentcore add credential --name <svc> --api-key <key> or --type oauth
2. ConfigMaps/env vars → agentcore.json configuration
3. Networking:
   • Internet-only APIs → "networkMode": "PUBLIC" (default)
   • Private resources (RDS, ElastiCache) → "networkMode": "VPC"
4. Memory/state (Redis, DynamoDB) → agentcore add memory --strategies SEMANTIC,SUMMARIZATION
5. IRSA → AgentCore Identity (CDK creates execution roles automatically)

Phase 5: Test & Deploy

1. Test locally: agentcore dev then agentcore dev "test prompt"
2. Preview: agentcore deploy --plan
3. Deploy: agentcore deploy
4. Verify: agentcore status and agentcore invoke --runtime <AgentName> "test"
5. Set up CI/CD — use generate_cicd_pipeline MCP tool

Phase 6: Cutover

1. Run both EKS and AgentCore agents in parallel
2. Route traffic gradually using weighted routing
3. Monitor via agentcore logs and agentcore traces list
4. After validation, scale down EKS: kubectl scale deployment <name> --replicas=0
5. Clean up K8s resources (Deployment, Service, Ingress, HPA, Secrets, ConfigMaps)

Key Decisions

Common Pitfalls

• AgentCore Memory is NOT available during local dev (agentcore dev). Deploy first to test memory.
• Entrypoint must be main.py (or configured in agentcore.json)
• Remove Flask/FastAPI/uvicorn — AgentCore Runtime handles HTTP serving
• Extended execution supports up to 8 hours. Decompose longer workloads.
• First deployment takes a few minutes while CDK bootstraps your account
• EKS tokens expire every ~15 minutes. Refresh with aws eks update-kubeconfig

MCP Tools Reference

This skill works with the eks-to-agentcore MCP server. Available tools:

Guidelines

• Always specify a namespace when scanning (scan_eks_cluster(namespace="agents")) to follow least-privilege principles
• Env var values are never captured — only names are used for heuristic analysis
• Start with the simplest agent (low complexity) as a pilot migration
• Use CodeZip build type unless you have a specific reason for Container
• Keep the EKS agent running in standby for 1-2 weeks after cutover as a rollback option
• Use agentcore deploy --plan before every deployment to preview changes