Post by Dani Mitchell
Sr WW Generative AI Solutions Architect at AWS | Making agentic AI simple to understand
Bedrock AgentCore Runtime got even simpler! ๐ Remember my post about deploying AI agents to production in 5 steps? Well, not long ago, the AgentCore Runtime team just made it even easier! ๐๐ฒ๐ณ๐ผ๐ฟ๐ฒ: You had to containerize your code and push to ECR. ๐ก๐ผ๐: Just zip your Python code (up to 250 MB) and upload to S3. That's it. ๐ฆโก๏ธ๐ชฃ Here's the streamlined flow: 1๏ธโฃ ๐๐๐ถ๐น๐ฑ ๐๐ผ๐๐ฟ ๐ฎ๐ด๐ฒ๐ป๐ ๐น๐ผ๐ฐ๐ฎ๐น๐น๐ (same as before - ANY framework, ANY model) 2๏ธโฃ ๐ฃ๐๐๐ต ๐๐ผ๐๐ฟ ๐ฐ๐ผ๐ฑ๐ฒ to ECR (Container image) or S3 (Zip file) 3๏ธโฃ ๐๐ฟ๐ฒ๐ฎ๐๐ฒ ๐๐ผ๐๐ฟ ๐ฟ๐๐ป๐๐ถ๐บ๐ฒ ๐ฎ๐ด๐ฒ๐ป๐ 4๏ธโฃ ๐๐ฟ๐ฒ๐ฎ๐๐ฒ ๐ฎ๐ป ๐ฒ๐ป๐ฑ๐ฝ๐ผ๐ถ๐ป๐ (still automatic!) 5๏ธโฃ ๐๐ป๐๐ผ๐ธ๐ฒ ๐๐ผ๐๐ฟ ๐ฒ๐ป๐ฑ๐ฝ๐ผ๐ถ๐ป๐! No Dockerfile. No container registry setup. Just Python code โ zip โ production. You still get all the enterprise goodies: โ Isolated microVMs per session โ Auto-sanitized after termination โ Full observability with AgentCore Observability The path to production-grade AI agents just got even smoother. If you've been waiting to move your agent off localhostโฆ it's never been easier! ๐ #AWS #AmazonBedrock #AgentCore #AgentCoreRuntime #AgenticAI