Build highly scalable serverless LangGraph multi-agent systems in AWS with Amazon Bedrock AgentCore
📰 AWS Machine Learning
Learn to build scalable serverless LangGraph multi-agent systems in AWS using Amazon Bedrock AgentCore for generative AI applications
Action Steps
- Design a LangGraph architecture using Amazon Bedrock AgentCore Memory for efficient data storage and retrieval
- Implement serverless functions in AWS to integrate with LangGraph Agents and Amazon Bedrock AgentCore Observability for real-time monitoring
- Configure Amazon Bedrock AgentCore to orchestrate LangGraph Agents and enable scalable multi-agent interactions
- Test and validate the serverless LangGraph multi-agent system using Amazon Bedrock AgentCore
- Deploy and manage the system using AWS services such as AWS Lambda and Amazon CloudWatch
Who Needs to Know This
Machine learning engineers and architects can benefit from this solution to build highly scalable and serverless multi-agent systems, while DevOps teams can leverage Amazon Bedrock AgentCore for streamlined management and monitoring
Key Insight
💡 Amazon Bedrock AgentCore enables efficient and scalable management of LangGraph multi-agent systems in a serverless architecture
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Build scalable serverless LangGraph multi-agent systems in AWS with Amazon Bedrock AgentCore #AWS #MachineLearning #Serverless
Key Takeaways
Learn to build scalable serverless LangGraph multi-agent systems in AWS using Amazon Bedrock AgentCore for generative AI applications
Full Article
In this post, we provide a solution to build highly scalable, serverless multi-agent generative AI systems on AWS using LangGraph Agents as orchestrators integrated with Amazon Bedrock AgentCore Memory and Amazon Bedrock AgentCore Observability.
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