Building an AI Ops Assistant with Amazon Bedrock AgentCore
AWS ML Blog · rss · 2026-07-08
AWS Ops engineers typically spend 30-45 minutes troubleshooting issues across multiple consoles, docs, and manual tickets. This post explains how to build an automated AWS support assistant using Amazon Bedrock AgentCore to consolidate the troubleshooting workflow into a single conversational interface.
Core Architecture & Components:
- Orchestration Framework: Uses Strands Agents to build a Python app running on AgentCore Runtime, powered by the Amazon Nova Pro foundation model.
- MCP Integration: Connects to AWS documentation, AWS Support API, and AWS Service API via three separate MCP servers, enabling external tool calling.
- Gateway & Memory: AgentCore Gateway centrally manages tool endpoints and integrates re:Post community knowledge; AgentCore Memory maintains short-term context for the active session.
- Security & Infrastructure: Configures Bedrock Guardrails to filter harmful content, block Prompt injection, and mask PII. The React frontend (hosted on AWS Amplify) and backend are protected by API Gateway and WAF, with one-click deployment via a single CloudFormation script.
The article also shares two key code patterns for production-grade Agents: using asyncio.gather to parallelize MCP client initialization to reduce cold start latency, and implementing Memory context retrieval with an elegant timeout mechanism.
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