AgentOps: Operationalize agentic AI at scale with Amazon Bedrock AgentCore

This article presents AgentOps, an operational discipline for deploying and managing agentic AI systems at scale using Amazon Bedrock AgentCore. It outlines best practices across four key pillars and provides a reference architecture for enterprise implementation.

• Governance & Security: Multi-account strategy, deterministic controls, identity management, and tool governance
• Build & Operations: Versioned artifacts, CI/CD pipelines for agents/tools/memory, containerized deployment to AgentCore Runtime
• Evaluation: Four-level assessment (tool, conversation turn, session outcome, system) with on-demand and online evaluation modes
• Observability: Four telemetry layers (agent, service, infrastructure, application) with CloudWatch dashboards and OpenTelemetry integration
• DevOps lifecycle integration: AgentOps considerations mapped across plan, develop, build, test, deploy, and maintain stages
• Multi-account architecture: Separate dev, pre-prod, production accounts with shared services for ECR, secrets, and monitoring
• Agent Registry: Centralized discovery and reuse of agents, tools, and MCP servers across organization

The article emphasizes treating agents as versioned, deployable artifacts with strict governance boundaries, comprehensive evaluation gates, and continuous production monitoring to ensure reliable agentic AI at enterprise scale.