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awslabs/agentcore-samples — reference samples, blueprints, and IaC for Amazon Bedrock AgentCore

ABCOctober 20, 20262 min read

AI Security

This repository aggregates sample code, reference blueprints, and infrastructure-as-code for Amazon Bedrock AgentCore. The README positions the project as framework- and model-agnostic and emphasizes a shift from the Bedrock AgentCore Starter Toolkit to the new AgentCore CLI; samples that still require the old toolkit live under legacy/ with a MIGRATION.md mapping to the new CLI workflow. What the repo actually provides The contents are organized for progressively larger scopes: quickstarts, focused capability examples, complete applications, integrations, and deployment automation. Notable items called out in the README include: getting-started/ — Python and TypeScript quickstarts that use the AgentCore CLI to create and deploy agents. features/ — capability-focused samples covering Runtime (serverless deployment), Gateway (convert APIs/services into tools), Identity (IdP integration), Memory (managed memory), Tools (code interpreter, browser, web search), Observability (OpenTelemetry), Evaluation, and Policy (Cedar). end-to-end/, integrations/, infrastructure-as-code/, and blueprints/ — combined reference apps, IdP/observability/data connectors, IaC templates (CloudFormation/CDK/Terraform), and full-stack reference applications for production deployment. Limits, missing evidence,

and production caveats The README and repo are practical: they supply examples, diagrams, and deployment templates. However, the repository does not publish performance benchmarks, cost models, latency/throughput targets, or SLA guarantees — all essential for production planning. Claims about being “securely and at scale” and “model-agnostic” are stated in the documentation but should be validated against your target LLM, traffic profile, and security/compliance requirements. Operational items you’ll need to validate before production include model performance (prompting and safety), end-to-end latency, concurrency limits for the serverless runtime, cost at scale, identity and access controls across integrated IdPs, data residency and retention controls, and the effectiveness of observability/evaluation hooks in real traffic.

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