Build · 3 weeks
AWS AgentCore Quickstart
Production AI agent infrastructure on AWS — deployed, governed, and observable in 3 weeks. Managed runtime with Amazon Bedrock integration, guardrails, and enterprise-grade security for autonomous agent workflows.
View quickstart on GitHubWeek 1 — Foundation
- AgentCore runtime deployment and configuration
- IAM roles and resource policies for agent identity
- VPC deployment with private subnets and encryption
- Amazon Bedrock model access and integration
- Security baseline — KMS, audit trail, network isolation
Week 2 — Agent Development
- Memory and context management for stateful workflows
- Tool integration — Lambda functions, API connectors
- Guardrails — content filtering, token budgets, human-in-the-loop
- Agent tracing and session logging
- First agent deployed to staging environment
Week 3 — Production
- CI/CD pipeline for agent deployment and versioning
- Observability — CloudWatch metrics, performance dashboards
- Load testing and production validation
- Runbook and knowledge transfer
- Production go-live with monitoring enabled
Deliverables
What you walk away with
Production AgentCore Environment
Managed agent runtime deployed, secured, and ready for your autonomous AI workflows.
Agent Deployment Pipeline
CI/CD pipeline for agent versioning, testing, and promotion across environments.
Guardrails Configuration
Content filtering, token budgets, and human-in-the-loop gates — configured for your risk tolerance.
Observability Stack
Agent tracing, session logging, CloudWatch dashboards, and performance alerting.
IaC Codebase
Terraform — version-controlled, documented, and owned by your team.
Architecture Documentation
Decision log, security model, integration patterns, and operations runbook.
Associated AWS services
Platform coverage
Ready to deploy production AI agents on AWS?
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