Scaling Cloud Migrations with Agentic AI on Amazon Bedrock AgentCore

AWS Professional Services has developed a multi-agent framework on Amazon Bedrock AgentCore to address common bottlenecks in large-scale enterprise cloud migrations. Traditionally, discovery, infrastructure code generation, and post-migration operations are time-consuming, often taking weeks per application. This framework automates these processes through purpose-built AI agents, reducing IaC development time from 3-4 weeks to minutes across a portfolio of over 300 applications.

The architecture involves four key agents: the Intake Agent for automated discovery, the Infrastructure as Code (IaC) Agent for generating secure and standards-compliant infrastructure code, the Migration Intelligence and Governance Agent for portfolio-wide reporting and assessments, and the Site Reliability Engineering (SRE) Agent for proactive post-migration operations. These agents operate within Amazon Bedrock AgentCore, which provides a scalable, secure platform for building, connecting, and optimizing AI agents.

The framework leverages the Strands Agents SDK and Model Context Protocol (MCP) server patterns, with each agent calling MCP tools via the AgentCore Gateway. This setup ensures secure, auditable, and compliant operations, with shared context stored in AgentCore memory to track progress across applications.

The Intake Agent automates the initial discovery phase by ingesting architecture documentation, inventories, and dependency maps, producing target AWS architectures and migration patterns. The IaC Agent then interprets this data to generate infrastructure code based on organizational standards, which is validated through Amazon Bedrock's Guardrails policies before deployment. The Migration Intelligence and Governance Agent provides ongoing visibility into migration progress and compliance, integrating with tools like Jira, Confluence, and Webex.

Post-migration, the SRE Agent monitors application performance via Amazon CloudWatch, enabling proactive management and automated remediation, thus shifting teams from reactive firefighting to continuous improvement.

The implementation has demonstrated significant results, notably reducing IaC development time from weeks to minutes, ensuring pattern consistency, and maintaining security compliance automatically. The framework supports a secure, efficient, and scalable migration process, aligning with enterprise security standards and enabling rapid, reliable cloud adoption.

For organizations undertaking large-scale migrations, this approach offers a practical, measurable pathway to accelerate timelines, improve governance, and reduce operational overhead, leveraging purpose-built AI agents and secure cloud-native infrastructure.