The expanded architecture uses Amazon Bedrock AgentCore Gateway to manage target registries and process incoming authorization grants from Okta. Instead of placing authorization checks directly inside tool code, the system enforces a default-deny Cedar policy set evaluated directly at the Gateway before reaching Model Context Protocol servers. This setup accommodates agents across different hosting environments, including Amazon Elastic Kubernetes Service. Implementing the additions takes roughly 90 minutes using tools such as Docker and kubectl alongside necessary permissions.
Key points
Centralizing access policies at the Gateway prevents agents from needing direct access to…: Centralizing access policies at the Gateway prevents agents from needing direct access to provider secrets.
Agents hosted in different environments like Amazon Elastic Kubernetes Service can be sec…: Agents hosted in different environments like Amazon Elastic Kubernetes Service can be secured under the same model.
Audit decisions are consolidated into CloudWatch through OpenTelemetry spans and Okta Sys…: Audit decisions are consolidated into CloudWatch through OpenTelemetry spans and Okta System Log streaming via Amazon EventBridge.
Sources checked by our analysis pipeline: 1
Artificial Intelligence
Govern AI agent access with Okta Cross App Access and Amazon Bedrock AgentCore – Part 2
In Part 1, you built a task agent on Amazon Bedrock AgentCore, a platform to build, connect, and optimize agents at scale, with any framework or model. The agent runs on Amazon Bedrock AgentCore runtime, a capability of Amazon Bedrock AgentCore, and acts for signed-in users through Okta Cross App Access (XAA). Okta decided which agent might act for which user, and Amazon Bedrock AgentCore Identity, a capability of Amazon Bedrock AgentCore, redeemed Okta’s grant inside the agent. That proves the governance mechanism, and it runs on a deliberately small topology: one agent, two Model Context Protocol (MCP) servers, and the authorization check written into each server.
The mechanism scales. The topology doesn’t. Three things that are fine for one agent and two tools become the work in an enterprise with hundreds of agents and thousands of tools:
What Part 1 does | Why it stops scaling | What Part 2 does instead |
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