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Eon uses Amazon Bedrock AgentCore gateway to unify multi-cloud investigation tools

Eon built a single Model Context Protocol (MCP) gateway on Amazon Bedrock AgentCore to replace per‑tool credentials and local MCP servers across AWS, Azure and Google Cloud. The managed gateway provides identity federation via Amazon Cognito, Cedar‑based least‑privilege policies, and cross‑account connectivity without VPC peering or PrivateLink. Developers and an autonomous SRE agent running…

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Key points

  • Onboarding time fell from roughly two days to about two minutes using a single MCP gateway.
  • Unified access across AWS, Azure, and GCP removes VPC peering, PrivateLink, and per‑tool credential management.
  • Cedar policies enforce least‑privilege read/write separation for over 100 engineers and autonomous agents.

The new architecture cut onboarding time for new engineers from roughly two days of credential setup to about two minutes. Over 100 developers and autonomous agents have used the gateway for around 10,000 sessions, and Eon reports storage‑cost reductions of up to 50 % in its internal measurements. Cedar policies are managed as code in GitHub, allowing fine‑grained read/write control per SSO group and per‑agent identity.

Eon’s experience shows that a managed AgentCore gateway can simplify multi‑cloud tool integration, eliminate network‑level overhead, and provide secure, policy‑driven access for both humans and AI agents.

The story so far

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  1. Eon uses Amazon Bedrock AgentCore gateway to unify multi-cloud investigation toolsthis story
Full story from AWS Machine Learning Blog · by Dor Shaboy primary sourceOpen source ↗

How Eon built multi-cloud investigation with an MCP Gateway on Amazon Bedrock AgentCore

AWS Machine Learning Blog · 20 October 2026

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This text was published by AWS Machine Learning Blog and written by Dor Shaboy. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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