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title: Architect an open blueprint for cloud-native AI agents
description: A detailed architecture blueprint for running AI agents as cloud-native workloads on Kubernetes-based platforms like Red Hat OpenShift. The blueprint separates...
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# Architect an open blueprint for cloud-native AI agents

**[Red Hat Developer](https://daily.dev/sources/rhdev)** · 21 min read · 0 upvotes · 0 comments

## Summary

A detailed architecture blueprint for running AI agents as cloud-native workloads on Kubernetes-based platforms like Red Hat OpenShift. The blueprint separates the model (stateless inference), harness (agent loop and memory), and sandbox runtime (isolation) into distinct components with independent lifecycles. Key design principles include: sandboxed pods with three nested isolation rings (process, pod, hardware), workload identity via SPIFFE/SPIRE replacing static API keys, tool governance through an MCP Gateway using claims-based authorization, and a three-tier inference routing system separating security, cost, and efficiency decisions. Two deployment patterns are contrasted — Agent-as-a-Workload (one pod per agent) and Agent-as-a-Service (shared loop runtime). The blueprint emphasizes open interfaces (OpenAI-compatible APIs, MCP, agent-sandbox SIG, SPIFFE) to keep vendor choices reversible, while honestly cataloging open problems like multi-agent coordination, memory poisoning, and fleet-scale policy authoring.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://developers.redhat.com/articles/2026/07/20/architect-open-blueprint-cloud-native-ai-agents>

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---

Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#ai-agents](https://daily.dev/tags/ai-agents), [#mcp](https://daily.dev/tags/mcp), [#vllm](https://daily.dev/tags/vllm)

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