I just published a deep-dive on building multi-agent systems for platform engineering using Google's Agent Development Kit (ADK) on GCP.
What's Covered
- ADK Architecture – Agents, Tools, and Orchestration patterns explained through a distributed systems lens
- 7 Architectural Patterns – From Hierarchical Orchestration to Market-Based Auctions, with guidance on when to use each
- Platform Engineering Use Cases – AI SRE, Intent-to-Infrastructure, Self-Healing Infrastructure
- Assessment Framework – 6 pillars adapted from AWS WAF and Microsoft CAF for evaluating multi-agent implementations
- Implementation Roadmap – A 3-phase approach from foundation to scale
Key Metrics from Real Implementations
| Metric | Result |
|---|---|
| MTTR Reduction | 85% (4.2 hrs → 38 min) |
| Incident Prevention | 78% before customer impact |
| Infrastructure Cost Savings | 23% |
| Annual Savings | $1.8M+ |
The Core Insight
Multi-agent systems are distributed systems with intelligence. Apply your microservices knowledge, add reasoning capabilities, and you're 80% there.
If you're a cloud engineer, platform engineer, or SRE exploring how multi-agent AI fits into your infrastructure strategy, this one's for you.
👉 Read the full article: Building Multi-Agent Systems on GCP: An Architectural Patterns Framework
Would love to hear your thoughts, especially if you're already experimenting with ADK or multi-agent patterns in production. What use cases are you exploring?
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