Introducing GKE agentic migration for AI-assisted EKS-to-GKE migrations with built-in governance

The useful part

Enterprises are increasingly standardizing on Google Kubernetes Engine (GKE) to run their most critical and AI-driven workloads. From Cloud Storage FUSE for high-throughput data access to custom compute classes (CCC) and advanced GPU slicing, GKE provides the scale and efficiency required for modern applications. Your platform teams must manually dissect sprawling infrastructure-as-code (IaC), navigate cloud-specific architectural differences, and build custom translation scripts.

How it works

• Raw models hallucinate non-existent resource properties, drop critical network or identity configurations, and lose context across interdependent files.
• The time platform engineers spend auditing, untangling, and debugging model errors ends up cannibalizing any upfront speed gains, creating manual toil and unpredictability.
• "For large enterprise clients, the biggest barrier to cloud modernization is execution risk and unpredictability.
• While your engineering teams often experiment with general-purpose LLMs to draft conversions, ad-hoc prompting quickly can become an operational trap.
• Today, we are excited to announce the open-source release of GKE agentic migration, a purpose-built agent plugin that replaces brittle, ad-hoc prompting with an AI-assisted migration pipeline protected by...

What to take from it

It gives our global engineering practice a provable, compiler-grade migration factory that slashes deli...

Details worth keeping

Unlike raw chat prompts that lose context and hallucinate configurations, Google's GKE agentic migration pairs the speed of generative AI with the deterministic guardrails enterprises need: structured state persistence, multi-persona boundaries between platform and app teams, and non-negotiable human approval gates.