Analyzes current usage, recommends cost-saving measures, and applies optimizations to GKE workloads.

For teams running batch/HPC and AI/ML inference workloads on GKE with specialized hardware.

Assesses security requirements, identifies risks, and provides actionable recommendations for IAM, network, and data protection.

Deploy and optimize AI/ML inference workloads on GKE using GPUs, TPUs, and model servers.

For architects evaluating Google Cloud workloads against the Well-Architected Framework pillars: reliability, cost optimization, and operational excellence.