Connecting AI agents with unstructured data using Google Cloud Storage MCP Servers
Enterprises need to integrate unstructured data from Google Cloud Storage into AI agent systems while maintaining security, standardization, and efficient context retrieval at scale.
Experimenting with TPUs, GKE Managed DRANET, and Multi-cluster Inference Gateway
Ensuring high availability and service continuity when AI inference workloads fail in one region while maintaining access to the service across multiple regions.
Scaling AI Agents: A Step-by-Step Guide to Deploying ADK on GKE Autopilot
Moving AI agents built with Google's Agent Development Kit from local prototypes to production-ready, scalable infrastructure.
A Guide to AI Cold Starts on Cloud Run
Managing startup latencies up to 20 seconds for AI workloads on Cloud Run serverless GPUs, which causes poor user experience and is driving developers back to traditional container orchestration.
Developer's guide to Gemini Enterprise and A2UI integration
Conversational AI agents lack a standard way to render rich UI components (date pickers, maps, multi-select lists) within chat interfaces, forcing agents to rely only on text or markdown responses.