How Google Uses gRPC

Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement application-level session tracking directly within the runtime to accurately measure the committed concurrent workload of active conversations. By feeding these precise session counts alongside standard CPU utilization metrics into a hybrid routing algorithm, infrastructure can effectively distribute stateful AI traffic and prevent individual backend bottlenecks.

Google Cloud has introduced a high-performance integration that connects Rapid Storage directly to PyTorch via the fsspec interface to eliminate AI training bottlenecks. By utilizing Google’s Colossus architecture and bidirectional gRPC streaming, the solution offers up to 15 TiB/s aggregate throughput and significant reductions in latency. These improvements allow developers to speed up total training time by 23% with zero code changes required beyond updating the storage bucket type.

The article announces the general availability of Gemini Code Assist in Apigee API Management, highlighting its AI-assisted capabilities for API development.

Google Cloud has announced the general availability of the Apigee APIM Operator, which enhances API management capabilities within Google Kubernetes Engine (GKE).

The article announces the general availability of the Apigee Extension Processor, a new capability that enhances Apigee's ability to manage and secure backend services and modern application archit...