Cloud Pathways is now generally available on GKE as a core component of the Google Cloud AI Hypercomputer. It was initially developed by Google DeepMind to train frontier models like Gemini. Pathways is a distributed machine-learning runtime designed for large, diverse accelerator fleets. Over 130 million Cloud TPU chip-hours have been processed using Pathways on GKE in the last 90 days. Every Google Cloud customer can now leverage its single-controller runtime, colocated Python sidecars, and elastic fault tolerance. A preview integration with Cluster Director extends Cloud Pathways to Slurm clusters for unified JAX execution and interactive notebooks. Cloud Pathways solves the complexity of traditional multi-controller setups for scaling AI workloads across thousands of accelerators. It replaces multi-controller management with a unified single-controller architecture built on the open-source Interim Framework Runtime. This allows a single JAX client process to orchestrate multiple large TPU slices as if locally connected. Key features include single-controller orchestration, colocated Python sidecars for compute-intensive logic, and resilient and elastic training. It also offers an interactive mode and Shared Pathways Service for flexible multi-user access. Leading AI labs and enterprises, such as a major consumer technology company and ZenteiQ, are already using Cloud Pathways for mission-critical production workloads. Cloud Pathways is available today in all Google Cloud regions supporting Cloud TPU v5e, v5p, Trillium, and Ironwood on GKE.