Ray Serve + GCP
by Anyscale · open-source · Last verified 2026-03-17
Ray Serve deploys scalable model serving applications on Google Cloud Platform using GKE and Vertex AI infrastructure, with Ray's distributed runtime managing replica placement, traffic splitting, and resource scheduling across GPU node pools. The integration supports multi-model serving graphs, A/B rollouts, and seamless scale-to-zero on GCP Spot instances for cost optimization.
https://docs.ray.io/en/latest/serve/index.html ↗B
B—Above Average
Adoption: B+Quality: AFreshness: ACitations: BEngagement: F
Specifications
- License
- Apache-2.0
- Pricing
- open-source
- Capabilities
- distributed-serving, traffic-splitting, autoscaling, multi-model-graphs, gke-integration
- Integrations
- gcp-gke, gcp-vertex-ai, kubernetes, vllm
- Use Cases
- multi-model-serving, ab-testing-models, production-llm-api, cost-optimized-inference
- API Available
- Yes
- Tags
- deployment, gcp, kubernetes, distributed-serving, autoscaling
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
62.5Adoption
72
Quality
87
Freshness
87
Citations
65
Engagement
0