High-Throughput LLM Serving with vLLM and Drizzle

How Drizzle:AI Integrates with the vLLM Production Stack

Drizzle provides an accelerated, expert implementation of the complete vLLM Production Stack on a secure and scalable Kubernetes platform (EKS, AKS, or GKE). We don’t just install a library; we deploy the entire ecosystem of open-source tools as recommended by the vLLM team. This allows you to harness the full power of this state-of-the-art inference solution without the implementation headaches.

Key Features of the Integration

State-of-the-Art Throughput: Leverage vLLM’s core PagedAttention technology to achieve significantly higher throughput for your LLM inference, reducing latency and serving more users with fewer resources.
Complete Production Stack: We deploy the full, recommended stack including vLLM for the inference engine and Ray Serve for scalable, production-ready model deployment.
Built-in Observability: Gain immediate insight into your model’s performance with integrated Prometheus for metrics collection and pre-configured Grafana dashboards for comprehensive observability.
Cost-Effective Scalability: By maximizing inference throughput and enabling intelligent autoscaling with Ray Serve, our vLLM integration dramatically reduces GPU costs, allowing you to serve powerful models in a cost-effective manner.