RayDog
The Ease of Ray, Supercharged by YellowDog
Seamlessly scale AI/ML workloads from prototype to production—without infrastructure barriers or code changes.
Try RayDog Today with $500 in Free Cloud Credits
Sign-up now to experience RayDog’s orchestrated compute power – scale AI and ML workloads from prototype to production with ease.
Why RayDog?
Ray is the open-source framework that simplifies distributed AI and ML development.
RayDog takes it further—delivering instant orchestration, intelligent autoscaling, and enterprise-grade reliability through YellowDog’s dynamic workload manager. With RayDog, innovation scales without limits.
The RayDog Advantage
Infrastructure Management
Fully managed compute infrastructure
Scalability
Seamlessly scale from local to 10,000 nodes
Autoscaling
Dynamic upscaling and automated downscaling
Multi-Cloud Support
Provisions across cloud and regions
Cost Optimization
Smart compute bidding + reclamation of idle resources
Security & Compliance
Policy-based governance and protection
Developer Experience
Ray-ready out of the box—no code changes
Observability & Monitoring
Telemetry on performance and cost
Turn Compute Into Competitive Advantage
RayDog enables financial institutions, AI innovators and data-driven research teams to move from managing infrastructure to driving innovation. By combining the ease of using Ray with YellowDog’s orchestrated compute platform, RayDog delivers speed, scale, and efficiency where it matters most.
“In quantitative finance, time to market, speed and scale are everything. Ray has become a popular choice for its ease of use and excellent developer experience. Using RayDog to combine it with YellowDog’s powerful compute infrastructure, we can write and test new data processing applications on local datasets, then seamlessly scale them to massive compute power with no code changes. This gives us the power to instantly turn up the dial up when performance matters most — ensuring we hit our objectives while giving our engineers the freedom to innovate faster.”
-Jon Fautley, Head of Cloud Infrastructure, Qube Research & Technologies
Flexible Cluster Topologies
Supports single AZ, multi-AZ, and multi-region Ray clusters with intelligent provisioning and Spot/on-demand balancing.
RayDog Builder & Autoscaler
Choose between manual or automated scaling modes; integrates seamlessly with Ray’s native Autoscaler via YAML config.
Superior Scale & Stability
Reduces Ray head-node load by abstracting infrastructure; proven stable up to ~10K nodes per cluster.
Cost-Efficient Orchestration
Leverages spot instances with advanced preemption handling and Waterfall provisioning strategies.
Multi-Cloud & Hybrid Support
Build clusters across multiple clouds or hybrid setups using YellowDog Worker Pools.
Enterprise-Grade Tooling
Includes full observability, governance, and API/SDK support for advanced operations.
Dive Deeper: Read the RayDog Whitepaper
Explore how RayDog pushes the boundaries of distributed computing—covering topology options, performance optimisations, and large-scale orchestration techniques for Ray workloads.
Kickstart your RayDog journey with $500 in Free Cloud Credits
Get hands-on with RayDog and experience enterprise-grade Ray orchestration at no cost. We’re offering $500 in free cloud credits to help you build, test and scale your first RayDog workloads today.