Get Started

Free Cloud Credits

$500 in free YellowDog cloud credits to push your compute to the limit

Spin up production-grade clusters on YellowDog for high-scale workload orchestration – no YAML required. Just connect, run, and see how far your workloads can scale.

Trial overview

Get hands-on with YellowDog using a pre-provisioned trial environment backed by $500 in free cloud credits. Run real workloads, measure performance, and see how intelligent orchestration handles scale.

Quant-optimised

Quant workloads run on dedicated infrastructure optimised for speed and scale.

Python & Ray ready

Reuse existing Python and Ray code without rebuilding infrastructure.

Faster simulations

Run larger Monte Carlo simulations in less time using scalable compute.

Parallel workloads at scale

Turn backtesting parallelised workloads from weeks into hours.

Claim $500 to scale workloads smarter with intelligent orchestration

Get hands-on with YellowDog and experience enterprise-grade orchestration at no cost. Use $500 in free cloud credits to build, test, and scale compute-intensive workloads.

    What you get with your $500 YellowDog trial

    30 days free trial period

    Build, test, and run any type of AI/ML workload with $500 in free cloud credits.

    Pre-provisioned cloud resources

    Dedicated VPC, subnets, and security groups ready to go for your trial environment.

    Pre-configured YellowDog account

    CSTs, CRTs, allowances, groups, and image families set up for you from day one.

    Ray-ready machine images

    Machine images so clusters come up correctly that are ready configured for Ray.

    Sample workloads & demos

    Including Monte Carlo option pricing to start from a known-good baseline.

    Transparent tagging & accounting

    Every instance tagged with your trial details for easy cost and performance analysis.

    QUANTITATIVE RESEARCH

    Built for quant engineers who need fastest time to insight

    Accelerates quantitative research by orchestrating compute for faster backtesting, simulation, and model execution.

    Purpose-built for scale

    Quant workloads run on dedicated infrastructure that is optimsed for speed and scale.

    Python and Ray ready

    Reuse existing Python and Ray code without rebuilding infrastructure.

    Parallel workloads

    Orchestrated parallelised workloads so backtesting goes from weeks to hours.

    Faster Monte Carlo

    Run larger Monte Carlo simulations in less time using scalable compute.

    PLATFORM ENGINEERING

    Reduced friction for platform engineering teams

    Optimised infrastructure for compute-intensive workloads, without expanding platform complexity

    Optimised infrastructure

    Reliable, scalable compute capacity without expanding platform complexity.

    Spot orchestration

    Benefit from multi-region spot orchestration and slash compute costs.

    Production-ready

    Production-grade clusters to scale workloads quickly without operational overhead.

    AI/ML & batch jobs

    Use YellowDog as a controlled “high-performance compute lane” alongside your existing Kubernetes and cloud estate.

    GEN AI & INFERENCE

    Faster Gen AI modelling and inference

    Optimises compute for GenAI inference, delivering faster, more efficient model responses at lower cost.

    High-throughput

    Spin up production-grade inference clusters optimised for low latency.

    Multi-region spot

    Build and run even larger models on lower-cost multi-region compute.

    Production-ready

    Production-grade clusters to scale workloads quickly without operational overhead.

    AI/ML & batch jobs

    Use YellowDog as a controlled “high-performance compute lane” alongside your existing Kubernetes and cloud estate.

    See YellowDog and Ray in action

    Watch how we spin up production-grade clusters, distribute Python workloads at scale, and cut runtimes from hours to minutes—all from a single, Ray-native workflow.