Scalable Compute

Compute big tasks, small tasks, and parallel tasks in the cloud without hassle.

Compute anything, change nothing

ML, AI, and data apps have varied compute needs: Some require small-scale compute, some many CPU cores, some need GPUs, and some plenty of memory.

With one line of code, you can annotate your functions with their resource requirements. Existing code and libraries work without changes. No need to learn new paradigms or frameworks.

Scalable pool of compute resources

The Outerbounds Platform comes with an auto-scaling, fully managed compute cluster, deployed on your AWS account, optimized for Metaflow workloads.

Use the cluster flexibly for all compute needs from 10,000-way hyperparameter sweeps and data processing with TBs of RAM to multi-GPU model training.

Minimize cloud costs

Workloads are monitored to improve utilization, optimize instance pools, attribute costs and help minimize your cloud invoices.

Utilize cloud savings plans, spot instances, and right-sized instances for optimal cost.

Increase productivity through easily accessible compute

Outerbounds has proven to be transformative for us. Our teams go over rigorous experiments while developing models. The platform has allowed us to execute and train models without the burden of worrying about infrastructure. The ability to scale our operations both vertically and horizontally, and launch parallel experiments and pipelines, has made Metaflow and Outerbounds an appealing choice for our Machine Learning team, significantly enhancing our productivity.

Soma S Dhavala, Director, Wadwhani Institute for AI

Test scalable compute in the Metaflow sandbox

Test scalable compute in the Metaflow sandbox