Anyscale is a unified platform built to help businesses run large-scale machine learning and data workloads smoothly and reliably. Born from the creators of Ray, the open-source framework, Anyscale adds the governance, optimization, and developer experience needed to move projects from experimentation to production without unnecessary complexity. The company works across cloud providers, enabling teams to deploy and manage clusters on AWS, Google Cloud, or Kubernetes while maintaining flexibility and control over their infrastructure.
Developers can launch Ray clusters of any size using their preferred cloud resources and customize them for workloads that blend CPUs and GPUs. Instead of spending valuable time configuring infrastructure, they can focus on solving business problems and building products.
Keerti Melkote, CEO, believes this balance between sophistication and simplicity is what sets Anyscale apart. “Scaling should feel like a natural extension of your work,” he explains. “You should not be thinking about clusters, you should be thinking about ideas.”
Why Keerti Believes Scale Should Be Seamless
When we asked Keerti what drew him to Anyscale, he paused before answering. “I have always believed in the power of platforms that take away unnecessary complexity. At Aruba, we simplified networking for enterprises. With Anyscale, the opportunity is to do something similar for distributed computing. Ray was already a breakthrough in open source, but many organizations needed more to bring it into production at scale. That is where Anyscale comes in.”
The company provides more than just cluster management. It layers on features like the RayTurbo compute engine, which makes workloads run more efficiently, and advanced observability tools that allow teams to monitor performance across clouds. Enterprises can enforce governance, restrict access, and comply with industry standards while still moving quickly.
We asked Keerti how Anyscale approaches enterprise readiness. “Businesses need confidence that their data and systems are secure,” he says. “We have certified compliance with SOC 2 Type 2, and we designed Anyscale with a shared responsibility model. Customers keep their data in their cloud, in the regions of their choice, while we manage the infrastructure that makes workloads run seamlessly. This balance keeps control where it belongs but removes the heavy lifting.”
Designing for the People Who Build
The Anyscale console includes tools that are instantly familiar to developers. Workspaces feel like an extension of environments they already know, with hosted options for VS Code, Jupyter Lab, and terminals. These workspaces make interactive development smoother, while also allowing easy connection to local IDEs.
We asked Keerti why this developer-first approach matters. “Developers are the ones bringing ideas to life. If the environment slows them down or feels foreign, they spend time fighting tools instead of building solutions. Our goal was to make it seamless. You can prototype in a workspace, package your code, and then move it into production jobs or services without reconfiguring everything. It shortens the path from idea to deployment.”
This simplicity becomes critical for teams handling machine learning workloads, where iteration speed can make or break a project. By using cached container images and optimized scaling, Anyscale ensures clusters can expand or contract on demand, even taking advantage of spot instances for cost efficiency. The end result is speed without runaway costs.
Turning Ideas into Production Workloads
The journey from experimentation to production often involves a shift from running training jobs to serving models at scale. Anyscale supports this full lifecycle. Developers can run training workloads or data processing pipelines as jobs, triggered manually or automated through CI/CD systems. Once a model is ready to serve, they can deploy it as a managed service through Anyscale, benefiting from zero downtime upgrades and dynamic scaling.
Keerti sees this integration as central to Anyscale’s value. “The challenge is not just getting a model trained. It is keeping it reliable in production. Our services layer is built on Ray Serve, but we added the tools needed for high availability, monitoring, and debugging. This means developers can serve multiple models, handle production traffic, and scale clusters up and down without disruption. It gives them confidence.”
That confidence translates into business outcomes. Enterprises can experiment, launch, and scale AI-powered applications faster, while startups can compete with larger players without the overhead of managing their own infrastructure.
Making Advanced Computing Accessible
Anyscale is more than a platform for scaling workloads. Keerti sees it as part of a broader movement to democratize access to advanced computing. “We want to make distributed computing as simple and accessible as possible. When teams of all sizes can run workloads at scale, innovation accelerates. New ideas come from everywhere, not just from the largest companies.”
The company’s consumption-based model helps reinforce this accessibility. Customers only pay for the compute resources they use, which makes it easier for smaller teams to get started. At the same time, larger enterprises benefit from fine-grained controls, priority scheduling, and governance features that support mission-critical deployments.
Professional services round out the offering, including dedicated support and customized training. Keerti emphasizes that these services are about enabling customer success rather than upselling. “Every organization is at a different point in their journey. Some need guidance, some just need reliability. Our role is to meet them where they are and help them move faster.”
What the Future Holds for Anyscale
When asked what excites him most about the road ahead, Keerti reflects on the future of the developer experience. “I believe we are just beginning. As workloads get more complex, the tools need to get simpler. Our mission is to keep reducing friction, so people can focus on what really matters.”
That philosophy echoes the company’s origins with Ray, where the goal was to make distributed computing easier for developers everywhere. Anyscale builds on that foundation by offering the reliability, governance, and scale that enterprises demand, without losing sight of developer needs.
As the conversation draws to a close, Keerti leaves us with a final thought. “Technology should empower, not distract. If we do our job well, people will spend less time worrying about infrastructure and more time creating value. That is what Anyscale is all about.”
Keerti Melkote, CEO, Anyscale
