DEVOPSdigest

Rafay Systems announced the availability of the Rafay Cloud Automation Platform — the evolution of its Kubernetes Operations Platform — to enable platform teams to deliver automation and self-service capabilities to developers, data scientists and other cloud users.

This new version combines Rafay’s Kubernetes and environment management offerings into a single platform. It provides organizations with a comprehensive solution for building self-service automation to provision and manage the full stack (i.e., infrastructure, environments, clusters, applications, etc.) which is required to support modern applications — across any environment including public clouds, private data centers and the edge. The Cloud Automation Platform facilitates, for example, a way for platform teams to provide self-service infrastructure templates for generative AI use cases to developers and data scientists, while being able to effortlessly manage continuous operations of AI and machine learning (ML) applications. Enterprise platform team members, developers and data scientists attending AWS re:Invent 2023 in Las Vegas this week can see live demonstrations at Rafay’s booth 918.

“The Achilles’ heel of today’s cloud modernization journey is the inherent complexities in automating and templatizing cloud environments and Kubernetes — but these complexities shouldn’t be delegated to developers,” said Haseeb Budhani, CEO and co-founder of Rafay Systems. “To innovate faster, developers should be shielded from these complexities by enterprise platform teams. Rafay’s Cloud Automation Platform provides an automation solution for platform teams, bridging the complexity gap so enterprises can focus on rapid innovation rather than cloud environment and Kubernetes management.”

The Rafay Cloud Automation Platform allows platform teams to build self-service automation for their top initiatives, including:

- AI and Data Sciences Workbenches as a Service: Platform teams provide data scientists and researchers with AI and ML infrastructure on demand to accelerate their company’s AI journey and jumpstart AI and ML experimentation.

- Landing Zones and Environments as a Service: Developers have the ability to provision and gain access to cloud landing zones and environments including all service dependencies with policy such as time-to-live included.

- Namespaces and Clusters as a Service: Developers can access their own namespace or entire cluster with guardrails built in such as role-based access control, network policy, cost management and more.