Self-Service

Enabling Developer Self-Service

One-click experience for developers and data scientists to spin up new
environments on-premises or in the public cloud on-demand

Standardized Cloud Environments for Developers

Enable faster, error-free development by providing pre-approved, standardized resource templates.



Rafay’s Environment Manager allows developers to quickly provision compliant environments using standardized Infrastructure as Code (IaC) templates. This eliminates the need for custom-built environments, ensuring consistency across teams.

Faster
Time-to-Market

Developers can provision environments quickly and consistently.

Enhanced Accountability

Built-in compliance with security policies ensures resources are provisioned correctly every time.

How Rafay powers developer self-service for F2000 companies

With Rafay, developers only need to request infrastructure and deploy apps resulting in 46x faster
deployment and 50% less time-to-market for applications

How do you enable self-service?

Start with standardization to centrally enforce the latest add-ons, policies and
cost controls across all clusters and landing zone

Standardization Suite

Customer Results

58%
Reduction in time to deploy
0
Time wasted on infrastructure details

Latest Blogs from the Kubernetes Current

Image for Experience What Composable AI Infrastructure Actually Looks Like — In Just Two Hours

Experience What Composable AI Infrastructure Actually Looks Like — In Just Two Hours

April 24, 2025 / by

The pressure to deliver on the promise of AI has never been greater. Enterprises must find ways to make effective use of their GPU infrastructure to meet the demands of AI/ML workloads and accelerate time-to-market. Yet, despite making… Read More

Image for GPU PaaS™ (Platform-as-a-Service) for AI Inference at the Edge: Revolutionizing Multi-Cluster Environments

GPU PaaS™ (Platform-as-a-Service) for AI Inference at the Edge: Revolutionizing Multi-Cluster Environments

April 19, 2025 / by Mohan Atreya

Enterprises are turning to AI/ML to solve new problems and simplify their operations, but running AI in the datacenter often compromises performance. Edge inference moves workloads closer to users, enabling low-latency experiences with fewer overheads, but it’s traditionally… Read More

Image for Democratizing GPU Access: How PaaS Self-Service Workflows Transform AI Development

Democratizing GPU Access: How PaaS Self-Service Workflows Transform AI Development

April 11, 2025 / by Gautam Chintapenta

A surprising pattern is emerging in enterprises today: End-users building AI applications have to wait months before they are granted access to multi-million dollar GPU infrastructure.  The problem is not a new one. IT processes in… Read More

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