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 Powering GPU Cloud Billing: Rafay + Monetize360 Integration

Powering GPU Cloud Billing: Rafay + Monetize360 Integration
June 16, 2025 / by Mohan Atreya

In the fast-evolving world of GPU cloud services and AI infrastructure, accurate, flexible, and real-time billing is no longer optional — it’s mission critical. That’s why Rafay has partnered with Monetize360 to deliver an end-to-end pricing, billing, and revenue management… Read More

Image for Choosing the Right Fractional GPU Strategy for Cloud Providers

Choosing the Right Fractional GPU Strategy for Cloud Providers
July 14, 2025 / by Mohan Atreya

As demand for GPU-accelerated workloads soars across industries, cloud providers are under increasing pressure to offer flexible, cost-efficient, and isolated access to GPUs. While full GPU allocation remains the norm, it often leads to resource waste—especially for lightweight or intermittent… Read More

Image for Demystifying Fractional GPUs in Kubernetes: MIG, Time Slicing, and Custom Schedulers

Demystifying Fractional GPUs in Kubernetes: MIG, Time Slicing, and Custom Schedulers
July 11, 2025 / by Mohan Atreya

As GPU acceleration becomes central to modern AI/ML workloads, Kubernetes has emerged as the orchestration platform of choice. However, allocating full GPUs for many real-world workloads is an overkill resulting in under utilization and soaring costs. Enter the need for fractional… Read More

Want Free Access?

Sign-up for free and try all the features
of the Rafay PaaS.

Sign Up Now