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 Optimizing AI Workloads for Multi-Cloud Environments with Rafay and GPU PaaS

Optimizing AI Workloads for Multi-Cloud Environments with Rafay and GPU PaaS

November 27, 2024 / by Mohan Atreya

Rafay’s platform enables you build a GPU PaaS for AI workloads so you can confidently operate machine learning models, generative AI, and neural networks at scale. It orchestrates your hybrid and multi-cloud computing resources, improves operational flexibility, and… Read More

Image for Operationalizing AI: Solutions to Machine Learning Workflow Automation Challenges

Operationalizing AI: Solutions to Machine Learning Workflow Automation Challenges

November 15, 2024 / by Mohan Atreya

Machine learning (ML) has emerged as a transformative force, enabling organizations to derive critical insights, enhance customer experiences, and make data-driven predictions. However, operationalizing machine learning workflows presents significant challenges, especially for enterprises with complex, cloud-based infrastructures. Machine… Read More

Image for Achieving Optimal AI Performance with Tuning-as-a-Service

Achieving Optimal AI Performance with Tuning-as-a-Service

November 12, 2024 / by Mohan Atreya

Tuning-as-a-Service (another TaaS but not to be confused with Training-as-a-service) is a cloud-based solution that optimizes AI models by automating the adjustment of hyperparameters to enhance model accuracy, efficiency, and overall performance. By leveraging advanced algorithms and scalable… Read More

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