Automate, Secure and Standardize Multi-Cloud Kubernetes Operations with Rafay

Streamline Kubernetes Cluster Lifecycle Management Across Public Clouds

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Challenges of Kubernetes Cluster Management in Public Clouds

Complexity of Multi-Cloud Operations

Each cloud provider (AWS, Azure, GCP, OCI) has its own set of tools and interfaces for Kubernetes management, leading to increased operational complexity.

Manual and Time-Consuming Updates

Regularly updating Amazon Machine Images (AMIs) and other components across clusters often requires significant manual effort, increasing the risk of errors and downtime.

Decentralized Provisioning Without Guardrails

SREs, developers, and other teams often provision clusters independently. Without centralized templates and policies, this leads to inconsistent configurations and operational risk.

Simplify Kubernetes Management Today

Why Choose Rafay for Kubernetes Cluster Lifecycle Management?

Centralized Multi-Cloud Management

Unified Control Plane:
Manage Kubernetes clusters across AWS, Azure, GCP, and OCI from a single interface, reducing complexity and improving operational efficiency. Consistent Policies:
Enforce uniform security, governance, and operational policies across all clusters, ensuring compliance and reducing the risk of configuration drift.

Automated Updates and Patching

Multi-Layer Upgrade Automation:
Automate updates across three key layers: Kubernetes versions (least frequent, most disruptive), Node OS images/AMIs (moderate frequency), Add-ons and in-cluster services (most frequent) Minimal Downtime with Automation:
Automated workflows minimize disruptions during updates, helping maintain high availability and streamline operations across environments.

Standardized Cluster Provisioning

Templates for Cluster Creation & Upgrades:
Use centrally defined templates for provisioning and updates to ensure consistency across teams and environments, and to reduce manual errors. Flexible Interfaces:
Support UI, GitOps, API, and Infrastructure-as-Code tools like Terraform to align with your team’s preferred workflows.

Role-Based Provisioning for Platform Teams

Governed Access for SREs and Developers:
Empower SREs and developers with governed provisioning access using predefined templates and policy guardrails. Portal & Workflow Integration:
Integrate seamlessly with identity providers (IDPs), internal developer portals (e.g., Backstage), and ITSM systems like ServiceNow for streamlined cluster requests and provisioning workflows.

Upgrade Your Multi-Cloud Strategy

Why companies use Rafay for CLM in public clouds

Free your team from performing menial tasks in public clouds

Before

After

Before Periodic Cluster Upgrades

After E2E automatic of cluster upgrade workflows (plus version skipping)

Before Monthly Node-OS / AMI Patching

After One click patching/updates via Git Workflows

Before Standardize clusters & prevent drift

After Rafay Cloud Credentials

Before Manage multiple tools and workflows across teams, accounts and clouds

After Apply & enforce standard cluster blueprints

Before Lack of support for using native Terraform for cluster lifecycle activities

After Robust 24/7 enterprise support

Customer Results

45%

Increase in productivity with fleet-based automated workflow

100%

Compliance clusters

4x

Faster cluster and add-on upgrades and patches

Try Rafay Now

Go Live Today In Any Cloud With Managed K8s

Centrally enforce the latest add-ons, policies and cost
controls across all clusters and landing zone

Public Cloud Suite

Latest Blogs from the Kubernetes Current

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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

Rafay and Netris: Partnering to speed up consumption and monetization for GPU Clouds

March 12, 2025 / by Haseeb Budhani

Rafay, a pioneer in delivering platform-as-a-service (PaaS) capabilities for self-service compute consumption, and Netris, a leader in networking Automation, Abstraction, and Multi-tenancy for AI & Cloud operators , are collaborating to help GPU Cloud Providers speed up consumption… Read More

Is Fine-Tuning or Prompt Engineering the Right Approach for AI?

March 6, 2025 / by Rajat Tiwari

While prompt engineering is a quick and cost-effective solution for general tasks, fine-tuning enables superior AI performance on proprietary data. We previously discussed how building a RAG-based chatbot for enterprise data paved the way for creating a… Read More

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