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Amazon EKS v1.25 using Rafay

Our recent release update in May to our Preview environment adds support for a number of new features and enhancements. We will write about the other new features in separate blogs. This blog is focused on our turnkey support for Amazon EKS v1.25.

Both new cluster provisioning and in-place upgrades of existing EKS clusters are supported. As with most Kubernetes releases, this version also deprecates and removes a number of features. To ensure there is zero impact to our customers, we have made sure that every feature in the Rafay Kubernetes Operations Platform has been validated on this Kubernetes version.

This release will be promoted from Preview to Production in a few days and will be made available to all customers.

Note that no action is needed on the part of our SaaS customers with the new release. Once the rollout is completed, all they need to do is learn about the new features and determine how and when they would like to use them.

Kubernetes v1.26 for Rafay MKS

Our recent release update in May to our Preview environment adds support for a number of new features and enhancements. We will write about these in separate blogs. This blog is focused on support for Kubernetes v1.26 with Rafay MKS (i.e. upstream Kubernetes for bare metal and VM based environments).

Both new cluster provisioning and in-place upgrades of existing clusters are supported. As with most Kubernetes releases, this version also deprecates and removes a number of features. To ensure there is zero impact to our customers, we have made sure that every feature in the Rafay Kubernetes Operations Platform has been validated on this Kubernetes version. This will be promoted from Preview to Production in a few days and will be made available to all customers.

Kubernetes v1.26 Release

Solutions for Key Kubernetes Challenges for AI/ML in the Enterprise - Part 2

This is part-2 of our blog series on challenges and solutions for AI/ML in the enterprise. This blog is based on our learnings over the last two years as we worked very closely with our customers that make extensive use of Kubernetes for AI/ML use cases. In part-1, we looked at the following:

  • Why Kubernetes is particularly compelling for AI/ML.
  • Described some of the key challenges that organizations will encounter with AI/ML and Kubernetes

In this part, we will look at some innovative approaches by which organizations can address these challenges.

EKS Anywhere Bare Metal Cluster Management Made Easy with Rafay

Amazon Elastic Kubernetes Service (EKS) is a managed service that you can use to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane or nodes. One of the options available with EKS is EKS Anywhere for Bare Metal environments, which allows you to run Kubernetes on your own hardware. While this provides more control and flexibility to businesses, it also comes with its own set of challenges.

While the benefits of managing EKS Anywhere on Bare Metal are significant, it’s important to note that the process can be challenging and time consuming, particularly if you lack experience with kubernetes on Bare Metal infrastructure. This is where Rafay’s Kubernetes Platform for managing EKS Anywhere Bare Metal clusters can come in handy.

In this blog, we'll explore how Rafay’s Platform can address pain points and simplify the management process.

Rafay terraform provider

Rafay's Terraform Provider

Terraform is today one of the most popular tools to provision resources on all major cloud platforms, such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure. It uses Infrastructure as a Code (IaC) to automate infrastructure provisioning. This blog will discuss the Terraform provider for Rafay.

The Rafay Terraform provider Terraform Provider is a plugin that allows Terraform to manage resources in the Rafay platform. It enables users to automate the creation, configuration, and deletion of Rafay resources such as clusters, projects, policies, and environments. It is available as an open-source project on GitHub, and it can be installed using the standard Terraform plugin installation process Terraform installation

Key Kubernetes Challenges for AI/ML in the Enterprise - Part 1

This blog is based on our learnings over the last two years as we worked very closely with our customers that make extensive use of Kubernetes for AI/ML.

This is part-1 of a two part series. In part-1, we will

  • Start by looking at why Kubernetes is particularly compelling for AI/ML.
  • Describe some of the key challenges that organizations will encounter with AI/ML and Kubernetes

In part-2, we will look at ways by which organizations can address these challenges.

Announcing our April 2023 (v1.24) Release

A few weeks back in early April 2023, we upgraded our Preview environment to v1.24 of the Rafay Kubernetes Operations Platform. Our sincere thanks to our customers and partners that have been actively testing the new functionality. We have received timely feedback that we have been able to incorporate into our product documentation and into the platform as well.

Today, we upgraded our Production environment to this release. As always, our customers will have seamless access to the new functionality with no interruptions to their applications or clusters. In this blog, I will describe some of the new features that are part of this release.

April Release v1.24

How Platform Teams can enable developers to use their preferred Kubernetes Tools

There are cases where developers may prefer to use tools on their laptops such as Lens Desktop to visualize resources and interact with Kubernetes clusters. The use of a desktop based app such as Lens can be a better user experience for developers over the Kubectl CLI.

In this blog, we will describe how Platform Teams can use Rafay’s Zero-Trust Access service to enable developers to use popular Kubernetes visualization apps to troubleshoot their applications. Watch a video showing how a developer can use Lens Desktop with Rafay's Zero Trust Kubectl Access service to securely and remotely access Kubernetes clusters.