Skip to content

Challenges

Optimizing Amazon's VPC CNI for your EKS Clusters 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. Kubernetes clusters require a Container Network Interface (CNI) that is responsible for cluster networking. One of the options available with EKS is the Amazon VPC CNI, which allows your Kubernetes Pods to utilize IP Addresses defined within your VPCs Subnets. While this provides more control and flexibility to businesses, it also comes with its own set of challenges.

While the benefits of managing and customizing the Amazon VPC CNI on EKS are significant, it’s important to note that the process can be challenging and time consuming, particularly if you lack experience with kubernetes or Amazon's VPC and its resources.

This is where Rafay’s EKS integration can come in handy. In this blog, we'll explore how Rafay’s Platform can address pain points and simplify the management process.

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.

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.