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Amazon EKS v1.26 Clusters using Rafay

In our recent release in May, we added support for a number of new features and enhancements. One of these was support for new EKS cluster provisioning based on Kubernetes v1.26.

Customers have shared with us that they would like to provision new EKS clusters using new Kubernetes versions so that they do not have to plan/schedule for Kubernetes upgrades for these clusters right away. On the other hand, they want to be extremely careful with their existing clusters and plan/test in-place upgrades for these. There is no benefit in rushing this and impacting mission critical applications etc.

Based on this feedback, starting this release, we plan to introduce support for new Kubernetes versions for CSPs (i.e. EKS, AKS and GKE) in two phases. In the first phase, which will come very quickly, we will support new cluster provisioning for the new Kubernetes version. This requires us to extensively validate support for ALL supported interfaces in the platform (See details below). We will follow up with a Phase 2 which will bring support for zero touch in-place upgrades.

Important

Support for zero touch, in-place upgrades in Rafay from EKS v1.25 to v1.26 will follow in a few weeks. This requires us to add support for new preflight tests etc and perform extensive testing and validation.

Helm-Based Import

Early this year, we released the ability to import existing brownfield clusters into the Rafay platform using an official Helm Chart. With the helm-based import, it's a simple 3 step process a) Add the rafay-helm-charts to your helm repo b) Download the values.yaml using the API, RCTL or TF. This allows you to customize certain configurations as needed. c) Helm install with the custom values. This will bootstrap the Rafay operator onto the cluster.

Steps for this process are documented here.

Advantages of using Helm-Based Import

  • automate through the same Helm based interface that you are used to today and add this to your existing Helm automation
  • ability to use custom values.yaml file just like you would do with normal Helm to deploy the same bootstrap chart to multiple clusters
  • expanded and deeper integration with our technology partners - for example you can install Rafay through the AWS Marketplace

Values.yaml file customization

Using the API or TF, the default values.yaml file can be downloaded that will be used for the Helm install. Whether you are operating using the SaaS or self-hosted controller, the API endpoints, tokens, registries etc. will be populated with the latest and up to date information. You can change things like the Rafay relay image cpu and memory limits to fine tune performance accordingly. An example of what the values.yaml file looks like is shown here: 

global:
  Rafay:
    ClusterLabels:
      rafay.dev/clusterID: 'kg1nqzk'
      rafay.dev/clusterLocation: 'newyorkcity-us'
      rafay.dev/clusterName: 'do-c'
      rafay.dev/clusterType: 'imported'
      rafay.dev/kubernetesProvider: 'OTHER'

connector:
  image:
    repository: "registry.rafay-edge.net/rafay/rafay-connector"
    pullPolicy: IfNotPresent
    tag: "r1.25.0-1"

controller:
  image:
    repository: "registry.rafay-edge.net/rafay/cluster-controller"
    pullPolicy: IfNotPresent
    tag: "r1.25.0-1"

relay:
  image:
    repository: "registry.rafay-edge.net/rafay/rafay-relay-agent"
    pullPolicy: IfNotPresent
    tag: "r1.25.0-1"
  resources:
    requests:
      cpu: 100m
      memory: 128Mi
    limits:
      cpu: 500m
      memory: 512Mi

initContainer:
  image:
    repository: "registry.rafay-edge.net/rafay/busybox"
    pullPolicy: IfNotPresent
    tag: "1.33"

token: "ci174q5rhpjof3hkjv40"
api_addr: "api.rafay.dev."
control_addr: "control.rafay.dev."
allow_insecure_bootstrap: ""
cluster_id: 'kg1nqzk'
max_dials: '2'
relays: '[{"token":"ci174q5rhpjof3hkjv4g","addr":"app.rafay.dev.:443","endpoint":"*.connector.kubeapi-proxy.rafay.dev.:443","name":"rafay-core-relay-agent","templateToken":"bsegkge8bg0jn4l6pdjg"}]'
http_proxy: ""
https_proxy: ""
no_proxy: ""
proxy_auth: ""
openshift: false

Example

In this YouTube video below, I show an example of how you can use the Rafay API to download the values.yaml file, which you can customize according to your needs and then import the cluster into Rafay using Helm.

Blog Ideas

Sincere thanks to readers of our blog who spend time reading our product blogs. Please Contact the Rafay Product Team if you would like us to write about other topics.

Azure Linux Container Host for AKS Clusters

In late May 2023, Microsoft announced General Availability of Azure Linux Container Host. This is based on the "CBL Mariner" OSS project maintained by Microsoft.

  • It is an operating system image that is optimized for running container workloads on Azure Kubernetes Service (AKS).
  • The OS image is maintained by Microsoft and based on Microsoft Azure Linux, an open-source Linux distribution created by Microsoft.
  • It is lightweight, containing only the packages needed to run container workloads.
  • It is hardened based on validation tests and is compatible with Azure agents.

Understanding Component Upgrades in an Upstream Rafay MKS Cluster

Upgrading a Kubernetes cluster is a crucial process that ensures your infrastructure stays up-to-date with the latest features, bug fixes, and security patches. As part of this process, several components within the cluster undergo upgrades.

In this blog post, we will explore the components that typically get upgraded during a cluster upgrade and highlight some of the periodic upgrades that both Cloud Service Providers (CSPs) and Rafay undertakes to enhance cluster performance and stability.

Developer Self Service via Cluster Templates

Our recent release update in May adds support for a number of new features and enhancements and we have written about the these enhancements and new features in our blogs. This blog is focused on Cluster Templates for GKE that enables customers to implement a Developer Self Service for Kubernetes clusters.

We added support for cluster templates in early 2022 starting with support for Amazon EKS initially, then followed by cluster templates for Azure AKS and with this release, cluster templates for Google's GKE. Common Use Cases for Cluster Templates are "Ephemeral Clusters" for lower environments such as:

  • Developer Test Beds
  • QA environments
  • Product support to replicate customer issues

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.

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