5 Tools for Automating Kubernetes Cluster Deployments


Melissa Gonzalez | Updated: 09-09-2021 17:02 IST | Created: 09-09-2021 17:02 IST
5 Tools for Automating Kubernetes Cluster Deployments
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The deployment, implementation, and management of Kubernetes clusters is a hot topic in the industry. Luckily, you may be able to sidestep the hornets' nest by automating your deployment.

There are a variety of different automation services, each with its own discrete benefits and implementations. Researching the best product for you may be overwhelming at first, but finding the best way to automate cluster creation, configuration, maintenance, and upgrades doesn't have to be a headache.

Some of the most popular options include Rancher RKE, Kubernetes Operations, Kubespray, Kube-AWS, and Spinnaker.io. Exploring the benefits and stopgaps of each is an excellent way to find your best fit and put you ahead of the industry curve. Here are five tools for automating Kubernetes cluster deployments.

Rancher Kubernetes Engine (RKE)

Rancher Kubernetes Engine (RKE) is one of the versatile and easy ways to automate a Kubernetes cluster deployment. It features simplified installation, automated operation, FIPS-enabled, and 24x7 enterprise-level support. These features and more make Rancher RKE one of the best solutions for clients that need to automate Kubernetes.

Simplified installation

You don't have to worry about installation when using Rancher Kubernetes Engine. Through a single binary and single YAML file, you can complete the installation of RKE. CNCF-certified, Rancher Kubernetes Engine removes host dependencies and provides ease of deployment, upgrading, and rollback.CNCF certification ensures every release of RKE supports the same APIs as Kubernetes.

Automated operation

RKE offers automated operations. Using its inter-product integration capabilities, installation and upgrades can be completed with a few clicks.

FIPS-enabled

RKE is compliant with strict security standards and provides excellent defense for cloud-native apps.

Kubernetes Operations (kops)

Kops is an open-source tool that can help you get your Kubernetes off the ground in record time. This open-source project automates clusters in AWS and GCE. Kops also supports cloud-native features and automatic updates.

Utilizing kops significantly simplifies the setup and management of a cluster compared to a manual setup. If you are familiar with kubectl, it can make automating operational tasks easier. You'll have no issue scaling up nodes or scaling up the cluster. Who doesn't love an automation solution that grows with you?

Kubernetes Operations offers automated deployment on AWS, GCE, OpenStack, and VMware vSphere.

  • The State-sync model provides dry-runs and automatic idempotency.
  • Eight different CNI networking providers.
  • Support for add-ons, upgrading from kube-up, and ability to generate Terraform.
  • Command-line autocompletion.

Kops will let you set up clusters with extensive configuration options and parameters. This intense customizability means that the solution fits you, and not the other way around. Kops solves some of the toughest puzzles in Kubernetes deployment, including added project complexity and deployment speed.

Kubespray

One of the most popular ways to automate a Kubernetes cluster is with Kubespray. Built from Ansible's provisioning and deployment capabilities, they're a highly effective and customizable way to automate clusters.

Within Kubespray, tasks like creating clusters, composing inventory files, and cluster deployment can all be automated. The playbooks available allow you to automatically scale, update, and upgrade Kubernetes clusters.

Kubespray is one of the most effective options if you run a hybrid environment with more than one public cloud on your premises.

One drawback of using Kubespray is the inability to self-provision. This drawback can be remedied by Kubespray's support of Terraform on public clouds. Kubespray is one of the most versatile options and can be used on many different services, including AWS, GCE, and Azure.

Kube-AWS

Kube-AWS is another command-line tool that can automate Kubernetes cluster deployment. You can use command line prompts to create, update and destroy clusters on AWS with Kube-AWS.

Available only for AWS customers, Kube-AWS offers seamless integration with other AWS services, including CloudFormation, EC2, KMS, S3, Auto Scaling, and Spot Fleet.

Kube-AWS has incredible customization options for your stack. You have access to cloud-config and CloudFormation stack templates as well.

While Kube-AWS is only available for AWS cloud-based systems, it will allow you to run applications at scale from anywhere. You'll also be able to seamlessly move applications and add new functionality when needed. If you're already an avid AWS user, Kube-AWS might be the next no-brainer integration for you.

Spinnaker.io

Originally developed by Netflix, this now open-sourced project offers support for automating Kubernetes cluster deployment. Designed to complement the toolset in Kubernetes, Spinnaker.io provides deployment pipelines that will make automation a breeze.

Spinnaker offers multi-cloud delivery and a power pipeline:

  • Easy deployment, scaling and rollbacks directly from the console.
  • Notifications are available through email, Slack, and Hipchat.
  • Support for Helm charts and handles blue/green and canary deployments.
  • Multi-cloud deployment and continuous integration.

Some other features include role-based access control, chaos money integration, CI integrations, and CLI for setup and admin. If you need a flexible management system that will make automating cluster deployment easier, Spinnaker is an ideal solution that integrates with most major cloud providers.

Make your life easier

Deploying Kubernetes can be a headache and a half. Luckily, you can use automation to set and forget your Kubernetes cluster deployment. By adding some of the tools above to your toolbelt, you'll be sitting back and watching your Kubernetes deployment run itself in no time.

(Devdiscourse's journalists were not involved in the production of this article. The facts and opinions appearing in the article do not reflect the views of Devdiscourse and Devdiscourse does not claim any responsibility for the same.)

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