K9s vs Kubeadm AWS

Overview

K9s

Stacks75

Followers103

Votes2

GitHub Stars31.7K

Forks2.0K

kubeadm-aws

Stacks2

Followers19

Votes0

GitHub Stars861

Forks56

K9s vs Kubeadm AWS: What are the differences?

Installation Method: K9s is a command-line tool that can be easily installed on a local machine, while Kubeadm AWS is specifically designed for provisioning Kubernetes clusters on AWS and requires additional setup steps and configurations.
Use Cases: K9s is mainly used for monitoring and managing Kubernetes clusters, providing a simplified interface for interacting with the cluster resources. On the other hand, Kubeadm AWS is focused on setting up Kubernetes clusters on AWS cloud platform.
Scalability: K9s is more suitable for smaller-scale clusters and individual cluster management, whereas Kubeadm AWS is designed for larger-scale deployments on AWS with built-in scalability features and optimizations.
Integration with AWS Services: Kubeadm AWS integrates seamlessly with various AWS services such as EC2, EBS, and VPC, providing a more streamlined and automated deployment process compared to K9s.
Configuration Options: K9s provides a more limited set of configuration options and customization features compared to Kubeadm AWS, which offers extensive customization capabilities for tailoring the Kubernetes cluster to specific requirements.
Community Support: K9s has a vibrant open-source community with active contributions and updates, while Kubeadm AWS is more focused on AWS-specific features and updates, reflecting the priorities of the AWS Kubernetes community.

In Summary, K9s and Kubeadm AWS differ in installation methods, use cases, scalability, integration with AWS services, configuration options, and community support.

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CLI (Node.js)

Manual

Detailed Comparison

K9s	kubeadm-aws
K9s provides a curses based terminal UI to interact with your Kubernetes clusters. The aim of this project is to make it easier to navigate, observe and manage your applications in the wild. K9s continually watches Kubernetes for changes and offers subsequent commands to interact with observed resources.	Bash and Terraform code which provisions affordable single master Kubernetes cluster on AWS. You can run a 1 master, 1 worker cluster for somewhere around $6 a month.
-	Automatic backup and recovery; Automated provisioning; Variables; Auto Scaling of worker nodes; Persistent volumes
Statistics
GitHub Stars 31.7K	GitHub Stars 861
GitHub Forks 2.0K	GitHub Forks 56
Stacks 75	Stacks 2
Followers 103	Followers 19
Votes 2	Votes 0
Pros & Cons
Pros 2 Nice UI and fast way to manage my kubernetes clusters	No community feedback yet
Integrations
Kubernetes	Terraform Amazon EC2 NGINX Kubernetes AWS Elastic Load Balancing (ELB)

What are some alternatives to K9s, kubeadm-aws?

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

Flocker

Flocker is a data volume manager and multi-host Docker cluster management tool. With it you can control your data using the same tools you use for your stateless applications. This means that you can run your databases, queues and key-value stores in Docker and move them around as easily as the rest of your app.

Related Comparisons

K9s vs Kubeadm AWS: What are the differences?

Installation Method: K9s is a command-line tool that can be easily installed on a local machine, while Kubeadm AWS is specifically designed for provisioning Kubernetes clusters on AWS and requires additional setup steps and configurations.
Use Cases: K9s is mainly used for monitoring and managing Kubernetes clusters, providing a simplified interface for interacting with the cluster resources. On the other hand, Kubeadm AWS is focused on setting up Kubernetes clusters on AWS cloud platform.
Scalability: K9s is more suitable for smaller-scale clusters and individual cluster management, whereas Kubeadm AWS is designed for larger-scale deployments on AWS with built-in scalability features and optimizations.
Integration with AWS Services: Kubeadm AWS integrates seamlessly with various AWS services such as EC2, EBS, and VPC, providing a more streamlined and automated deployment process compared to K9s.
Configuration Options: K9s provides a more limited set of configuration options and customization features compared to Kubeadm AWS, which offers extensive customization capabilities for tailoring the Kubernetes cluster to specific requirements.
Community Support: K9s has a vibrant open-source community with active contributions and updates, while Kubeadm AWS is more focused on AWS-specific features and updates, reflecting the priorities of the AWS Kubernetes community.

In Summary, K9s and Kubeadm AWS differ in installation methods, use cases, scalability, integration with AWS services, configuration options, and community support.

K9s vs Kubeadm AWS

Overview