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  1. Stackups
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  4. Helm Charts
  5. Helm vs K9s

Helm vs K9s

OverviewComparisonAlternatives

Overview

Helm
Helm
Stacks1.4K
Followers911
Votes18
K9s
K9s
Stacks75
Followers103
Votes2
GitHub Stars31.7K
Forks2.0K

Helm vs K9s: What are the differences?

Helm and K9s are both tools commonly used in the world of Kubernetes, but they serve different purposes and have distinct functionalities. In this markdown, we will outline the key differences between Helm and K9s.

  1. Installation: Helm is a package manager for Kubernetes that allows users to define, install, and manage applications on a Kubernetes cluster. It is installed both on the local machine and on the Kubernetes cluster. On the other hand, K9s is a command-line interface (CLI) tool that provides a visual, terminal-based interface for managing and troubleshooting Kubernetes clusters. It is only installed on the local machine and does not require any installation on the cluster itself.

  2. Usage: Helm provides a higher-level, package-centric approach to managing Kubernetes resources. It uses charts, which are packages of pre-configured Kubernetes resources, to deploy applications onto a cluster. Helm allows users to install, upgrade, and uninstall applications using commands and values files to customize the application's configuration. K9s, on the other hand, provides a cluster-centric view and allows users to interact with different Kubernetes resources like pods, services, deployments, and others directly from the terminal. It provides an intuitive and efficient way to navigate, inspect, and monitor the cluster in real-time.

  3. Customization: Helm allows users to customize the deployment of an application by providing values files that contain configuration options for the different Kubernetes resources in the chart. These values can be easily modified during installation or upgrade to tailor the application to specific needs. K9s, on the other hand, does not involve customization of application deployment but provides advanced filtering, searching, and sorting capabilities to help users explore and troubleshoot the cluster more effectively.

  4. Management of Dependencies: Helm allows users to define dependencies between applications using charts and track them using the requirements.yaml file. This allows for the management of complex applications that depend on multiple components. K9s, on the other hand, focuses on providing a comprehensive view of the cluster and does not have built-in functionality for managing dependencies between applications.

  5. GUI vs CLI: Helm can be used both through the command-line interface (CLI) and through the Helm graphical user interface (GUI) called Helm Classic. This provides flexibility for users who prefer a visual interface for managing applications on Kubernetes. K9s, on the other hand, is primarily a CLI tool and does not provide a graphical interface.

  6. Community Support: Helm has a larger and more established community compared to K9s. This means that there are more resources, documentation, and community support available for Helm compared to K9s. Helm also has an extensive library of existing charts available for popular applications, making it easier for users to deploy and manage these applications on Kubernetes.

In summary, Helm is a package manager for Kubernetes that allows users to easily deploy and manage applications on a cluster, while K9s provides a terminal-based interface for efficiently navigating and troubleshooting a Kubernetes cluster. Helm focuses on application deployment and management with extensive customization options, while K9s provides a comprehensive view of the cluster for efficient cluster administration and monitoring.

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Detailed Comparison

Helm
Helm
K9s
K9s

Helm is the best way to find, share, and use software built for Kubernetes.

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.

Statistics
GitHub Stars
-
GitHub Stars
31.7K
GitHub Forks
-
GitHub Forks
2.0K
Stacks
1.4K
Stacks
75
Followers
911
Followers
103
Votes
18
Votes
2
Pros & Cons
Pros
  • 8
    Infrastructure as code
  • 6
    Open source
  • 2
    Easy setup
  • 1
    Testa­bil­i­ty and re­pro­ducibil­i­ty
  • 1
    Support
Pros
  • 2
    Nice UI and fast way to manage my kubernetes clusters
Integrations
Docker
Docker
Kubernetes
Kubernetes
Kubernetes
Kubernetes

What are some alternatives to Helm, K9s?

Kubernetes

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

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

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

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

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

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

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

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

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

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.

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