Kubernetes vs Rancher

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Kubernetes vs Rancher: What are the differences?

What is Kubernetes? Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops. 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.

What is Rancher? Open Source Platform for Running a Private Container Service. 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.

Kubernetes and Rancher can be primarily classified as "Container" tools.

Some of the features offered by Kubernetes are:

  • Lightweight, simple and accessible
  • Built for a multi-cloud world, public, private or hybrid
  • Highly modular, designed so that all of its components are easily swappable

On the other hand, Rancher provides the following key features:

  • Manage Hosts, Deploy Containers, Monitor Resources
  • User Management & Collaboration
  • Native Docker APIs & Tools

"Leading docker container management solution", "Simple and powerful" and "Open source" are the key factors why developers consider Kubernetes; whereas "Easy to use", "Open source and totally free" and "Multi-host docker-compose support" are the primary reasons why Rancher is favored.

Kubernetes and Rancher are both open source tools. It seems that Kubernetes with 55K GitHub stars and 19.1K forks on GitHub has more adoption than Rancher with 11.9K GitHub stars and 1.34K GitHub forks.

According to the StackShare community, Kubernetes has a broader approval, being mentioned in 1046 company stacks & 1096 developers stacks; compared to Rancher, which is listed in 89 company stacks and 35 developer stacks.

What is 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.

What is 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.
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What are some alternatives to Kubernetes and Rancher?
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.
Nomad
Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications.
OpenStack
OpenStack is a cloud operating system that controls large pools of compute, storage, and networking resources throughout a datacenter, all managed through a dashboard that gives administrators control while empowering their users to provision resources through a web interface.
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.
DC/OS
Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications.
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Decisions about Kubernetes and Rancher
Yshay Yaacobi
Yshay Yaacobi
Software Engineer · | 28 upvotes · 360.9K views
atSolutoSoluto
Docker Swarm
Docker Swarm
.NET
.NET
F#
F#
C#
C#
JavaScript
JavaScript
TypeScript
TypeScript
Go
Go
Visual Studio Code
Visual Studio Code
Kubernetes
Kubernetes

Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

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Sebastian Gębski
Sebastian Gębski
CTO at Shedul/Fresha · | 6 upvotes · 60.1K views
atFresha EngineeringFresha Engineering
Docker
Docker
Docker Compose
Docker Compose
Kubernetes
Kubernetes
Terraform
Terraform
Ansible
Ansible
Amazon EC2
Amazon EC2
Amazon EKS
Amazon EKS
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS

Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

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Emanuel Evans
Emanuel Evans
Senior Architect at Rainforest QA · | 12 upvotes · 160.9K views
atRainforest QARainforest QA
Heroku
Heroku
Kubernetes
Kubernetes
Google Kubernetes Engine
Google Kubernetes Engine
Google Cloud SQL for PostgreSQL
Google Cloud SQL for PostgreSQL
PostgreSQL
PostgreSQL
Google Cloud Memorystore
Google Cloud Memorystore
Redis
Redis
CircleCI
CircleCI
Google Cloud Build
Google Cloud Build
Helm
Helm
Terraform
Terraform

We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

Read the blog post to go more in depth.

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Docker
Docker
Docker Compose
Docker Compose
Jenkins
Jenkins
Kubernetes
Kubernetes
Amazon EC2
Amazon EC2
Heroku
Heroku
FeathersJS
FeathersJS
Node.js
Node.js
ExpressJS
ExpressJS
PostgreSQL
PostgreSQL
React
React
Redux
Redux
Semantic UI React
Semantic UI React
AVA
AVA
ESLint
ESLint
nginx
nginx
GitHub
GitHub
#Containerized
#Containers
#Backend
#Stack
#Frontend

Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

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Ido Shamun
Ido Shamun
at The Elegant Monkeys · | 6 upvotes · 68.5K views
atDailyDaily
Kubernetes
Kubernetes
GitHub
GitHub
CircleCI
CircleCI
Docker
Docker
Helm
Helm

Kubernetes powers our #backend services as it is very easy in terms of #devops (the managed version). We deploy everything using @helm charts as it provides us to manage deployments the same way we manage our code on GitHub . On every commit a CircleCI job is triggered to run the tests, build Docker images and deploy them to the registry. Finally on every master commit CircleCI also deploys the relevant service using Helm chart to our Kubernetes cluster

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Russel Werner
Russel Werner
Lead Engineer at StackShare · | 0 upvotes · 3.7K views
atStackShareStackShare
Heroku
Heroku
Kubernetes
Kubernetes
Amazon EKS
Amazon EKS
Google Kubernetes Engine
Google Kubernetes Engine