Docker Machine vs Kubernetes vs Rancher

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Docker Machine
Docker Machine

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Kubernetes
Kubernetes

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Rancher
Rancher

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What is Docker Machine?

Machine lets you create Docker hosts on your computer, on cloud providers, and inside your own data center. It creates servers, installs Docker on them, then configures the Docker client to talk to them.

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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Why do developers choose Docker Machine?
Why do developers choose Kubernetes?
Why do developers choose Rancher?

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    What are some alternatives to Docker Machine, Kubernetes, and Rancher?
    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
    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere
    boot2docker
    boot2docker is a lightweight Linux distribution based on Tiny Core Linux made specifically to run Docker containers. It runs completely from RAM, weighs ~27MB and boots in ~5s (YMMV).
    Ansible
    Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.
    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.
    See all alternatives
    Decisions about Docker Machine, Kubernetes, and Rancher
    Yshay Yaacobi
    Yshay Yaacobi
    Software Engineer · | 27 upvotes · 285.1K views
    atSolutoSoluto
    Docker Swarm
    Docker Swarm
    Kubernetes
    Kubernetes
    Visual Studio Code
    Visual Studio Code
    Go
    Go
    TypeScript
    TypeScript
    JavaScript
    JavaScript
    C#
    C#
    F#
    F#
    .NET
    .NET

    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 · 50K views
    atFresha EngineeringFresha Engineering
    Amazon RDS
    Amazon RDS
    Amazon S3
    Amazon S3
    Amazon EKS
    Amazon EKS
    Amazon EC2
    Amazon EC2
    Ansible
    Ansible
    Terraform
    Terraform
    Kubernetes
    Kubernetes
    Docker Compose
    Docker Compose
    Docker
    Docker

    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 · 128.4K views
    atRainforest QARainforest QA
    Terraform
    Terraform
    Helm
    Helm
    Google Cloud Build
    Google Cloud Build
    CircleCI
    CircleCI
    Redis
    Redis
    Google Cloud Memorystore
    Google Cloud Memorystore
    PostgreSQL
    PostgreSQL
    Google Cloud SQL for PostgreSQL
    Google Cloud SQL for PostgreSQL
    Google Kubernetes Engine
    Google Kubernetes Engine
    Kubernetes
    Kubernetes
    Heroku
    Heroku

    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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    GitHub
    GitHub
    nginx
    nginx
    ESLint
    ESLint
    AVA
    AVA
    Semantic UI React
    Semantic UI React
    Redux
    Redux
    React
    React
    PostgreSQL
    PostgreSQL
    ExpressJS
    ExpressJS
    Node.js
    Node.js
    FeathersJS
    FeathersJS
    Heroku
    Heroku
    Amazon EC2
    Amazon EC2
    Kubernetes
    Kubernetes
    Jenkins
    Jenkins
    Docker Compose
    Docker Compose
    Docker
    Docker
    #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 · 47K views
    atDailyDaily
    Helm
    Helm
    Docker
    Docker
    CircleCI
    CircleCI
    GitHub
    GitHub
    Kubernetes
    Kubernetes

    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 · 5.3K views
    atStackShareStackShare
    Amazon EC2 Container Service
    Amazon EC2 Container Service
    CircleCI
    CircleCI
    Helm
    Helm
    Slack
    Slack
    Google Kubernetes Engine
    Google Kubernetes Engine
    Amazon EKS
    Amazon EKS
    Kubernetes
    Kubernetes
    Heroku
    Heroku

    We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.

    We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.

    The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.

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    Robert Zuber
    Robert Zuber
    CTO at CircleCI · | 6 upvotes · 14.2K views
    atCircleCICircleCI
    Helm
    Helm
    Nomad
    Nomad
    Kubernetes
    Kubernetes
    Docker
    Docker

    Our backend consists of two major pools of machines. One pool hosts the systems that run our site, manage jobs, and send notifications. These services are deployed within Docker containers orchestrated in Kubernetes. Due to Kubernetes’ ecosystem and toolchain, it was an obvious choice for our fairly statically-defined processes: the rate of change of job types or how many we may need in our internal stack is relatively low.

    The other pool of machines is for running our users’ jobs. Because we cannot dynamically predict demand, what types of jobs our users need to have run, nor the resources required for each of those jobs, we found that Nomad excelled over Kubernetes in this area.

    We’re also using Helm to make it easier to deploy new services into Kubernetes. We create a chart (i.e. package) for each service. This lets us easily roll back new software and gives us an audit trail of what was installed or upgraded.

    See more
    Interest over time
    Reviews of Docker Machine, Kubernetes, and Rancher
    Review ofKubernetesKubernetes

    It's a little bit complex to onboard, but once you grasp all the different concepts the platform is really powerful, and infrastructure stops being an issue.

    Service discovery, auto-recovery, scaling and orchestration are just a few of the features you get.

    Avatar of gonuts
    Michigan Technological University
    Review ofRancherRancher
    1. Consume too much unnecessary resource by just running rancher agent alone;
    2. Hard to recover from system failure
    3. Bad performance of load balancing (compare to dokcer swarm built-in LB or others).
    How developers use Docker Machine, Kubernetes, and Rancher
    Avatar of Matt Welke
    Matt Welke uses KubernetesKubernetes

    Just tinkering with it for personal use at this stage based on positive experience using it at work. Plan to use it for high traffic distributed systems if not using a managed hosting service like Heroku, AWS Lambda, or Google Cloud Functions. Reasons for using instead of these alternatives would be cheaper cost at higher scale.

    Avatar of etlweather
    etlweather uses RancherRancher

    The whole infrastructure is managed through Rancher. It provides a simple interface to all the underlying tools - Docker, HAProxy (automatically configures load balancer from the containers).

    Avatar of realcloudratics
    realcloudratics uses KubernetesKubernetes

    Good existential question. Kubernetes is painful in the extreme - especially when combined with Ansible. The layers of indirection are truly mind altering. But hey - containers are kewl!

    Avatar of Japan Digital Design
    Japan Digital Design uses KubernetesKubernetes

    Our developer experience system is on Kubernetes (Google Kubernetes Engine at the moment). We would like to expand our Kubernetes clusters over other Kubernetes engine.

    Avatar of ShareThis
    ShareThis uses KubernetesKubernetes

    Kubernetes is used for managing microclusters within our AWS infrastructure. This allows us to deploy new infrastructure in seconds.

    Avatar of papaver
    papaver uses KubernetesKubernetes

    minor experience with kubernetes. helped a client setup a kubernetes infrastructure. love the elegance of the system.

    Avatar of sapslaj
    sapslaj uses RancherRancher

    Currently looking to move to Swarm or Kubernetes due to a few issues I have with Rancher.

    Avatar of InsideSales.com
    InsideSales.com uses RancherRancher

    We use Rancher for container orchestration and automated deployment pipelines.

    Avatar of DNT
    DNT uses Docker MachineDocker Machine

    Crating Docker machines for production and local development.

    Avatar of Walter
    Walter uses Docker MachineDocker Machine

    Management of and deployment to production.

    Avatar of Dave Woolfenden
    Dave Woolfenden uses RancherRancher

    Enterprise-grade Kubernetes Distribution

    Avatar of Shiqiang Yu
    Shiqiang Yu uses RancherRancher

    Pull from CI/CD for live demo

    How much does Docker Machine cost?
    How much does Kubernetes cost?
    How much does Rancher cost?
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