Alternatives to Dokku logo

Alternatives to Dokku

Heroku, Flynn, Docker, Kubernetes, and Rancher are the most popular alternatives and competitors to Dokku.
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What is Dokku and what are its top alternatives?

Docker powered mini-Heroku. The smallest PaaS implementation you've ever seen.
Dokku is a tool in the Platform as a Service category of a tech stack.
Dokku is an open source tool with 20.8K GitHub stars and 1.6K GitHub forks. Here’s a link to Dokku's open source repository on GitHub

Top Alternatives to Dokku

  • Heroku

    Heroku

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling. ...

  • Flynn

    Flynn

    Flynn lets you deploy apps with git push and containers. Developers can deploy any app to any cluster in seconds. ...

  • Docker

    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 ...

  • 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. ...

  • Nanobox

    Nanobox

    Nanobox is the ideal platform for developers allowing you to focus on code, not config, by removing the need to deal with environment configuration and dev-ops complexity. ...

  • Jenkins

    Jenkins

    In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project. ...

Dokku alternatives & related posts

Heroku logo

Heroku

16.9K
12.7K
3.2K
Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
16.9K
12.7K
+ 1
3.2K
PROS OF HEROKU
  • 703
    Easy deployment
  • 460
    Free for side projects
  • 374
    Huge time-saver
  • 348
    Simple scaling
  • 261
    Low devops skills required
  • 189
    Easy setup
  • 174
    Add-ons for almost everything
  • 153
    Beginner friendly
  • 149
    Better for startups
  • 133
    Low learning curve
  • 47
    Postgres hosting
  • 41
    Easy to add collaborators
  • 30
    Faster development
  • 24
    Awesome documentation
  • 19
    Simple rollback
  • 18
    Focus on product, not deployment
  • 15
    Easy integration
  • 15
    Natural companion for rails development
  • 11
    Great customer support
  • 7
    GitHub integration
  • 6
    No-ops
  • 5
    Painless & well documented
  • 3
    Just works
  • 3
    Free
  • 2
    PostgreSQL forking and following
  • 2
    I love that they make it free to launch a side project
  • 2
    Great UI
  • 2
    MySQL extension
CONS OF HEROKU
  • 22
    Super expensive
  • 6
    No usable MySQL option
  • 6
    Not a whole lot of flexibility
  • 5
    Storage
  • 4
    Low performance on free tier

related Heroku posts

Russel Werner
Lead Engineer at StackShare · | 29 upvotes · 1.3M views

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

See more
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.2M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
Flynn logo

Flynn

13
44
16
Next generation open source platform as a service
13
44
+ 1
16
PROS OF FLYNN
  • 6
    Free
  • 5
    Supports few types of containers:libvirt-lxc, docker
  • 2
    PostgreSQL HA
  • 2
    Easy setup
  • 1
    12-factor methodology
CONS OF FLYNN
    Be the first to leave a con

    related Flynn posts

    Docker logo

    Docker

    90.8K
    70.4K
    3.8K
    Enterprise Container Platform for High-Velocity Innovation.
    90.8K
    70.4K
    + 1
    3.8K
    PROS OF DOCKER
    • 816
      Rapid integration and build up
    • 687
      Isolation
    • 514
      Open source
    • 501
      Testa­bil­i­ty and re­pro­ducibil­i­ty
    • 456
      Lightweight
    • 214
      Standardization
    • 181
      Scalable
    • 104
      Upgrading / down­grad­ing / ap­pli­ca­tion versions
    • 85
      Security
    • 82
      Private paas environments
    • 32
      Portability
    • 24
      Limit resource usage
    • 14
      I love the way docker has changed virtualization
    • 14
      Game changer
    • 12
      Fast
    • 10
      Concurrency
    • 6
      Docker's Compose tools
    • 3
      Because its fun
    • 3
      Easy setup
    • 3
      Fast and Portable
    • 2
      Makes shipping to production very simple
    • 2
      It's dope
    • 1
      Its cool
    • 1
      Docker hub for the FTW
    • 1
      Very easy to setup integrate and build
    • 1
      Package the environment with the application
    • 1
      Open source and highly configurable
    • 1
      Simplicity, isolation, resource effective
    • 1
      Highly useful
    • 1
      MacOS support FAKE
    CONS OF DOCKER
    • 7
      New versions == broken features
    • 4
      Documentation not always in sync
    • 3
      Moves quickly
    • 3
      Unreliable networking

    related Docker posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.2M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more
    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 21 upvotes · 4M views

    Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

    It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

    I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

    We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

    If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

    The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

    Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

    See more
    Kubernetes logo

    Kubernetes

    30.1K
    24.8K
    588
    Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
    30.1K
    24.8K
    + 1
    588
    PROS OF KUBERNETES
    • 151
      Leading docker container management solution
    • 121
      Simple and powerful
    • 95
      Open source
    • 70
      Backed by google
    • 55
      The right abstractions
    • 24
      Scale services
    • 16
      Replication controller
    • 9
      Permission managment
    • 6
      Simple
    • 5
      Supports autoscaling
    • 5
      Cheap
    • 3
      Promotes modern/good infrascture practice
    • 3
      No cloud platform lock-in
    • 3
      Self-healing
    • 3
      Open, powerful, stable
    • 3
      Scalable
    • 3
      Reliable
    • 2
      A self healing environment with rich metadata
    • 2
      Captain of Container Ship
    • 2
      Quick cloud setup
    • 1
      Custom and extensibility
    • 1
      Expandable
    • 1
      Easy setup
    • 1
      Gke
    • 1
      Golang
    • 1
      Backed by Red Hat
    • 1
      Everything of CaaS
    • 1
      Runs on azure
    • 1
      Cloud Agnostic
    • 1
      Sfg
    CONS OF KUBERNETES
    • 13
      Poor workflow for development
    • 10
      Steep learning curve
    • 4
      Orchestrates only infrastructure
    • 2
      High resource requirements for on-prem clusters

    related Kubernetes posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 37 upvotes · 3.4M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Yshay Yaacobi

    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...

    See more
    Rancher logo

    Rancher

    750
    1.1K
    642
    Open Source Platform for Running a Private Container Service
    750
    1.1K
    + 1
    642
    PROS OF RANCHER
    • 102
      Easy to use
    • 79
      Open source and totally free
    • 62
      Multi-host docker-compose support
    • 58
      Simple
    • 58
      Load balancing and health check included
    • 44
      Rolling upgrades, green/blue upgrades feature
    • 42
      Dns and service discovery out-of-the-box
    • 37
      Only requires docker
    • 34
      Multitenant and permission management
    • 29
      Easy to use and feature rich
    • 11
      Cross cloud compatible
    • 11
      Does everything needed for a docker infrastructure
    • 8
      Simple and powerful
    • 8
      Next-gen platform
    • 7
      Very Docker-friendly
    • 6
      Support Kubernetes and Swarm
    • 6
      Application catalogs with stack templates (wizards)
    • 6
      Supports Apache Mesos, Docker Swarm, and Kubernetes
    • 6
      Rolling and blue/green upgrades deployments
    • 6
      High Availability service: keeps your app up 24/7
    • 5
      Easy to use service catalog
    • 4
      Very intuitive UI
    • 4
      IaaS-vendor independent, supports hybrid/multi-cloud
    • 4
      Awesome support
    • 3
      Scalable
    • 2
      Requires less infrastructure requirements
    CONS OF RANCHER
    • 7
      Hosting Rancher can be complicated

    related Rancher posts

    Docker Compose logo

    Docker Compose

    12K
    8.5K
    471
    Define and run multi-container applications with Docker
    12K
    8.5K
    + 1
    471
    PROS OF DOCKER COMPOSE
    • 118
      Multi-container descriptor
    • 107
      Fast development environment setup
    • 75
      Easy linking of containers
    • 65
      Simple yaml configuration
    • 58
      Easy setup
    • 15
      Yml or yaml format
    • 11
      Use Standard Docker API
    • 7
      Open source
    • 4
      Can choose Discovery Backend
    • 4
      Go from template to application in minutes
    • 2
      Scalable
    • 2
      Easy configuration
    • 2
      Kubernetes integration
    • 1
      Quick and easy
    CONS OF DOCKER COMPOSE
    • 7
      Tied to single machine
    • 4
      Still very volatile, changing syntax often

    related Docker Compose posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.2M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more

    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.

    See more
    Nanobox logo

    Nanobox

    13
    21
    0
    The Ideal Platform for Developers
    13
    21
    + 1
    0
    PROS OF NANOBOX
      Be the first to leave a pro
      CONS OF NANOBOX
        Be the first to leave a con

        related Nanobox posts

        Jenkins logo

        Jenkins

        36.1K
        28.8K
        2.2K
        An extendable open source continuous integration server
        36.1K
        28.8K
        + 1
        2.2K
        PROS OF JENKINS
        • 520
          Hosted internally
        • 463
          Free open source
        • 313
          Great to build, deploy or launch anything async
        • 243
          Tons of integrations
        • 208
          Rich set of plugins with good documentation
        • 108
          Has support for build pipelines
        • 71
          Open source and tons of integrations
        • 63
          Easy setup
        • 61
          It is open-source
        • 54
          Workflow plugin
        • 11
          Configuration as code
        • 10
          Very powerful tool
        • 9
          Many Plugins
        • 8
          Git and Maven integration is better
        • 8
          Great flexibility
        • 6
          Continuous Integration
        • 6
          Slack Integration (plugin)
        • 6
          Github integration
        • 5
          Easy customisation
        • 5
          Self-hosted GitLab Integration (plugin)
        • 4
          100% free and open source
        • 4
          Docker support
        • 3
          Excellent docker integration
        • 3
          Fast builds
        • 3
          Platform idnependency
        • 2
          Pipeline API
        • 2
          Customizable
        • 2
          Can be run as a Docker container
        • 2
          It`w worked
        • 2
          Hosted Externally
        • 2
          AWS Integration
        • 2
          JOBDSL
        • 2
          It's Everywhere
        • 1
          NodeJS Support
        • 1
          PHP Support
        • 1
          Ruby/Rails Support
        • 1
          Universal controller
        • 1
          Easily extendable with seamless integration
        • 1
          Build PR Branch Only
        CONS OF JENKINS
        • 12
          Workarounds needed for basic requirements
        • 7
          Groovy with cumbersome syntax
        • 6
          Plugins compatibility issues
        • 6
          Limited abilities with declarative pipelines
        • 5
          Lack of support
        • 4
          No YAML syntax
        • 2
          Too tied to plugins versions

        related Jenkins posts

        Thierry Schellenbach

        Releasing new versions of our services is done by Travis CI. Travis first runs our test suite. Once it passes, it publishes a new release binary to GitHub.

        Common tasks such as installing dependencies for the Go project, or building a binary are automated using plain old Makefiles. (We know, crazy old school, right?) Our binaries are compressed using UPX.

        Travis has come a long way over the past years. I used to prefer Jenkins in some cases since it was easier to debug broken builds. With the addition of the aptly named “debug build” button, Travis is now the clear winner. It’s easy to use and free for open source, with no need to maintain anything.

        #ContinuousIntegration #CodeCollaborationVersionControl

        See more
        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 21 upvotes · 4M views

        Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

        It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

        I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

        We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

        If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

        The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

        Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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