Alternatives to Docker logo

Alternatives to Docker

LXC, rkt, Kubernetes, Cloud Foundry, and Vagrant are the most popular alternatives and competitors to Docker.
110.5K
87.8K
+ 1
3.8K

What is Docker and what are its top alternatives?

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
Docker is a tool in the Virtual Machine Platforms & Containers category of a tech stack.
Docker is an open source tool with 61.3K GitHub stars and 17.7K GitHub forks. Here’s a link to Docker's open source repository on GitHub

Top Alternatives to Docker

  • LXC

    LXC

    LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers. ...

  • rkt

    rkt

    Rocket is a cli for running App Containers. The goal of rocket is to be composable, secure, and fast. ...

  • 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. ...

  • Cloud Foundry

    Cloud Foundry

    Cloud Foundry is an open platform as a service (PaaS) that provides a choice of clouds, developer frameworks, and application services. Cloud Foundry makes it faster and easier to build, test, deploy, and scale applications. ...

  • Vagrant

    Vagrant

    Vagrant provides the framework and configuration format to create and manage complete portable development environments. These development environments can live on your computer or in the cloud, and are portable between Windows, Mac OS X, and Linux. ...

  • Red Hat OpenShift

    Red Hat OpenShift

    OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications. ...

  • VirtualBox

    VirtualBox

    VirtualBox is a powerful x86 and AMD64/Intel64 virtualization product for enterprise as well as home use. Not only is VirtualBox an extremely feature rich, high performance product for enterprise customers, it is also the only professional solution that is freely available as Open Source Software under the terms of the GNU General Public License (GPL) version 2. ...

  • containerd

    containerd

    An industry-standard container runtime with an emphasis on simplicity, robustness, and portability ...

Docker alternatives & related posts

LXC logo

LXC

98
176
16
Linux containers
98
176
+ 1
16
PROS OF LXC
  • 4
    Lightweight
  • 3
    Simple and powerful
  • 3
    Easy to use
  • 2
    Good security
  • 2
    LGPL
  • 1
    Reliable
  • 1
    Trusted
CONS OF LXC
    Be the first to leave a con

    related LXC posts

    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 4.5M 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
    rkt logo

    rkt

    30
    101
    10
    App Container runtime
    30
    101
    + 1
    10
    PROS OF RKT
    • 5
      Security
    • 3
      Robust container portability
    • 2
      Composable containers
    CONS OF RKT
      Be the first to leave a con

      related rkt posts

      Kubernetes logo

      Kubernetes

      37.2K
      31.5K
      622
      Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
      37.2K
      31.5K
      + 1
      622
      PROS OF KUBERNETES
      • 155
        Leading docker container management solution
      • 124
        Simple and powerful
      • 100
        Open source
      • 74
        Backed by google
      • 56
        The right abstractions
      • 24
        Scale services
      • 18
        Replication controller
      • 9
        Permission managment
      • 7
        Simple
      • 7
        Supports autoscaling
      • 6
        Cheap
      • 4
        Self-healing
      • 4
        Reliable
      • 4
        No cloud platform lock-in
      • 3
        Open, powerful, stable
      • 3
        Scalable
      • 3
        Quick cloud setup
      • 3
        Promotes modern/good infrascture practice
      • 2
        Backed by Red Hat
      • 2
        Runs on azure
      • 2
        Cloud Agnostic
      • 2
        Custom and extensibility
      • 2
        Captain of Container Ship
      • 2
        A self healing environment with rich metadata
      • 1
        Golang
      • 1
        Easy setup
      • 1
        Everything of CaaS
      • 1
        Sfg
      • 1
        Expandable
      • 1
        Gke
      CONS OF KUBERNETES
      • 13
        Poor workflow for development
      • 11
        Steep learning curve
      • 5
        Orchestrates only infrastructure
      • 2
        High resource requirements for on-prem clusters

      related Kubernetes posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 38 upvotes · 4.1M 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
      Cloud Foundry logo

      Cloud Foundry

      154
      281
      4
      Deploy and scale applications in seconds on your choice of private or public cloud
      154
      281
      + 1
      4
      PROS OF CLOUD FOUNDRY
      • 1
        Perfectly aligned with springboot
      • 1
        Free distributed tracing (zipkin)
      • 1
        Application health management
      • 1
        Free service discovery (Eureka)
      CONS OF CLOUD FOUNDRY
        Be the first to leave a con

        related Cloud Foundry posts

        Vagrant logo

        Vagrant

        8.3K
        6K
        1.5K
        A tool for building and distributing development environments
        8.3K
        6K
        + 1
        1.5K
        PROS OF VAGRANT
        • 352
          Development environments
        • 291
          Simple bootstraping
        • 238
          Free
        • 139
          Boxes
        • 132
          Provisioning
        • 84
          Portable
        • 81
          Synced folders
        • 69
          Reproducible
        • 51
          Ssh
        • 44
          Very flexible
        • 5
          Works well, can be replicated easily with other devs
        • 5
          Easy-to-share, easy-to-version dev configuration
        • 3
          Great
        • 2
          Quick way to get running
        • 2
          Just works
        • 1
          What is vagrant?
        • 1
          Container Friendly
        • 1
          DRY - "Do Not Repeat Yourself"
        • 1
          Good documentation
        CONS OF VAGRANT
        • 2
          Can become v complex w prod. provisioner (Salt, etc.)
        • 2
          Multiple VMs quickly eat up disk space
        • 1
          Development environment that kills your battery

        related Vagrant posts

        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 23 upvotes · 4.5M 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
        Tim Abbott
        Shared insights
        on
        VirtualBox
        Vagrant
        Zulip
        at

        We use VirtualBox primarily as a Vagrant provider for macOS for the Zulip development environment. It's totally reasonable software for providing a convenient virtual machine setup on macOS (and for debugging when things go wrong, which is mostly how we use it since the Vagrant provider for macOS just works).

        See more
        Red Hat OpenShift logo

        Red Hat OpenShift

        1.1K
        1.2K
        480
        Red Hat's free Platform as a Service (PaaS) for hosting Java, PHP, Ruby, Python, Node.js, and Perl apps
        1.1K
        1.2K
        + 1
        480
        PROS OF RED HAT OPENSHIFT
        • 97
          Good free plan
        • 61
          Open Source
        • 45
          Easy setup
        • 41
          Nodejs support
        • 39
          Well documented
        • 31
          Custom domains
        • 27
          Mongodb support
        • 26
          Clean and simple architecture
        • 24
          PHP support
        • 20
          Customizable environments
        • 10
          Ability to run CRON jobs
        • 8
          Easier than Heroku for a WordPress blog
        • 6
          Autoscaling
        • 6
          Easy deployment
        • 6
          PostgreSQL support
        • 6
          Good balance between Heroku and AWS for flexibility
        • 5
          Free, Easy Setup, Lot of Gear or D.I.Y Gear
        • 4
          Shell access to gears
        • 3
          Great Support
        • 2
          Overly complicated and over engineered in majority of e
        • 2
          Its free and offer custom domain usage
        • 2
          Golang support
        • 1
          No credit card needed
        • 1
          This is the only free one among the three as of today
        • 1
          Meteor support
        • 1
          High Security
        • 1
          Logging & Metrics
        • 1
          because it is easy to manage
        • 1
          Autoscaling at a good price point
        • 1
          Easy setup and great customer support
        • 1
          Great free plan with excellent support
        CONS OF RED HAT OPENSHIFT
        • 2
          Decisions are made for you, limiting your options
        • 2
          License cost
        • 1
          Behind, sometimes severely, the upstreams

        related Red Hat OpenShift posts

        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber · | 38 upvotes · 4.1M 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
        Michael Ionita

        We use Kubernetes because we decided to migrate to a hosted cluster (not AWS) and still be able to scale our clusters up and down depending on load. By wrapping it with OpenShift we are now able to easily adapt to demand but also able to separate concerns into separate Pods depending on use-cases we have.

        See more
        VirtualBox logo

        VirtualBox

        22.2K
        17.3K
        1.1K
        Run nearly any operating system on a single machine and to freely switch between OS instances running simultaneously
        22.2K
        17.3K
        + 1
        1.1K
        PROS OF VIRTUALBOX
        • 359
          Free
        • 231
          Easy
        • 169
          Default for vagrant
        • 110
          Fast
        • 73
          Starts quickly
        • 45
          Open-source
        • 42
          Running in background
        • 41
          Simple, yet comprehensive
        • 27
          Default for boot2docker
        • 21
          Extensive customization
        • 2
          Free to use
        • 1
          Cross-platform
        • 1
          Mouse integration
        • 1
          Easy tool
        CONS OF VIRTUALBOX
          Be the first to leave a con

          related VirtualBox posts

          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.1M 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 · | 23 upvotes · 4.5M 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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