Alternatives to Mockito logo

Alternatives to Mockito

JUnit, Appium, Robolectric, mockk, and Git are the most popular alternatives and competitors to Mockito.
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What is Mockito and what are its top alternatives?

Mockito is a popular Java framework used for creating mock objects in automated unit tests. It provides a simple and clean API for writing test cases and verifying behavior through mock objects. Mockito allows developers to simulate interactions with dependencies without the need for complex setups or external frameworks. However, one limitation of Mockito is that it does not support mocking of final classes or methods.

  1. PowerMock: PowerMock extends Mockito and other testing frameworks to allow mocking of final classes and static methods. Key features include support for mocking final classes and methods, integration with Mockito, JUnit, and TestNG, and compatibility with popular build tools. Pros include flexibility in mocking final classes and methods, but cons include increased complexity and potential for misuse.
  2. JMockit: JMockit is a mocking framework that offers advanced features for creating mock objects and verifying behavior. Key features include support for mocking final classes and methods, integration with JUnit and TestNG, and built-in support for code coverage analysis. Pros include powerful mocking capabilities, but cons include a steeper learning curve compared to Mockito.
  3. Mockk: Mockk is a mocking framework for Kotlin that provides a concise and expressive syntax for creating mock objects and stubbing behavior. Key features include support for Kotlin DSL, integration with popular testing libraries, and compatibility with Android development. Pros include Kotlin language support, but cons include limited documentation and community support compared to Mockito.
  4. EasyMock: EasyMock is a Java mocking framework that focuses on simplicity and ease of use for creating mock objects. Key features include support for creating mock objects with minimal code, integration with JUnit and TestNG, and compatibility with popular IDEs. Pros include simplicity in creating mock objects, but cons include less flexibility compared to Mockito.
  5. Spock Framework: The Spock Framework is a testing and specification framework for Java and Groovy that offers built-in mocking capabilities. Key features include support for writing specification-based test cases, integration with JUnit and TestNG, and a concise syntax for creating mock objects. Pros include expressive test case syntax, but cons include a learning curve for developers new to the framework.
  6. WireMock: WireMock is a standalone stubbing and mocking web service for testing HTTP-based APIs. Key features include support for creating mock HTTP endpoints, request matching and response stubbing, and integration with popular testing frameworks. Pros include comprehensive support for testing web services, but cons include setup and configuration overhead compared to Mockito for unit testing.
  7. PowerMockito: PowerMockito combines PowerMock and Mockito to provide enhanced mocking capabilities for final classes and static methods in Java tests. Key features include support for mocking final classes and methods, integration with Mockito, JUnit, and TestNG, and compatibility with popular build tools. Pros include extended capabilities for mocking final classes and methods, but cons include potential for misuse and increased complexity.
  8. WireMock.Net: WireMock.Net is a port of the WireMock HTTP stubbing and mocking web service for .NET applications. Key features include support for mocking HTTP endpoints, request matching and response stubbing, and integration with popular testing frameworks in the .NET ecosystem. Pros include the ability to test HTTP-based APIs in .NET applications, but cons include setup and configuration overhead compared to Mockito for unit testing.
  9. MockitoKotlin: MockitoKotlin is an idiomatic Kotlin wrapper for Mockito that provides a more Kotlin-friendly API for creating mock objects in tests. Key features include extension functions for Mockito classes, null safety in Kotlin, and seamless integration with Kotlin test frameworks. Pros include Kotlin language support and improved syntax for Mockito in Kotlin projects, but cons include the need for additional dependencies in Kotlin projects.
  10. Mockito2: Mockito2 is the latest version of the Mockito framework, which includes new features and improvements over the original Mockito library. Key features include enhanced mocking capabilities, improved error messages, and better integration with Java 8 features. Pros include continued support and updates for the Mockito framework, but cons include potential compatibility issues with existing Mockito codebases.

Top Alternatives to Mockito

  • JUnit
    JUnit

    JUnit is a simple framework to write repeatable tests. It is an instance of the xUnit architecture for unit testing frameworks. ...

  • Appium
    Appium

    Appium is an open source test automation framework for use with native, hybrid, and mobile web apps. It drives iOS and Android apps using the WebDriver protocol. Appium is sponsored by Sauce Labs and a thriving community of open source developers. ...

  • Robolectric
    Robolectric

    It is a framework that brings fast and reliable unit tests to Android. Tests run inside the JVM on your workstation in seconds. Test drive your Android application with robolectric ...

  • mockk
    mockk

    It is an open-source library focused on making mocking in Kotlin great. It is a library with the possibility of mocking default arguments, final classes, varargs, coroutines and extension methods. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

  • Visual Studio Code
    Visual Studio Code

    Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows. ...

  • 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 ...

Mockito alternatives & related posts

JUnit logo

JUnit

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A programmer-oriented testing framework for Java
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      Jack Graves

      We use JUnit and Jest to perform the bulk of our automated test scenarios, with additional work with Apache JMeter for performance testing - for example, the Atlassian Data Center compliance testing is performed with JMeter. Jest provides testing for the React interfaces, which make up the backend of our App offerings. JUnit is used for Unit Testing our Server-based Apps. Mocha is another tool we use.

      See more

      We are looking for a Testing Tool that can integrate with Java/ React/ Go/ Python/ Node.js. Which amongst the three tools JUnit, NUnit & Selenium would be the best for this use case?

      See more
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      Appium

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      Automation for iOS and Android Apps
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        related Appium posts

        Looking for some advice: we are planning to create a hybrid app for both iOS and Android; this app will consume a REST API. We are looking for a tool for this development with the following attributes:

        • Shallow learning curve; easiness to adopt (all team is new into mobile development, with diverse backgrounds: Java, Python & AngularJS),

        • Easiness to test (we discarded Angular-based tools already: creating a unit test in Angular we considered time-consuming and low value. At this point of the project, we cannot afford UI testing with Selenium/Appium based tools).

        • So far, we are not considering any specific capability of the device. Still, in the mid/long term, we would require the usage of GPS (geolocalization) and accelerometer (not sure if it's possible to use it from a hybrid app). Suggest any other tool if you wish.

        See more
        Kevin Roulleau
        QA Engineer Freelance at happn · | 5 upvotes · 1.2M views

        I chose WebdriverIO and Appium to implement a E2E tests solution on a native mobile app. WebdriverIO goes well beyond just implementing the Selenium / Appium protocol and allows to run tests in parallel out of the box. Appium has the big advantage of supporting iOS and Android platforms, so the test codebase and tools are exactly the same, which greatly reduces the learning curve and implementation time.

        See more
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            mockk

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                Git

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                Simon Reymann
                Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11M 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 · 9.7M 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
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                • 30
                  Great for collaboration
                • 24
                  It's fun
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                  Clean interface and good integrations
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                • 16
                  Because: Git
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                • 4
                  Uses GIT
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                • 3
                  Easy deployment via SSH
                • 3
                  Ci
                • 3
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                • 3
                  Nice to use
                • 2
                  Easy and efficient maintainance of the projects
                • 2
                  Beautiful
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                  Self Hosted
                • 2
                  Issues tracker
                • 2
                  Easy source control and everything is backed up
                • 2
                  Never dethroned
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                  All in one development service
                • 2
                  Good tools support
                • 2
                  Free HTML hostings
                • 2
                  IAM integration
                • 2
                  Very Easy to Use
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                  Leads the copycats
                • 2
                  Free private repos
                • 1
                  Profound
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                CONS OF GITHUB
                • 55
                  Owned by micrcosoft
                • 38
                  Expensive for lone developers that want private repos
                • 15
                  Relatively slow product/feature release cadence
                • 10
                  API scoping could be better
                • 9
                  Only 3 collaborators for private repos
                • 4
                  Limited featureset for issue management
                • 3
                  Does not have a graph for showing history like git lens
                • 2
                  GitHub Packages does not support SNAPSHOT versions
                • 1
                  No multilingual interface
                • 1
                  Takes a long time to commit
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                related GitHub posts

                Johnny Bell

                I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

                I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

                I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

                Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

                Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

                With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

                If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

                See more

                Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

                Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

                Check Out My Architecture: CLICK ME

                Check out the GitHub repo attached

                See more
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                Visual Studio Code

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                • 5
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                • 4
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                  Excellent as git difftool and mergetool
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                • 3
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                  Has more than enough languages for any developer
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                  'batteries included'
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                  More tools to integrate with vs
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                  Emmet preinstalled
                • 2
                  VS Code Server: Browser version of VS Code
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                  Microsoft
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                  Big extension marketplace
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                  Fast and ruby is built right in
                • 1
                  File:///C:/Users/ydemi/Downloads/yuksel_demirkaya_webpa
                CONS OF VISUAL STUDIO CODE
                • 46
                  Slow startup
                • 29
                  Resource hog at times
                • 20
                  Poor refactoring
                • 13
                  Poor UI Designer
                • 11
                  Weak Ui design tools
                • 10
                  Poor autocomplete
                • 8
                  Super Slow
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                • 8
                  Microsoft sends telemetry data
                • 7
                  Poor in PHP
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                  It's MicroSoft
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                • 3
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                • 2
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                • 1
                  Terminal does not identify path vars sometimes
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                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...

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                Simon Reymann
                Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11M 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.
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                related Docker posts

                Simon Reymann
                Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11M 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 · 9.7M 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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