Alternatives to Cucumber logo

Alternatives to Cucumber

Selenium, RSpec, TestNG, JUnit, and Celery are the most popular alternatives and competitors to Cucumber.
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What is Cucumber and what are its top alternatives?

Cucumber is a popular BDD (Behavior-Driven Development) tool that allows for the creation of executable specifications written in a language called Gherkin. It helps in bridging the communication gap between stakeholders and developers by defining application behavior in plain text. Key features of Cucumber include its support for multiple programming languages, integration with various testing frameworks, and easy collaboration among team members. However, Cucumber may have a steep learning curve for beginners and can be time-consuming to set up and maintain.

  1. SpecFlow: SpecFlow is a BDD tool for .NET that integrates with Visual Studio and provides seamless integration with various testing frameworks. Pros include easy integration with popular IDEs, support for multiple languages, and a strong community. Cons may include a slight learning curve for beginners.
  2. JBehave: JBehave is a BDD framework for Java that allows for the creation of human-readable stories. Key features include seamless integration with Java tools, support for different testing levels, and easy reporting capabilities. Pros include a simple syntax and easy maintenance, while cons may include limited community support.
  3. Serenity BDD: Serenity BDD is an open-source library that combines BDD, automated acceptance testing, and reporting capabilities. Features include reusable test scripts, detailed reporting, and integration with various tools. Pros include comprehensive documentation and integration with CI/CD pipelines, while cons may include a learning curve for beginners.
  4. Robot Framework: Robot Framework is an open-source, generic test automation framework that supports BDD and ATDD. Key features include keyword-driven testing, easy test data input, and clear log reports. Pros include a simple syntax and easy extensibility, while cons may include limited support for programming languages other than Python.
  5. Gauge: Gauge is an open-source BDD framework that supports various programming languages and IDEs. Features include easy test automation, custom DSL creation, and parallel test execution. Pros include a lightweight framework and easy integration with CI tools, while cons may include limited community support.
  6. FitNesse: FitNesse is a collaborative BDD tool that allows for the creation of executable specifications in a wiki format. Key features include easy collaboration, dynamic test data, and automated test execution. Pros include a simple setup process and real-time test feedback, while cons may include limited support for complex test scenarios.
  7. Behave: Behave is a Python BDD framework that leverages the Gherkin syntax for writing feature files. Features include easy test creation, integration with various testing tools, and support for parallel testing. Pros include a simple syntax and easy integration with Python libraries, while cons may include limited support for non-Python projects.
  8. TestComplete: TestComplete is a comprehensive test automation platform that supports BDD testing with its keyword-driven approach. Key features include cross-browser testing, built-in object recognition, and easy scriptless testing. Pros include a user-friendly interface and extensive support for various technologies, while cons may include a higher cost compared to other tools.
  9. Karate: Karate is an open-source BDD framework for API testing that uses a Cucumber-like syntax. Features include easy test creation, support for HTTP, SOAP, and GraphQL services, and parallel test execution. Pros include seamless integration with REST APIs and easy data-driven testing, while cons may include limited support for UI testing.
  10. Behat: Behat is a PHP BDD framework that enables the creation of human-readable, reusable test scripts. Key features include support for different testing levels, integration with various PHP frameworks, and easy extensibility. Pros include a simple setup process and seamless integration with PHP projects, while cons may include a limited learning curve for beginners.

Top Alternatives to Cucumber

  • Selenium
    Selenium

    Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that. Boring web-based administration tasks can (and should!) also be automated as well. ...

  • RSpec
    RSpec

    Behaviour Driven Development for Ruby. Making TDD Productive and Fun.

  • TestNG
    TestNG

    It is a testing framework designed to simplify a broad range of testing needs, it covers all categories of tests: unit, functional, end-to-end, integration, etc.Run your tests in arbitrarily big thread pools with various policies available (all methods in their own thread, one thread per test class, etc. ...

  • JUnit
    JUnit

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

  • Celery
    Celery

    Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. ...

  • 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. ...

Cucumber alternatives & related posts

Selenium logo

Selenium

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Web Browser Automation
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PROS OF SELENIUM
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    Automates browsers
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    Testing
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    Essential tool for running test automation
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    Record-Playback
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    Remote Control
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    Data crawling
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    Supports end to end testing
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    Easy set up
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    Functional testing
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    The Most flexible monitoring system
  • 3
    End to End Testing
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    Easy to integrate with build tools
  • 2
    Comparing the performance selenium is faster than jasm
  • 2
    Record and playback
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    Compatible with Python
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    Easy to scale
  • 2
    Integration Tests
  • 0
    Integrated into Selenium-Jupiter framework
CONS OF SELENIUM
  • 8
    Flaky tests
  • 4
    Slow as needs to make browser (even with no gui)
  • 2
    Update browser drivers

related Selenium posts

Kamil Kowalski
Lead Architect at Fresha · | 28 upvotes · 4.1M views

When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.

See more
Benjamin Poon
QA Manager - Engineering at HBC Digital · | 8 upvotes · 2.2M views

For our digital QA organization to support a complex hybrid monolith/microservice architecture, our team took on the lofty goal of building out a commonized UI test automation framework. One of the primary requisites included a technical minimalist threshold such that an engineer or analyst with fundamental knowledge of JavaScript could automate their tests with greater ease. Just to list a few: - Nightwatchjs - Selenium - Cucumber - GitHub - Go.CD - Docker - ExpressJS - React - PostgreSQL

With this structure, we're able to combine the automation efforts of each team member into a centralized repository while also providing new relevant metrics to business owners.

See more
RSpec logo

RSpec

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Behaviour Driven Development for Ruby
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      I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

      We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

      Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

      We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

      Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

      See more
      Simon Bettison
      Managing Director at Bettison.org Limited · | 8 upvotes · 825.6K views

      In 2012 we made the very difficult decision to entirely re-engineer our existing monolithic LAMP application from the ground up in order to address some growing concerns about it's long term viability as a platform.

      Full application re-write is almost always never the answer, because of the risks involved. However the situation warranted drastic action as it was clear that the existing product was going to face severe scaling issues. We felt it better address these sooner rather than later and also take the opportunity to improve the international architecture and also to refactor the database in. order that it better matched the changes in core functionality.

      PostgreSQL was chosen for its reputation as being solid ACID compliant database backend, it was available as an offering AWS RDS service which reduced the management overhead of us having to configure it ourselves. In order to reduce read load on the primary database we implemented an Elasticsearch layer for fast and scalable search operations. Synchronisation of these indexes was to be achieved through the use of Sidekiq's Redis based background workers on Amazon ElastiCache. Again the AWS solution here looked to be an easy way to keep our involvement in managing this part of the platform at a minimum. Allowing us to focus on our core business.

      Rails ls was chosen for its ability to quickly get core functionality up and running, its MVC architecture and also its focus on Test Driven Development using RSpec and Selenium with Travis CI providing continual integration. We also liked Ruby for its terse, clean and elegant syntax. Though YMMV on that one!

      Unicorn was chosen for its continual deployment and reputation as a reliable application server, nginx for its reputation as a fast and stable reverse-proxy. We also took advantage of the Amazon CloudFront CDN here to further improve performance by caching static assets globally.

      We tried to strike a balance between having control over management and configuration of our core application with the convenience of being able to leverage AWS hosted services for ancillary functions (Amazon SES , Amazon SQS Amazon Route 53 all hosted securely inside Amazon VPC of course!).

      Whilst there is some compromise here with potential vendor lock in, the tasks being performed by these ancillary services are no particularly specialised which should mitigate this risk. Furthermore we have already containerised the stack in our development using Docker environment, and looking to how best to bring this into production - potentially using Amazon EC2 Container Service

      See more
      TestNG logo

      TestNG

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      A testing framework inspired from JUnit and NUnit
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          Joshua Dean Küpper
          CEO at Scrayos UG (haftungsbeschränkt) · | 1 upvote · 565.3K views

          We use JUnit for our Java Unit and Integration tests in Version 5. Combined with @JMockit2 and @truth (from Google) we perform all kinds of tests on our minecraft, standalone and microservice architecture.

          We prefer JUnit over TestNG because of the bigger community, better support and the generally more agile development. JUnit integrates nicely with most software, while TestNG support is a little more limited.

          See more
          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
              Celery logo

              Celery

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                Scheduled Task
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                Various backend broker
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                Easy to use
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                Great community
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                Workflow
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                Free
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              CONS OF CELERY
              • 4
                Sometimes loses tasks
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              related Celery posts

              James Cunningham
              Operations Engineer at Sentry · | 21 upvotes · 361.8K views

              Sentry started as (and remains) an open-source project, growing out of an error logging tool built in 2008. That original build nine years ago was Django and Celery (Python’s asynchronous task codebase), with PostgreSQL as the database and Redis as the power behind Celery.

              We displayed a truly shrewd notion of branding even then, giving the project a catchy name that companies the world over remain jealous of to this day: django-db-log. For the longest time, Sentry’s subtitle on GitHub was “A simple Django app, built with love.” A slightly more accurate description probably would have included Starcraft and Soylent alongside love; regardless, this captured what Sentry was all about.

              #MessageQueue #InMemoryDatabases

              See more
              James Cunningham
              Operations Engineer at Sentry · | 18 upvotes · 1.8M views
              Shared insights
              on
              CeleryCeleryRabbitMQRabbitMQ
              at

              As Sentry runs throughout the day, there are about 50 different offline tasks that we execute—anything from “process this event, pretty please” to “send all of these cool people some emails.” There are some that we execute once a day and some that execute thousands per second.

              Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

              #MessageQueue

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              Git logo

              Git

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              PROS OF GIT
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                Efficient branching and merging
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                Fast
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                Open source
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                Better than svn
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                Great command-line application
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                Simple
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                Free
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                Easy to use
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                Does not require server
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                Distributed
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                Small & Fast
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                Feature based workflow
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                Staging Area
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                Most wide-spread VSC
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                Role-based codelines
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                Disposable Experimentation
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                Frictionless Context Switching
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                Data Assurance
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                Efficient
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                Just awesome
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                Github integration
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                Easy branching and merging
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                Compatible
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                Flexible
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                Possible to lose history and commits
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                Rebase supported natively; reflog; access to plumbing
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                Light
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                Team Integration
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                Fast, scalable, distributed revision control system
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                Easy
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                Flexible, easy, Safe, and fast
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                CLI is great, but the GUI tools are awesome
              • 1
                It's what you do
              • 0
                Phinx
              CONS OF GIT
              • 16
                Hard to learn
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                Inconsistent command line interface
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                Easy to lose uncommitted work
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                Worst documentation ever possibly made
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                Awful merge handling
              • 3
                Unexistent preventive security flows
              • 3
                Rebase hell
              • 2
                Ironically even die-hard supporters screw up badly
              • 2
                When --force is disabled, cannot rebase
              • 1
                Doesn't scale for big data

              related Git posts

              Simon Reymann
              Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.2M 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 · | 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
              GitHub logo

              GitHub

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                Great for team collaboration
              • 867
                Easy setup
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                Issue tracker
              • 487
                Great community
              • 483
                Remote team collaboration
              • 449
                Great way to share
              • 442
                Pull request and features planning
              • 147
                Just works
              • 132
                Integrated in many tools
              • 122
                Free Public Repos
              • 116
                Github Gists
              • 113
                Github pages
              • 83
                Easy to find repos
              • 62
                Open source
              • 60
                Easy to find projects
              • 60
                It's free
              • 56
                Network effect
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                Extensive API
              • 43
                Organizations
              • 42
                Branching
              • 34
                Developer Profiles
              • 32
                Git Powered Wikis
              • 30
                Great for collaboration
              • 24
                It's fun
              • 23
                Clean interface and good integrations
              • 22
                Community SDK involvement
              • 20
                Learn from others source code
              • 16
                Because: Git
              • 14
                It integrates directly with Azure
              • 10
                Standard in Open Source collab
              • 10
                Newsfeed
              • 8
                Fast
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                Beautiful user experience
              • 8
                It integrates directly with Hipchat
              • 7
                Easy to discover new code libraries
              • 6
                Smooth integration
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                Integrations
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                Graphs
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                Nice API
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                It's awesome
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                Cloud SCM
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                Quick Onboarding
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                Remarkable uptime
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                CI Integration
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                Reliable
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                Hands down best online Git service available
              • 4
                Version Control
              • 4
                Unlimited Public Repos at no cost
              • 4
                Simple but powerful
              • 4
                Loved by developers
              • 4
                Free HTML hosting
              • 4
                Uses GIT
              • 4
                Security options
              • 4
                Easy to use and collaborate with others
              • 3
                Easy deployment via SSH
              • 3
                Ci
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                IAM
              • 3
                Nice to use
              • 2
                Easy and efficient maintainance of the projects
              • 2
                Beautiful
              • 2
                Self Hosted
              • 2
                Issues tracker
              • 2
                Easy source control and everything is backed up
              • 2
                Never dethroned
              • 2
                All in one development service
              • 2
                Good tools support
              • 2
                Free HTML hostings
              • 2
                IAM integration
              • 2
                Very Easy to Use
              • 2
                Easy to use
              • 2
                Leads the copycats
              • 2
                Free private repos
              • 1
                Profound
              • 1
                Dasf
              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
              • 1
                Expensive

              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

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              Visual Studio Code

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              2.3K
              Build and debug modern web and cloud applications, by Microsoft
              179.3K
              163.5K
              + 1
              2.3K
              PROS OF VISUAL STUDIO CODE
              • 340
                Powerful multilanguage IDE
              • 308
                Fast
              • 193
                Front-end develop out of the box
              • 158
                Support TypeScript IntelliSense
              • 142
                Very basic but free
              • 126
                Git integration
              • 106
                Intellisense
              • 78
                Faster than Atom
              • 53
                Better ui, easy plugins, and nice git integration
              • 45
                Great Refactoring Tools
              • 44
                Good Plugins
              • 42
                Terminal
              • 38
                Superb markdown support
              • 36
                Open Source
              • 35
                Extensions
              • 26
                Awesome UI
              • 26
                Large & up-to-date extension community
              • 24
                Powerful and fast
              • 22
                Portable
              • 18
                Best code editor
              • 18
                Best editor
              • 17
                Easy to get started with
              • 15
                Lots of extensions
              • 15
                Good for begginers
              • 15
                Crossplatform
              • 15
                Built on Electron
              • 14
                Extensions for everything
              • 14
                Open, cross-platform, fast, monthly updates
              • 14
                All Languages Support
              • 13
                Easy to use and learn
              • 12
                "fast, stable & easy to use"
              • 12
                Extensible
              • 11
                Ui design is great
              • 11
                Totally customizable
              • 11
                Git out of the box
              • 11
                Useful for begginer
              • 11
                Faster edit for slow computer
              • 10
                SSH support
              • 10
                Great community
              • 10
                Fast Startup
              • 9
                Works With Almost EveryThing You Need
              • 9
                Great language support
              • 9
                Powerful Debugger
              • 9
                It has terminal and there are lots of shortcuts in it
              • 8
                Can compile and run .py files
              • 8
                Python extension is fast
              • 7
                Features rich
              • 7
                Great document formater
              • 6
                He is not Michael
              • 6
                Extension Echosystem
              • 6
                She is not Rachel
              • 6
                Awesome multi cursor support
              • 5
                VSCode.pro Course makes it easy to learn
              • 5
                Language server client
              • 5
                SFTP Workspace
              • 5
                Very proffesional
              • 5
                Easy azure
              • 4
                Has better support and more extentions for debugging
              • 4
                Supports lots of operating systems
              • 4
                Excellent as git difftool and mergetool
              • 4
                Virtualenv integration
              • 3
                Better autocompletes than Atom
              • 3
                Has more than enough languages for any developer
              • 3
                'batteries included'
              • 3
                More tools to integrate with vs
              • 3
                Emmet preinstalled
              • 2
                VS Code Server: Browser version of VS Code
              • 2
                CMake support with autocomplete
              • 2
                Microsoft
              • 2
                Customizable
              • 2
                Light
              • 2
                Big extension marketplace
              • 2
                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
              • 8
                Huge cpu usage with few installed extension
              • 8
                Microsoft sends telemetry data
              • 7
                Poor in PHP
              • 6
                It's MicroSoft
              • 3
                Poor in Python
              • 3
                No Built in Browser Preview
              • 3
                No color Intergrator
              • 3
                Very basic for java development and buggy at times
              • 3
                No built in live Preview
              • 3
                Electron
              • 2
                Bad Plugin Architecture
              • 2
                Powered by Electron
              • 1
                Terminal does not identify path vars sometimes
              • 1
                Slow C++ Language Server

              related Visual Studio Code posts

              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 · 11.2M 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.
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