What is Jasmine and what are its top alternatives?
Jasmine is a popular behavior-driven development (BDD) testing framework for JavaScript. It provides a clean, readable syntax for writing tests and is easy to set up and use. Key features of Jasmine include spies, mocks, and asynchronous testing support. However, Jasmine can be verbose in terms of syntax, leading to longer test scripts and potential readability issues.
- Mocha: Mocha is a flexible testing framework that allows you to use any assertion library. It supports both synchronous and asynchronous testing and provides a variety of reporting options. Pros: flexible, supports multiple assertion libraries. Cons: may require additional libraries for certain features.
- Jest: Jest is a zero-configuration testing framework that comes with a built-in assertion library and mocking support. It is known for its fast and parallel test execution. Pros: built-in assertions and mocking, easy setup. Cons: can be slow for larger projects.
- Karma: Karma is a test runner that works with multiple testing frameworks like Jasmine, Mocha, and QUnit. It allows you to run tests on real devices and browsers. Pros: compatibility with various testing frameworks, real device testing. Cons: complex configuration for beginners.
- Cypress: Cypress is an end-to-end testing framework that includes a built-in assertion library and allows you to write tests in a more user-friendly way. It also provides a powerful GUI for debugging tests. Pros: end-to-end testing capabilities, easy setup. Cons: limited to testing in a browser environment.
- Ava: Ava is a test runner focused on speed and parallelization. It runs tests concurrently to reduce overall test time. Pros: fast execution, parallel testing. Cons: limited built-in assertions.
- Protractor: Protractor is an end-to-end testing framework specifically designed for Angular applications. It supports Jasmine for writing tests and interacts with the application like a real user. Pros: designed for Angular apps, real user interactions. Cons: may require additional setup for non-Angular projects.
- QUnit: QUnit is a lightweight testing framework developed by the jQuery team. It is easy to set up and is focused on simplicity and performance. Pros: lightweight, simple setup. Cons: lacks some advanced features compared to other frameworks.
- Chai: Chai is an assertion library that can be used with any testing framework. It provides a variety of assertion styles and interfaces to suit your testing needs. Pros: flexible assertion styles, works with any framework. Cons: may require additional setup when used with certain frameworks.
- Tape: Tape is a minimalistic testing framework that is easy to set up and use. It focuses on simplicity and modularity, making it a good choice for smaller projects. Pros: minimalistic, easy to use. Cons: lacks some advanced features found in other frameworks.
- Jasmine-Matchers: Jasmine-Matchers is a plugin for Jasmine that provides additional matchers for more readable and expressive tests. It enhances the built-in matcher library of Jasmine. Pros: extended matchers, improved readability. Cons: may add complexity to test scripts.
Top Alternatives to Jasmine
- Mocha
Mocha is a feature-rich JavaScript test framework running on node.js and the browser, making asynchronous testing simple and fun. Mocha tests run serially, allowing for flexible and accurate reporting, while mapping uncaught exceptions to the correct test cases. ...
- Jest
Jest provides you with multiple layers on top of Jasmine.
- Karma
Karma is not a testing framework, nor an assertion library. Karma just launches a HTTP server, and generates the test runner HTML file you probably already know from your favourite testing framework. So for testing purposes you can use pretty much anything you like. ...
- 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 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
Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows. ...
- 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 ...
- npm
npm is the command-line interface to the npm ecosystem. It is battle-tested, surprisingly flexible, and used by hundreds of thousands of JavaScript developers every day. ...
Jasmine alternatives & related posts
- Open source137
- Simple102
- Promise support81
- Flexible48
- Easy to add support for Generators29
- For browser and server testing12
- Curstom assertion libraries7
- Works with Karma5
- No other better tools3
- Simple setup1
- Works with saucelabs1
- Lots of tutorials and help online1
- Default reporter is nice, clean, and itemized1
- Works with BrowserStack1
- Simple integration testing1
- Cannot test a promisified functions without assertion3
- No assertion count in results2
- Not as many reporter options as Jest1
related Mocha posts
Needs advice on code coverage tool in Node.js/ExpressJS with External API Testing Framework
Hello community,
I have a web application with the backend developed using Node.js and Express.js. The backend server is in one directory, and I have a separate API testing framework, made using SuperTest, Mocha, and Chai, in another directory. The testing framework pings the API, retrieves responses, and performs validations.
I'm currently looking for a code coverage tool that can accurately measure the code coverage of my backend code when triggered by the API testing framework. I've tried using Istanbul and NYC with instrumented code, but the results are not as expected.
Could you please recommend a reliable code coverage tool or suggest an approach to effectively measure the code coverage of my Node.js/Express.js backend code in this setup?
I use both mocha and Jest because:
I don't care whether teams use Jest or Mocha. But jest is way too overhyped. Most devs are writing integration tests and think that it's so much better but frankly I don't write integration tests as the way to get both design feedback and confidence when I code. I adhere to the test pyramid, not ice cream cone or the dumb "trophy"
I TDD, so I only ever use the "API" of test frameworks. I don't do a lot of integration tests for TDD and all the bells and whistles Jest provides you from the command-line I just don't need. And I certainly do not care about or touch Jest Snapshots, I despise them
My tests are fast enough because I write isolated tests with TDD, so I don't run into performance issues. Example: I write my tests in a way that I can run 300 tests in literally 1 second with mocha. So the Jest ability to pinpoint and only run those tests which are affected by code changes. I want to run all of them every time when I TDD. It's a different mindset when you TDD
I also mainly code in IntelliJ or WebStorm because I feel the tools in that IDE far surpass VSCode and I also love running the test UI runner in it vs. lousy command-line
I feel both mocha and Jest read just fine in terms of code readability. Jest might have shorter assertion syntax but I don't really care. I just care that I can read the damn test and my tests are written well and my test descriptions, as well as the code itself including constants represent business language, not technical. I care most about BDD, clean code, 4 rules of simple design, and SOLID
I don't like using mock frameworks so no I don't use Jest's Mocking framework. I don't have to mock a lot in my tests due to the nature of how I strive to code...I keep my design simple and modular using principals such as clean code and 4 rules of simple design. If I must mock, I create very simple custom mocks with JS
On the contrary to the belief that integration tests and mount are the way to go (this belief drives me absolutely crazy, especially Dodd's promoting that), I TDD with shallow & enzyme. My tests are simple. My design is driven by my tests and my tests give me quick and useful feedback. I have a course I'm working on coming out soon on TDD with React to show you how to truly test the FE and why the ice cream cone and trophy suck (you're being scammed people). Watch for that here: https://twitter.com/DaveSchinkel/status/1062267649235791873
Don't forget to upvote this post!
Mocha Jest JavaScript React @jsdom Enzyme #tdd #bdd #testdrivendevelopment
- Open source36
- Mock by default makes testing much simpler32
- Testing React Native Apps23
- Parallel test running20
- Fast16
- Bundled with JSDOM to enable DOM testing13
- Mock by default screws up your classes, breaking tests8
- Out of the box code coverage7
- Promise support7
- One stop shop for unit testing6
- Great documentation3
- Assert Library Included2
- Built in watch option with interactive filtering menu1
- Preset support1
- Can be used for BDD0
- Karma0
- Documentation4
- Ambiguous configuration4
- Difficult3
- Many bugs still not fixed months/years after reporting2
- Multiple error messages for same error2
- Difficult to run single test/describe/file2
- Ambiguous2
- Bugged2
- BeforeAll timing out makes all passing tests fail1
- Slow1
- Reporter is too general1
- Unstable1
- Bad docs1
- Still does't support .mjs files natively1
- Can't fail beforeAll to abort tests1
- Interaction with watch mode on terminal0
related Jest posts
Our whole Vue.js frontend stack (incl. SSR) consists of the following tools:
- Nuxt.js consisting of Vue CLI, Vue Router, vuex, Webpack and Sass (Bundler for HTML5, CSS 3), Babel (Transpiler for JavaScript),
- Vue Styleguidist as our style guide and pool of developed Vue.js components
- Vuetify as Material Component Framework (for fast app development)
- TypeScript as programming language
- Apollo / GraphQL (incl. GraphiQL) for data access layer (https://apollo.vuejs.org/)
- ESLint, TSLint and Prettier for coding style and code analyzes
- Jest as testing framework
- Google Fonts and Font Awesome for typography and icon toolkit
- NativeScript-Vue for mobile development
The main reason we have chosen Vue.js over React and AngularJS is related to the following artifacts:
- Empowered HTML. Vue.js has many similar approaches with Angular. This helps to optimize HTML blocks handling with the use of different components.
- Detailed documentation. Vue.js has very good documentation which can fasten learning curve for developers.
- Adaptability. It provides a rapid switching period from other frameworks. It has similarities with Angular and React in terms of design and architecture.
- Awesome integration. Vue.js can be used for both building single-page applications and more difficult web interfaces of apps. Smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.
- Large scaling. Vue.js can help to develop pretty large reusable templates.
- Tiny size. Vue.js weights around 20KB keeping its speed and flexibility. It allows reaching much better performance in comparison to other frameworks.
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.
- Test Runner61
- Open source35
- Continuous Integration27
- Great for running tests22
- Test on Real Devices18
- Backed by google11
- Easy Debugging5
- Remote Control2
- Slow, because tests are run in a real browser1
- Requires the use of hacks to find tests dynamically1
related Karma posts
Protractor or Cypress for ionic-angular?
We have a huge ionic-angular app with almost 100 pages and 10+ injectables. There are no tests written yet. Before we start, we need some suggestions about the framework. Would you suggest Cypress or Angular's Protractor with Jasmine / Karma for a heavy ionic app with Angular?
Switched from Jasmine with Karma that come setup by Angular CLI to use Jest instead, since Jasmine and Karma were very finicky in my setup and had to be reconfigured frequently to run tests properly.
Jest was also easier to integrate into my workflow with Visual Studio Code.
- Distributed version control system1.4K
- Efficient branching and merging1.1K
- Fast959
- Open source845
- Better than svn726
- Great command-line application368
- Simple306
- Free291
- Easy to use232
- Does not require server222
- Distributed27
- Small & Fast22
- Feature based workflow18
- Staging Area15
- Most wide-spread VSC13
- Role-based codelines11
- Disposable Experimentation11
- Frictionless Context Switching7
- Data Assurance6
- Efficient5
- Just awesome4
- Github integration3
- Easy branching and merging3
- Compatible2
- Flexible2
- Possible to lose history and commits2
- Rebase supported natively; reflog; access to plumbing1
- Light1
- Team Integration1
- Fast, scalable, distributed revision control system1
- Easy1
- Flexible, easy, Safe, and fast1
- CLI is great, but the GUI tools are awesome1
- It's what you do1
- Phinx0
- Hard to learn16
- Inconsistent command line interface11
- Easy to lose uncommitted work9
- Worst documentation ever possibly made8
- Awful merge handling5
- Unexistent preventive security flows3
- Rebase hell3
- Ironically even die-hard supporters screw up badly2
- When --force is disabled, cannot rebase2
- Doesn't scale for big data1
related Git posts
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.
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.
GitHub
- Open source friendly1.8K
- Easy source control1.5K
- Nice UI1.3K
- Great for team collaboration1.1K
- Easy setup867
- Issue tracker504
- Great community487
- Remote team collaboration483
- Great way to share449
- Pull request and features planning442
- Just works147
- Integrated in many tools132
- Free Public Repos122
- Github Gists116
- Github pages113
- Easy to find repos83
- Open source62
- Easy to find projects60
- It's free60
- Network effect56
- Extensive API49
- Organizations43
- Branching42
- Developer Profiles34
- Git Powered Wikis32
- Great for collaboration30
- It's fun24
- Clean interface and good integrations23
- Community SDK involvement22
- Learn from others source code20
- Because: Git16
- It integrates directly with Azure14
- Standard in Open Source collab10
- Newsfeed10
- Fast8
- Beautiful user experience8
- It integrates directly with Hipchat8
- Easy to discover new code libraries7
- Smooth integration6
- Integrations6
- Graphs6
- Nice API6
- It's awesome6
- Cloud SCM6
- Quick Onboarding5
- Remarkable uptime5
- CI Integration5
- Reliable5
- Hands down best online Git service available5
- Version Control4
- Unlimited Public Repos at no cost4
- Simple but powerful4
- Loved by developers4
- Free HTML hosting4
- Uses GIT4
- Security options4
- Easy to use and collaborate with others4
- Easy deployment via SSH3
- Ci3
- IAM3
- Nice to use3
- Easy and efficient maintainance of the projects2
- Beautiful2
- Self Hosted2
- Issues tracker2
- Easy source control and everything is backed up2
- Never dethroned2
- All in one development service2
- Good tools support2
- Free HTML hostings2
- IAM integration2
- Very Easy to Use2
- Easy to use2
- Leads the copycats2
- Free private repos2
- Profound1
- Dasf1
- Owned by micrcosoft55
- Expensive for lone developers that want private repos38
- Relatively slow product/feature release cadence15
- API scoping could be better10
- Only 3 collaborators for private repos9
- Limited featureset for issue management4
- Does not have a graph for showing history like git lens3
- GitHub Packages does not support SNAPSHOT versions2
- No multilingual interface1
- Takes a long time to commit1
- Expensive1
related GitHub posts
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.
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
Visual Studio Code
- Powerful multilanguage IDE340
- Fast308
- Front-end develop out of the box193
- Support TypeScript IntelliSense158
- Very basic but free142
- Git integration126
- Intellisense106
- Faster than Atom78
- Better ui, easy plugins, and nice git integration53
- Great Refactoring Tools45
- Good Plugins44
- Terminal42
- Superb markdown support38
- Open Source36
- Extensions35
- Awesome UI26
- Large & up-to-date extension community26
- Powerful and fast24
- Portable22
- Best code editor18
- Best editor18
- Easy to get started with17
- Lots of extensions15
- Good for begginers15
- Crossplatform15
- Built on Electron15
- Extensions for everything14
- Open, cross-platform, fast, monthly updates14
- All Languages Support14
- Easy to use and learn13
- "fast, stable & easy to use"12
- Extensible12
- Ui design is great11
- Totally customizable11
- Git out of the box11
- Useful for begginer11
- Faster edit for slow computer11
- SSH support10
- Great community10
- Fast Startup10
- Works With Almost EveryThing You Need9
- Great language support9
- Powerful Debugger9
- It has terminal and there are lots of shortcuts in it9
- Can compile and run .py files8
- Python extension is fast8
- Features rich7
- Great document formater7
- He is not Michael6
- Extension Echosystem6
- She is not Rachel6
- Awesome multi cursor support6
- VSCode.pro Course makes it easy to learn5
- Language server client5
- SFTP Workspace5
- Very proffesional5
- Easy azure5
- Has better support and more extentions for debugging4
- Supports lots of operating systems4
- Excellent as git difftool and mergetool4
- Virtualenv integration4
- Better autocompletes than Atom3
- Has more than enough languages for any developer3
- 'batteries included'3
- More tools to integrate with vs3
- Emmet preinstalled3
- VS Code Server: Browser version of VS Code2
- CMake support with autocomplete2
- Microsoft2
- Customizable2
- Light2
- Big extension marketplace2
- Fast and ruby is built right in2
- File:///C:/Users/ydemi/Downloads/yuksel_demirkaya_webpa1
- Slow startup46
- Resource hog at times29
- Poor refactoring20
- Poor UI Designer13
- Weak Ui design tools11
- Poor autocomplete10
- Super Slow8
- Huge cpu usage with few installed extension8
- Microsoft sends telemetry data8
- Poor in PHP7
- It's MicroSoft6
- Poor in Python3
- No Built in Browser Preview3
- No color Intergrator3
- Very basic for java development and buggy at times3
- No built in live Preview3
- Electron3
- Bad Plugin Architecture2
- Powered by Electron2
- Terminal does not identify path vars sometimes1
- Slow C++ Language Server1
related Visual Studio Code posts
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...
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.
- Rapid integration and build up823
- Isolation692
- Open source521
- Testability and reproducibility505
- Lightweight460
- Standardization218
- Scalable185
- Upgrading / downgrading / application versions106
- Security88
- Private paas environments85
- Portability34
- Limit resource usage26
- Game changer17
- I love the way docker has changed virtualization16
- Fast14
- Concurrency12
- Docker's Compose tools8
- Fast and Portable6
- Easy setup6
- Because its fun5
- Makes shipping to production very simple4
- It's dope3
- Highly useful3
- Does a nice job hogging memory2
- Open source and highly configurable2
- Simplicity, isolation, resource effective2
- MacOS support FAKE2
- Its cool2
- Docker hub for the FTW2
- HIgh Throughput2
- Very easy to setup integrate and build2
- Package the environment with the application2
- Super2
- Asdfd0
- New versions == broken features8
- Unreliable networking6
- Documentation not always in sync6
- Moves quickly4
- Not Secure3
related Docker posts
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.
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.
- Best package management system for javascript647
- Open-source382
- Great community327
- More packages than rubygems, pypi, or packagist148
- Nice people matter112
- As fast as yarn but really free of facebook6
- Audit feature6
- Good following4
- Super fast1
- Stability1
- Problems with lockfiles5
- Bad at package versioning and being deterministic5
- Node-gyp takes forever3
- Super slow1
related npm posts
Our whole Node.js backend stack consists of the following tools:
- Lerna as a tool for multi package and multi repository management
- npm as package manager
- NestJS as Node.js framework
- TypeScript as programming language
- ExpressJS as web server
- Swagger UI for visualizing and interacting with the API’s resources
- Postman as a tool for API development
- TypeORM as object relational mapping layer
- JSON Web Token for access token management
The main reason we have chosen Node.js over PHP is related to the following artifacts:
- Made for the web and widely in use: Node.js is a software platform for developing server-side network services. Well-known projects that rely on Node.js include the blogging software Ghost, the project management tool Trello and the operating system WebOS. Node.js requires the JavaScript runtime environment V8, which was specially developed by Google for the popular Chrome browser. This guarantees a very resource-saving architecture, which qualifies Node.js especially for the operation of a web server. Ryan Dahl, the developer of Node.js, released the first stable version on May 27, 2009. He developed Node.js out of dissatisfaction with the possibilities that JavaScript offered at the time. The basic functionality of Node.js has been mapped with JavaScript since the first version, which can be expanded with a large number of different modules. The current package managers (npm or Yarn) for Node.js know more than 1,000,000 of these modules.
- Fast server-side solutions: Node.js adopts the JavaScript "event-loop" to create non-blocking I/O applications that conveniently serve simultaneous events. With the standard available asynchronous processing within JavaScript/TypeScript, highly scalable, server-side solutions can be realized. The efficient use of the CPU and the RAM is maximized and more simultaneous requests can be processed than with conventional multi-thread servers.
- A language along the entire stack: Widely used frameworks such as React or AngularJS or Vue.js, which we prefer, are written in JavaScript/TypeScript. If Node.js is now used on the server side, you can use all the advantages of a uniform script language throughout the entire application development. The same language in the back- and frontend simplifies the maintenance of the application and also the coordination within the development team.
- Flexibility: Node.js sets very few strict dependencies, rules and guidelines and thus grants a high degree of flexibility in application development. There are no strict conventions so that the appropriate architecture, design structures, modules and features can be freely selected for the development.
So when starting a new project you generally have your go to tools to get your site up and running locally, and some scripts to build out a production version of your site. Create React App is great for that, however for my projects I feel as though there is to much bloat in Create React App and if I use it, then I'm tied to React, which I love but if I want to switch it up to Vue or something I want that flexibility.
So to start everything up and running I clone my personal Webpack boilerplate - This is still in Webpack 3, and does need some updating but gets the job done for now. So given the name of the repo you may have guessed that yes I am using Webpack as my bundler I use Webpack because it is so powerful, and even though it has a steep learning curve once you get it, its amazing.
The next thing I do is make sure my machine has Node.js configured and the right version installed then run Yarn. I decided to use Yarn because when I was building out this project npm had some shortcomings such as no .lock
file. I could probably move from Yarn to npm but I don't really see any point really.
I use Babel to transpile all of my #ES6 to #ES5 so the browser can read it, I love Babel and to be honest haven't looked up any other transpilers because Babel is amazing.
Finally when developing I have Prettier setup to make sure all my code is clean and uniform across all my JS files, and ESLint to make sure I catch any errors or code that could be optimized.
I'm really happy with this stack for my local env setup, and I'll probably stick with it for a while.