What is QuickJS and what are its top alternatives?
QuickJS is a lightweight, embeddable JavaScript engine written by Fabrice Bellard, the creator of FFmpeg and QEMU. It aims to provide a small footprint without sacrificing performance, making it suitable for resource-constrained environments. QuickJS supports the full ECMAScript 2020 standard, includes a small and simple C API, and can easily be embedded in applications. However, the engine lacks certain features found in larger JavaScript engines and may not be as widely supported as other alternatives.
- V8: V8 is Google's open-source high-performance JavaScript and WebAssembly engine used in the Chrome browser. Key features include fast execution speed, support for modern JavaScript features, and a powerful optimizing compiler. Pros: excellent performance, extensive tooling support. Cons: can be memory-intensive.
- SpiderMonkey: SpiderMonkey is the JavaScript engine used in Mozilla Firefox. It supports many web standards and has strong compatibility with the JavaScript ecosystem. Pros: well-established, actively developed. Cons: might not be as fast as some other engines.
- JavaScriptCore: JavaScriptCore is the open-source JavaScript engine used in the Safari browser and WebKit project. It boasts high performance, a powerful optimizing compiler, and good compatibility with modern web standards. Pros: optimized for Apple platforms, actively maintained. Cons: limited cross-platform support.
- Espruino: Espruino is an open-source JavaScript interpreter designed for microcontrollers and embedded systems. It has a small memory footprint, offers good compatibility with existing JavaScript code, and supports a variety of hardware platforms. Pros: optimized for embedded systems, easy to use. Cons: may lack some of the features found in larger engines.
- Duktape: Duktape is a lightweight JavaScript engine for embedded systems with a focus on minimal footprint and ease of integration. It supports the ECMAScript 5.1 standard, includes a small C API, and can run on various platforms. Pros: small footprint, easy to embed. Cons: may not support all ECMAScript features.
- JerryScript: JerryScript is an ultra-lightweight JavaScript engine for the Internet of Things (IoT) devices. It is optimized for low memory usage, has a small code size, and supports a subset of the ECMAScript standard. Pros: designed for resource-constrained devices, efficient memory usage. Cons: limited feature set compared to full JavaScript engines.
- MuJS: MuJS is a lightweight ECMAScript 5.1-compatible JavaScript interpreter designed for embedding in applications. It has a small memory footprint, a simple C API, and is easy to integrate into projects. Pros: lightweight, fast startup time. Cons: limited features compared to more comprehensive engines.
- ChakraCore: ChakraCore is the open-source JavaScript engine used in Microsoft Edge. It offers high performance, support for modern JavaScript features, and can be used as a standalone interpreter or embedded in applications. Pros: actively maintained, good performance. Cons: limited cross-platform support.
- MuJS: MuJS is a lightweight ECMAScript 5.1-compatible JavaScript interpreter designed for embedding in applications. It has a small memory footprint, a simple C API, and is easy to integrate into projects. Pros: lightweight, fast startup time. Cons: limited features compared to more comprehensive engines.
- Hera: Hermes is an open-source JavaScript engine optimized for running React Native applications on mobile devices. It focuses on reducing memory usage and improving startup time, making it ideal for resource-constrained environments. Pros: optimized for mobile platforms, fast startup time. Cons: specialized for React Native applications.
Top Alternatives to QuickJS
- Lua
Lua combines simple procedural syntax with powerful data description constructs based on associative arrays and extensible semantics. Lua is dynamically typed, runs by interpreting bytecode for a register-based virtual machine, and has automatic memory management with incremental garbage collection, making it ideal for configuration, scripting, and rapid prototyping. ...
- Node.js
Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices. ...
- Hermes
It is a JavaScript engine optimized for fast start up of React Native apps on Android. It features ahead-of-time static optimization and compact bytecode. ...
- 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. ...
QuickJS alternatives & related posts
- Fast learning curve41
- Very easy to embed in C programs26
- Efficient memory usage26
- Open source20
- Good for game scripting19
- Pretty simple to learn9
- Quick to code8
- Simple Language8
- Syntax is amazing7
- Supported in most game engines7
- D6
- Coroutines2
- Can be used for a wide variety of development1
- Nooby4
- Not widespread2
- D1
- Python0
related Lua posts
I want to learn a coding language so that I can get a job right out of high school I'm currently 15 and a half. What should I learn and where, and where should I look for jobs with little to no experience in coding jobs? From what I've seen my top 4 coding languages to learn are C++, JavaScript, Python, and Lua.
For a Visual Studio Code/Atom developer that works mostly with Node.js/TypeScript/Ruby/Go and wants to get rid of graphic-text-editors-IDE-like at once, which one is worthy of investing time to pick up?
I'm a total n00b on the subject, but I've read good things about Neovim's Lua support, and I wonder what would be the VIM response/approach for it?
Node.js
- Npm1.4K
- Javascript1.3K
- Great libraries1.1K
- High-performance1K
- Open source805
- Great for apis487
- Asynchronous477
- Great community425
- Great for realtime apps390
- Great for command line utilities296
- Websockets86
- Node Modules84
- Uber Simple69
- Great modularity59
- Allows us to reuse code in the frontend58
- Easy to start42
- Great for Data Streaming35
- Realtime32
- Awesome28
- Non blocking IO25
- Can be used as a proxy18
- High performance, open source, scalable17
- Non-blocking and modular16
- Easy and Fun15
- Easy and powerful14
- Future of BackEnd13
- Same lang as AngularJS13
- Fullstack12
- Fast11
- Scalability10
- Cross platform10
- Simple9
- Mean Stack8
- Great for webapps7
- Easy concurrency7
- Typescript6
- Fast, simple code and async6
- React6
- Friendly6
- Control everything5
- Its amazingly fast and scalable5
- Easy to use and fast and goes well with JSONdb's5
- Scalable5
- Great speed5
- Fast development5
- It's fast4
- Easy to use4
- Isomorphic coolness4
- Great community3
- Not Python3
- Sooper easy for the Backend connectivity3
- TypeScript Support3
- Blazing fast3
- Performant and fast prototyping3
- Easy to learn3
- Easy3
- Scales, fast, simple, great community, npm, express3
- One language, end-to-end3
- Less boilerplate code3
- Npm i ape-updating2
- Event Driven2
- Lovely2
- Creat for apis1
- Node0
- Bound to a single CPU46
- New framework every day45
- Lots of terrible examples on the internet40
- Asynchronous programming is the worst33
- Callback24
- Javascript19
- Dependency hell11
- Dependency based on GitHub11
- Low computational power10
- Very very Slow7
- Can block whole server easily7
- Callback functions may not fire on expected sequence7
- Breaking updates4
- Unstable4
- Unneeded over complication3
- No standard approach3
- Bad transitive dependency management1
- Can't read server session1
related Node.js posts
I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery
For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:
Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have
GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.
MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website
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?
related Hermes posts
- 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
- Distributed28
- Small & Fast23
- Feature based workflow18
- Staging Area15
- Most wide-spread VSC13
- Disposable Experimentation11
- Role-based codelines11
- Frictionless Context Switching7
- Data Assurance6
- Efficient5
- Just awesome4
- Easy branching and merging3
- Github integration3
- Compatible2
- Possible to lose history and commits2
- Flexible2
- Team Integration1
- Easy1
- Light1
- Fast, scalable, distributed revision control system1
- Rebase supported natively; reflog; access to plumbing1
- 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 setup868
- 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
- It's awesome6
- Smooth integration6
- Cloud SCM6
- Nice API6
- Graphs6
- Integrations6
- Hands down best online Git service available5
- Reliable5
- Quick Onboarding5
- CI Integration5
- Remarkable uptime5
- Security options4
- Loved by developers4
- Uses GIT4
- Free HTML hosting4
- Easy to use and collaborate with others4
- Version Control4
- Simple but powerful4
- Unlimited Public Repos at no cost4
- Nice to use3
- IAM3
- Ci3
- Easy deployment via SSH3
- Free private repos2
- Good tools support2
- All in one development service2
- Never dethroned2
- Easy source control and everything is backed up2
- Issues tracker2
- Self Hosted2
- IAM integration2
- Very Easy to Use2
- Easy to use2
- Leads the copycats2
- Free HTML hostings2
- Easy and efficient maintainance of the projects2
- Beautiful2
- Dasf1
- Profound1
- 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
- Easy setup6
- Fast and Portable6
- Because its fun5
- Makes shipping to production very simple4
- Highly useful3
- It's dope3
- Package the environment with the application2
- Super2
- Open source and highly configurable2
- Simplicity, isolation, resource effective2
- MacOS support FAKE2
- Its cool2
- Does a nice job hogging memory2
- Docker hub for the FTW2
- HIgh Throughput2
- Very easy to setup integrate and build2
- 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.