Alternatives to OpenSSL logo

Alternatives to OpenSSL

OpenSSH, JavaScript, Git, GitHub, and Python are the most popular alternatives and competitors to OpenSSL.
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What is OpenSSL and what are its top alternatives?

OpenSSL is a widely used open-source toolkit implementing Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols. It provides cryptographic functions, SSL/TLS support, and various tools for managing certificates and keys. However, OpenSSL has faced security vulnerabilities and issues in the past, leading to concerns about its reliability and maintenance.

  1. LibreSSL: A fork of OpenSSL with a focus on code quality, security, and modernization. It aims to provide a more secure and maintained alternative to OpenSSL. Pros: Improved codebase, security enhancements. Cons: Limited community support.
  2. BoringSSL: Created by Google, BoringSSL is a fork of OpenSSL designed for internal use in their projects. It focuses on performance, usability, and security. Pros: Backed by Google, optimized for speed. Cons: Limited documentation.
  3. wolfSSL: A small, fast, and portable open-source TLS/SSL library with support for industry-standard security protocols. It emphasizes performance and memory usage optimization. Pros: Lightweight, commercial support available. Cons: Smaller community.
  4. GnuTLS: An open-source TLS library known for its flexibility and platform support. GnuTLS offers various features, including data encryption, X.509 certificate handling, and secure communication protocols. Pros: Extensive documentation, cross-platform compatibility. Cons: Not as widely adopted as OpenSSL.
  5. mbed TLS: Previously known as PolarSSL, mbed TLS is a lightweight cryptographic and SSL/TLS library designed for embedded systems and IoT devices. It provides secure communication for resource-constrained environments. Pros: Optimized for embedded devices, well-documented. Cons: Limited feature set compared to OpenSSL.
  6. NSS (Network Security Services): Developed by Mozilla, NSS is a set of libraries for building security-enabled applications. It supports various cryptographic algorithms, SSL/TLS protocols, and certificate management features. Pros: Strong integration with Mozilla products, active development. Cons: Complex setup process.
  7. mbedTLS: An open-source TLS library from Arm, mbedTLS offers a lightweight and portable solution for security protocols implementation. It is designed for embedded systems and IoT devices with a focus on performance and efficiency. Pros: Optimized for IoT, strong memory management. Cons: Limited feature set for complex applications.
  8. MatrixSSL: A lightweight, embeddable SSL/TLS stack suitable for resource-constrained environments. MatrixSSL is designed for performance and size optimization, making it ideal for embedded systems and IoT applications. Pros: Small footprint, high performance. Cons: Limited community support.
  9. Schannel: Microsoft's Security Support Provider Interface (SSPI) implementation of SSL/TLS protocols. Schannel is integrated into Windows operating systems and provides cryptographic services for secure communication. Pros: Seamless integration with Windows, frequently updated. Cons: Limited cross-platform compatibility.
  10. Botan: A C++ cryptography library offering support for various algorithms, protocols, and data formats. Botan aims to provide a secure and versatile toolkit for cryptographic operations in C++ applications. Pros: Extensive documentation, flexible design. Cons: Less popular compared to other alternatives.

Top Alternatives to OpenSSL

  • OpenSSH
    OpenSSH

    It is the premier connectivity tool for remote login with the SSH protocol. It encrypts all traffic to eliminate eavesdropping, connection hijacking, and other attacks. In addition, OpenSSH provides a large suite of secure tunneling capabilities, several authentication methods, and sophisticated configuration options. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • 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. ...

  • Python
    Python

    Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...

  • jQuery
    jQuery

    jQuery is a cross-platform JavaScript library designed to simplify the client-side scripting of HTML. ...

  • Node.js
    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. ...

  • 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. ...

OpenSSL alternatives & related posts

OpenSSH logo

OpenSSH

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Free suite of tools that help secure your network connections
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PROS OF OPENSSH
    Be the first to leave a pro
    CONS OF OPENSSH
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      related OpenSSH posts

      JavaScript logo

      JavaScript

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      PROS OF JAVASCRIPT
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        Lots of great frameworks
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        Fast
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        Light weight
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        Flexible
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        You can't get a device today that doesn't run js
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        Non-blocking i/o
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        Ubiquitousness
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        Expressive
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        Extended functionality to web pages
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        Relatively easy language
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        Executed on the client side
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        Relatively fast to the end user
      • 25
        Pure Javascript
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        Functional programming
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        Async
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        Full-stack
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        Setup is easy
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        Future Language of The Web
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        Its everywhere
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        Because I love functions
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        JavaScript is the New PHP
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        Like it or not, JS is part of the web standard
      • 9
        Expansive community
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        Everyone use it
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        Can be used in backend, frontend and DB
      • 9
        Easy
      • 8
        Most Popular Language in the World
      • 8
        Powerful
      • 8
        Can be used both as frontend and backend as well
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        For the good parts
      • 8
        No need to use PHP
      • 8
        Easy to hire developers
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        Agile, packages simple to use
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        Love-hate relationship
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        Photoshop has 3 JS runtimes built in
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        Evolution of C
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        It's fun
      • 7
        Hard not to use
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        Versitile
      • 7
        Its fun and fast
      • 7
        Nice
      • 7
        Popularized Class-Less Architecture & Lambdas
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        Supports lambdas and closures
      • 6
        It let's me use Babel & Typescript
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        Can be used on frontend/backend/Mobile/create PRO Ui
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        1.6K Can be used on frontend/backend
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        Client side JS uses the visitors CPU to save Server Res
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        Easy to make something
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        Clojurescript
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        Promise relationship
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        Stockholm Syndrome
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        Function expressions are useful for callbacks
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        Scope manipulation
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        Everywhere
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        Client processing
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        What to add
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        Because it is so simple and lightweight
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        Only Programming language on browser
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        Test
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        Hard to learn
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        Test2
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        Not the best
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        Easy to understand
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        Subskill #4
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        Easy to learn
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        Hard 彤
      CONS OF JAVASCRIPT
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        A constant moving target, too much churn
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        Horribly inconsistent
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        Javascript is the New PHP
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        No ability to monitor memory utilitization
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        Shows Zero output in case of ANY error
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        Thinks strange results are better than errors
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        Can be ugly
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        No GitHub
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        Slow
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        HORRIBLE DOCUMENTS, faulty code, repo has bugs

      related JavaScript posts

      Zach Holman

      Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

      But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

      But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

      Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

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      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 12.5M views

      How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

      Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

      Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

      https://eng.uber.com/distributed-tracing/

      (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

      Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

      See more
      Git logo

      Git

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        Better than svn
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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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        Frictionless Context Switching
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        Data Assurance
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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
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        It's what you do
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      CONS OF GIT
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        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
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        Unexistent preventive security flows
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        Rebase hell
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        Ironically even die-hard supporters screw up badly
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        When --force is disabled, cannot rebase
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        Doesn't scale for big data

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      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 10.7M 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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      Tymoteusz Paul
      Devops guy at X20X Development LTD · | 23 upvotes · 9.6M views

      Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

      It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

      I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

      We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

      If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

      The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

      Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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      GitHub logo

      GitHub

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      PROS OF GITHUB
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        Open source friendly
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        Easy source control
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        Nice UI
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        Great for team collaboration
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        Easy setup
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        Issue tracker
      • 487
        Great community
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        Remote team collaboration
      • 449
        Great way to share
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        Pull request and features planning
      • 147
        Just works
      • 132
        Integrated in many tools
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        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
      • 49
        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
      • 8
        Beautiful user experience
      • 8
        It integrates directly with Hipchat
      • 7
        Easy to discover new code libraries
      • 6
        Smooth integration
      • 6
        Integrations
      • 6
        Graphs
      • 6
        Nice API
      • 6
        It's awesome
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        Cloud SCM
      • 5
        Quick Onboarding
      • 5
        Remarkable uptime
      • 5
        CI Integration
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        Reliable
      • 5
        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
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        Free HTML hosting
      • 4
        Uses GIT
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        Security options
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        Easy to use and collaborate with others
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        Easy deployment via SSH
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        Ci
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        IAM
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        Nice to use
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        Easy and efficient maintainance of the projects
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        Beautiful
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        Self Hosted
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        Issues tracker
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        Easy source control and everything is backed up
      • 2
        Never dethroned
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        All in one development service
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        Good tools support
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        Free HTML hostings
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        IAM integration
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        Very Easy to Use
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        Easy to use
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        Leads the copycats
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        Free private repos
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        Profound
      • 1
        Dasf
      CONS OF GITHUB
      • 54
        Owned by micrcosoft
      • 38
        Expensive for lone developers that want private repos
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        Relatively slow product/feature release cadence
      • 10
        API scoping could be better
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        Only 3 collaborators for private repos
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        Limited featureset for issue management
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        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

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      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.

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

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

      Check Out My Architecture: CLICK ME

      Check out the GitHub repo attached

      See more
      Python logo

      Python

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        Object oriented
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      • 60
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      • 55
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      • 49
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      • 45
        Scientific computing
      • 35
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      • 29
        Productivity
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        Easy to read
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        Matlab alternative
      • 24
        Simple is better than complex
      • 20
        It's the way I think
      • 19
        Imperative
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        Free
      • 18
        Very programmer and non-programmer friendly
      • 17
        Powerfull language
      • 17
        Machine learning support
      • 16
        Fast and simple
      • 14
        Scripting
      • 12
        Explicit is better than implicit
      • 11
        Ease of development
      • 10
        Clear and easy and powerfull
      • 9
        Unlimited power
      • 8
        It's lean and fun to code
      • 8
        Import antigravity
      • 7
        Print "life is short, use python"
      • 7
        Python has great libraries for data processing
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        Although practicality beats purity
      • 6
        Now is better than never
      • 6
        Great for tooling
      • 6
        Readability counts
      • 6
        Rapid Prototyping
      • 6
        I love snakes
      • 6
        Flat is better than nested
      • 6
        Fast coding and good for competitions
      • 6
        There should be one-- and preferably only one --obvious
      • 6
        High Documented language
      • 5
        Great for analytics
      • 5
        Lists, tuples, dictionaries
      • 4
        Easy to learn and use
      • 4
        Simple and easy to learn
      • 4
        Easy to setup and run smooth
      • 4
        Web scraping
      • 4
        CG industry needs
      • 4
        Socially engaged community
      • 4
        Complex is better than complicated
      • 4
        Multiple Inheritence
      • 4
        Beautiful is better than ugly
      • 4
        Plotting
      • 3
        Many types of collections
      • 3
        Flexible and easy
      • 3
        It is Very easy , simple and will you be love programmi
      • 3
        If the implementation is hard to explain, it's a bad id
      • 3
        Special cases aren't special enough to break the rules
      • 3
        Pip install everything
      • 3
        List comprehensions
      • 3
        No cruft
      • 3
        Generators
      • 3
        Import this
      • 3
        If the implementation is easy to explain, it may be a g
      • 2
        Can understand easily who are new to programming
      • 2
        Batteries included
      • 2
        Securit
      • 2
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      • 2
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      • 2
        Only one way to do it
      • 2
        Because of Netflix
      • 2
        A-to-Z
      • 2
        Should START with this but not STICK with This
      • 2
        Powerful language for AI
      • 1
        Automation friendly
      • 1
        Sexy af
      • 1
        Slow
      • 1
        Procedural programming
      • 0
        Ni
      • 0
        Powerful
      • 0
        Keep it simple
      CONS OF PYTHON
      • 53
        Still divided between python 2 and python 3
      • 28
        Performance impact
      • 26
        Poor syntax for anonymous functions
      • 22
        GIL
      • 19
        Package management is a mess
      • 14
        Too imperative-oriented
      • 12
        Hard to understand
      • 12
        Dynamic typing
      • 12
        Very slow
      • 8
        Indentations matter a lot
      • 8
        Not everything is expression
      • 7
        Incredibly slow
      • 7
        Explicit self parameter in methods
      • 6
        Requires C functions for dynamic modules
      • 6
        Poor DSL capabilities
      • 6
        No anonymous functions
      • 5
        Fake object-oriented programming
      • 5
        Threading
      • 5
        The "lisp style" whitespaces
      • 5
        Official documentation is unclear.
      • 5
        Hard to obfuscate
      • 5
        Circular import
      • 4
        Lack of Syntax Sugar leads to "the pyramid of doom"
      • 4
        The benevolent-dictator-for-life quit
      • 4
        Not suitable for autocomplete
      • 2
        Meta classes
      • 1
        Training wheels (forced indentation)

      related Python posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 12.5M views

      How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

      Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

      Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

      https://eng.uber.com/distributed-tracing/

      (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

      Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

      See more
      Nick Parsons
      Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 4.3M views

      Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

      We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

      We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

      Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

      #FrameworksFullStack #Languages

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      jQuery logo

      jQuery

      191.5K
      67.9K
      6.6K
      The Write Less, Do More, JavaScript Library.
      191.5K
      67.9K
      + 1
      6.6K
      PROS OF JQUERY
      • 1.3K
        Cross-browser
      • 957
        Dom manipulation
      • 809
        Power
      • 660
        Open source
      • 610
        Plugins
      • 459
        Easy
      • 395
        Popular
      • 350
        Feature-rich
      • 281
        Html5
      • 227
        Light weight
      • 93
        Simple
      • 84
        Great community
      • 79
        CSS3 Compliant
      • 69
        Mobile friendly
      • 67
        Fast
      • 43
        Intuitive
      • 42
        Swiss Army knife for webdev
      • 35
        Huge Community
      • 11
        Easy to learn
      • 4
        Clean code
      • 3
        Because of Ajax request :)
      • 2
        Powerful
      • 2
        Nice
      • 2
        Just awesome
      • 2
        Used everywhere
      • 1
        Improves productivity
      • 1
        Javascript
      • 1
        Easy Setup
      • 1
        Open Source, Simple, Easy Setup
      • 1
        It Just Works
      • 1
        Industry acceptance
      • 1
        Allows great manipulation of HTML and CSS
      • 1
        Widely Used
      • 1
        I love jQuery
      CONS OF JQUERY
      • 6
        Large size
      • 5
        Sometimes inconsistent API
      • 5
        Encourages DOM as primary data source
      • 2
        Live events is overly complex feature

      related jQuery posts

      Kir Shatrov
      Engineering Lead at Shopify · | 22 upvotes · 2.4M views

      The client-side stack of Shopify Admin has been a long journey. It started with HTML templates, jQuery and Prototype. We moved to Batman.js, our in-house Single-Page-Application framework (SPA), in 2013. Then, we re-evaluated our approach and moved back to statically rendered HTML and vanilla JavaScript. As the front-end ecosystem matured, we felt that it was time to rethink our approach again. Last year, we started working on moving Shopify Admin to React and TypeScript.

      Many things have changed since the days of jQuery and Batman. JavaScript execution is much faster. We can easily render our apps on the server to do less work on the client, and the resources and tooling for developers are substantially better with React than we ever had with Batman.

      #FrameworksFullStack #Languages

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      Ganesa Vijayakumar
      Full Stack Coder | Technical Architect · | 19 upvotes · 5.3M views

      I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

      I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

      As per my work experience and knowledge, I have chosen the followings stacks to this mission.

      UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

      Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

      Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

      Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

      Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

      Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

      Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

      Happy Coding! Suggestions are welcome! :)

      Thanks, Ganesa

      See more
      Node.js logo

      Node.js

      187.7K
      159.4K
      8.5K
      A platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
      187.7K
      159.4K
      + 1
      8.5K
      PROS OF NODE.JS
      • 1.4K
        Npm
      • 1.3K
        Javascript
      • 1.1K
        Great libraries
      • 1K
        High-performance
      • 805
        Open source
      • 486
        Great for apis
      • 477
        Asynchronous
      • 423
        Great community
      • 390
        Great for realtime apps
      • 296
        Great for command line utilities
      • 84
        Websockets
      • 83
        Node Modules
      • 69
        Uber Simple
      • 59
        Great modularity
      • 58
        Allows us to reuse code in the frontend
      • 42
        Easy to start
      • 35
        Great for Data Streaming
      • 32
        Realtime
      • 28
        Awesome
      • 25
        Non blocking IO
      • 18
        Can be used as a proxy
      • 17
        High performance, open source, scalable
      • 16
        Non-blocking and modular
      • 15
        Easy and Fun
      • 14
        Easy and powerful
      • 13
        Future of BackEnd
      • 13
        Same lang as AngularJS
      • 12
        Fullstack
      • 11
        Fast
      • 10
        Scalability
      • 10
        Cross platform
      • 9
        Simple
      • 8
        Mean Stack
      • 7
        Great for webapps
      • 7
        Easy concurrency
      • 6
        Typescript
      • 6
        Fast, simple code and async
      • 6
        React
      • 6
        Friendly
      • 5
        Control everything
      • 5
        Its amazingly fast and scalable
      • 5
        Easy to use and fast and goes well with JSONdb's
      • 5
        Scalable
      • 5
        Great speed
      • 5
        Fast development
      • 4
        It's fast
      • 4
        Easy to use
      • 4
        Isomorphic coolness
      • 3
        Great community
      • 3
        Not Python
      • 3
        Sooper easy for the Backend connectivity
      • 3
        TypeScript Support
      • 3
        Blazing fast
      • 3
        Performant and fast prototyping
      • 3
        Easy to learn
      • 3
        Easy
      • 3
        Scales, fast, simple, great community, npm, express
      • 3
        One language, end-to-end
      • 3
        Less boilerplate code
      • 2
        Npm i ape-updating
      • 2
        Event Driven
      • 2
        Lovely
      • 1
        Creat for apis
      • 0
        Node
      CONS OF NODE.JS
      • 46
        Bound to a single CPU
      • 45
        New framework every day
      • 40
        Lots of terrible examples on the internet
      • 33
        Asynchronous programming is the worst
      • 24
        Callback
      • 19
        Javascript
      • 11
        Dependency hell
      • 11
        Dependency based on GitHub
      • 10
        Low computational power
      • 7
        Very very Slow
      • 7
        Can block whole server easily
      • 7
        Callback functions may not fire on expected sequence
      • 4
        Breaking updates
      • 4
        Unstable
      • 3
        Unneeded over complication
      • 3
        No standard approach
      • 1
        Bad transitive dependency management
      • 1
        Can't read server session

      related Node.js posts

      Shared insights
      on
      Node.jsNode.jsGraphQLGraphQLMongoDBMongoDB

      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:

      1. 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

      2. 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.

      3. 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

      See more
      Nick Rockwell
      SVP, Engineering at Fastly · | 46 upvotes · 3.9M views

      When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

      So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

      React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

      Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

      See more
      Visual Studio Code logo

      Visual Studio Code

      178.3K
      162.6K
      2.3K
      Build and debug modern web and cloud applications, by Microsoft
      178.3K
      162.6K
      + 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

      Vaibhav Taunk
      Team Lead at Technovert · | 31 upvotes · 4.2M views

      I am starting to become a full-stack developer, by choosing and learning .NET Core for API Development, Angular CLI / React for UI Development, MongoDB for database, as it a NoSQL DB and Flutter / React Native for Mobile App Development. Using Postman, Markdown and Visual Studio Code for development.

      See more
      Yshay Yaacobi

      Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

      Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

      After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

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