Alternatives to NGINX Unit logo

Alternatives to NGINX Unit

NGINX, Docker, uWSGI, Gunicorn, and PHP-FPM are the most popular alternatives and competitors to NGINX Unit.
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What is NGINX Unit and what are its top alternatives?

NGINX Unit is a dynamic web application server, designed to run applications in multiple languages. Unit is lightweight, polyglot, and dynamically configured via API. The design of the server allows reconfiguration of specific application parameters as needed by the engineering or operations.
NGINX Unit is a tool in the Web Servers category of a tech stack.
NGINX Unit is an open source tool with 2.4K GitHub stars and 208 GitHub forks. Here’s a link to NGINX Unit's open source repository on GitHub

Top Alternatives to NGINX Unit

  • NGINX

    NGINX

    nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...

  • Docker

    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere ...

  • uWSGI

    uWSGI

    The uWSGI project aims at developing a full stack for building hosting services. ...

  • Gunicorn

    Gunicorn

    Gunicorn is a pre-fork worker model ported from Ruby's Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resources, and fairly speedy. ...

  • PHP-FPM

    PHP-FPM

    It is an alternative PHP FastCGI implementation with some additional features useful for sites of any size, especially busier sites. It includes Adaptive process spawning, Advanced process management with graceful stop/start, Emergency restart in case of accidental opcode cache destruction etc. ...

  • Apache Tomcat

    Apache Tomcat

    Apache Tomcat powers numerous large-scale, mission-critical web applications across a diverse range of industries and organizations. ...

  • Puma

    Puma

    Unlike other Ruby Webservers, Puma was built for speed and parallelism. Puma is a small library that provides a very fast and concurrent HTTP 1.1 server for Ruby web applications. ...

  • Kubernetes

    Kubernetes

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...

NGINX Unit alternatives & related posts

NGINX logo

NGINX

92.6K
43K
5.5K
A high performance free open source web server powering busiest sites on the Internet.
92.6K
43K
+ 1
5.5K
PROS OF NGINX
  • 1.4K
    High-performance http server
  • 896
    Performance
  • 728
    Easy to configure
  • 606
    Open source
  • 529
    Load balancer
  • 286
    Scalability
  • 285
    Free
  • 222
    Web server
  • 173
    Simplicity
  • 134
    Easy setup
  • 29
    Content caching
  • 19
    Web Accelerator
  • 14
    Capability
  • 13
    Fast
  • 11
    Predictability
  • 10
    High-latency
  • 7
    Reverse Proxy
  • 6
    Fast and lightweight
  • 6
    Supports http/2
  • 4
    Enterprise version
  • 4
    Lots of Modules
  • 4
    The best of them
  • 4
    Great Community
  • 3
    Streaming media
  • 3
    Embedded Lua scripting
  • 3
    Reversy Proxy
  • 3
    High perfomance proxy server
  • 3
    Streaming media delivery
  • 2
    Slim
  • 2
    Lightweight
  • 2
    Fast and easy to set up
  • 2
    saltstack
  • 1
    Ingress controller
  • 1
    Virtual hosting
  • 1
    Narrow focus. Easy to configure. Fast
  • 1
    Along with Redis Cache its the Most superior
  • 1
    GRPC-Web
  • 0
    A
CONS OF NGINX
  • 8
    Advanced features require subscription

related NGINX posts

Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

See more
Gabriel Pa
Shared insights
on
Traefik
NGINX
at

We switched to Traefik so we can use the REST API to dynamically configure subdomains and have the ability to redirect between multiple servers.

We still use nginx with a docker-compose to expose the traffic from our APIs and TCP microservices, but for managing routing to the internet Traefik does a much better job

The biggest win for naologic was the ability to set dynamic configurations without having to restart the server

See more
Docker logo

Docker

111.4K
88.5K
3.8K
Enterprise Container Platform for High-Velocity Innovation.
111.4K
88.5K
+ 1
3.8K
PROS OF DOCKER
  • 821
    Rapid integration and build up
  • 688
    Isolation
  • 517
    Open source
  • 505
    Testa­bil­i­ty and re­pro­ducibil­i­ty
  • 459
    Lightweight
  • 217
    Standardization
  • 182
    Scalable
  • 105
    Upgrading / down­grad­ing / ap­pli­ca­tion versions
  • 86
    Security
  • 84
    Private paas environments
  • 33
    Portability
  • 25
    Limit resource usage
  • 15
    I love the way docker has changed virtualization
  • 15
    Game changer
  • 12
    Fast
  • 11
    Concurrency
  • 7
    Docker's Compose tools
  • 4
    Fast and Portable
  • 4
    Easy setup
  • 4
    Because its fun
  • 3
    Makes shipping to production very simple
  • 2
    It's dope
  • 1
    Highly useful
  • 1
    MacOS support FAKE
  • 1
    Its cool
  • 1
    Docker hub for the FTW
  • 1
    Very easy to setup integrate and build
  • 1
    Package the environment with the application
  • 1
    Does a nice job hogging memory
  • 1
    Open source and highly configurable
  • 1
    Simplicity, isolation, resource effective
CONS OF DOCKER
  • 7
    New versions == broken features
  • 5
    Documentation not always in sync
  • 5
    Unreliable networking
  • 3
    Moves quickly
  • 2
    Not Secure

related Docker posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.1M 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 · 4.5M 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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uWSGI logo

uWSGI

197
252
7
uWSGI application server container
197
252
+ 1
7
PROS OF UWSGI
  • 4
    Faster
  • 2
    Simple
  • 1
    Powerful
CONS OF UWSGI
    Be the first to leave a con

    related uWSGI posts

    I find I really like using GitHub because its issue tracker integrates really well into my project flow and the projects feature allows me to organize different efforts into boards. The automation features allow my issues to automatically progress through some states on the boards when I merge pull requests.

    My Python / Django app is deployed on Heroku with PostgreSQL database and uWSGI webserver.

    See more

    I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

    uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.

    See more
    Gunicorn logo

    Gunicorn

    853
    718
    76
    A Python WSGI HTTP Server for UNIX
    853
    718
    + 1
    76
    PROS OF GUNICORN
    • 34
      Python
    • 30
      Easy setup
    • 7
      Reliable
    • 3
      Fast
    • 2
      Light
    CONS OF GUNICORN
      Be the first to leave a con

      related Gunicorn posts

      Pierre Chapuis

      Unlike our frontend, we chose Flask, a microframework, for our backend. We use it with Python 3 and Gunicorn.

      One of the reasons was that I have significant experience with this framework. However, it also was a rather straightforward choice given that our backend almost only serves REST APIs, and that most of the work is talking to the database with SQLAlchemy .

      We could have gone with something like Hug but it is kind of early. We might revisit that decision for new services later on.

      See more

      I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

      uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.

      See more
      PHP-FPM logo

      PHP-FPM

      90
      88
      0
      An alternative FastCGI daemon for PHP
      90
      88
      + 1
      0
      PROS OF PHP-FPM
        Be the first to leave a pro
        CONS OF PHP-FPM
          Be the first to leave a con

          related PHP-FPM posts

          Apache Tomcat logo

          Apache Tomcat

          11.9K
          8.3K
          200
          An open source software implementation of the Java Servlet and JavaServer Pages technologies
          11.9K
          8.3K
          + 1
          200
          PROS OF APACHE TOMCAT
          • 79
            Easy
          • 72
            Java
          • 48
            Popular
          • 1
            Spring web
          CONS OF APACHE TOMCAT
            Be the first to leave a con

            related Apache Tomcat posts

            Остап Комплікевич

            I need some advice to choose an engine for generation web pages from the Spring Boot app. Which technology is the best solution today? 1) JSP + JSTL 2) Apache FreeMarker 3) Thymeleaf Or you can suggest even other perspective tools. I am using Spring Boot, Spring Web, Spring Data, Spring Security, PostgreSQL, Apache Tomcat in my project. I have already tried to generate pages using jsp, jstl, and it went well. However, I had huge problems via carrying already created static pages, to jsp format, because of syntax. Thanks.

            See more

            Java Spring JUnit

            Apache HTTP Server Apache Tomcat

            MySQL

            See more
            Puma logo

            Puma

            444
            226
            19
            A Modern, Concurrent Web Server for Ruby
            444
            226
            + 1
            19
            PROS OF PUMA
            • 3
              Convenient
            • 3
              Free
            • 3
              Easy
            • 2
              Multithreaded
            • 2
              Default Rails server
            • 2
              First-class support for WebSockets
            • 2
              Consumes less memory than Unicorn
            • 1
              Lightweight
            • 1
              Fast
            CONS OF PUMA
            • 0
              Uses `select` (limited client count)

            related Puma posts

            Jerome Dalbert
            Senior Backend Engineer at StackShare · | 6 upvotes · 158.6K views
            Shared insights
            on
            Unicorn
            Puma
            Rails
            at

            We switched from Unicorn (process model) to Puma (threaded model) to decrease the memory footprint of our Rails production web server. Memory indeed dropped from 6GB to only 1GB!

            We just had to decrease our worker count and increase our thread count instead. Performance (response time and throughput) remained the same, if not slightly better. We had no thread-safety errors, which was good.

            Free bonus points are:

            • Requests are blazing fast on our dev and staging environments!
            • Puma has first-class support for WebSockets, so we know for sure that Rails ActionCable or GraphQL subscriptions will work great.
            • Being on Puma makes us even more "default Rails"-compliant since it is the default Rails web server these days.
            See more
            Kubernetes logo

            Kubernetes

            37.6K
            31.8K
            622
            Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
            37.6K
            31.8K
            + 1
            622
            PROS OF KUBERNETES
            • 155
              Leading docker container management solution
            • 124
              Simple and powerful
            • 100
              Open source
            • 74
              Backed by google
            • 56
              The right abstractions
            • 24
              Scale services
            • 18
              Replication controller
            • 9
              Permission managment
            • 7
              Simple
            • 7
              Supports autoscaling
            • 6
              Cheap
            • 4
              Self-healing
            • 4
              Reliable
            • 4
              No cloud platform lock-in
            • 3
              Open, powerful, stable
            • 3
              Scalable
            • 3
              Quick cloud setup
            • 3
              Promotes modern/good infrascture practice
            • 2
              Backed by Red Hat
            • 2
              Runs on azure
            • 2
              Cloud Agnostic
            • 2
              Custom and extensibility
            • 2
              Captain of Container Ship
            • 2
              A self healing environment with rich metadata
            • 1
              Golang
            • 1
              Easy setup
            • 1
              Everything of CaaS
            • 1
              Sfg
            • 1
              Expandable
            • 1
              Gke
            CONS OF KUBERNETES
            • 13
              Poor workflow for development
            • 11
              Steep learning curve
            • 5
              Orchestrates only infrastructure
            • 2
              High resource requirements for on-prem clusters

            related Kubernetes posts

            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber · | 38 upvotes · 4.1M 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
            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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