Alternatives to Caddy logo

Alternatives to Caddy

NGINX, Traefik, HAProxy, Envoy, and JavaScript are the most popular alternatives and competitors to Caddy.
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What is Caddy and what are its top alternatives?

Caddy 2 is a powerful, enterprise-ready, open source web server with automatic HTTPS written in Go.
Caddy is a tool in the Web Servers category of a tech stack.
Caddy is an open source tool with 54.4K GitHub stars and 3.9K GitHub forks. Here’s a link to Caddy's open source repository on GitHub

Top Alternatives to Caddy

  • 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. ...

  • Traefik
    Traefik

    A modern HTTP reverse proxy and load balancer that makes deploying microservices easy. Traefik integrates with your existing infrastructure components and configures itself automatically and dynamically. ...

  • HAProxy
    HAProxy

    HAProxy (High Availability Proxy) is a free, very fast and reliable solution offering high availability, load balancing, and proxying for TCP and HTTP-based applications. ...

  • Envoy
    Envoy

    Originally built at Lyft, Envoy is a high performance C++ distributed proxy designed for single services and applications, as well as a communication bus and “universal data plane” designed for large microservice “service mesh” architectures. ...

  • 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. ...

Caddy alternatives & related posts

NGINX logo

NGINX

112.3K
60.1K
5.5K
A high performance free open source web server powering busiest sites on the Internet.
112.3K
60.1K
+ 1
5.5K
PROS OF NGINX
  • 1.4K
    High-performance http server
  • 893
    Performance
  • 730
    Easy to configure
  • 607
    Open source
  • 530
    Load balancer
  • 288
    Free
  • 288
    Scalability
  • 225
    Web server
  • 175
    Simplicity
  • 136
    Easy setup
  • 30
    Content caching
  • 21
    Web Accelerator
  • 15
    Capability
  • 14
    Fast
  • 12
    High-latency
  • 12
    Predictability
  • 8
    Reverse Proxy
  • 7
    The best of them
  • 7
    Supports http/2
  • 5
    Great Community
  • 5
    Lots of Modules
  • 5
    Enterprise version
  • 4
    High perfomance proxy server
  • 3
    Reversy Proxy
  • 3
    Streaming media delivery
  • 3
    Streaming media
  • 3
    Embedded Lua scripting
  • 2
    GRPC-Web
  • 2
    Blash
  • 2
    Lightweight
  • 2
    Fast and easy to set up
  • 2
    Slim
  • 2
    saltstack
  • 1
    Virtual hosting
  • 1
    Narrow focus. Easy to configure. Fast
  • 1
    Along with Redis Cache its the Most superior
  • 1
    Ingress controller
CONS OF NGINX
  • 10
    Advanced features require subscription

related NGINX posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.3M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
John-Daniel Trask
Co-founder & CEO at Raygun · | 19 upvotes · 257.1K views

We chose AWS because, at the time, it was really the only cloud provider to choose from.

We tend to use their basic building blocks (EC2, ELB, Amazon S3, Amazon RDS) rather than vendor specific components like databases and queuing. We deliberately decided to do this to ensure we could provide multi-cloud support or potentially move to another cloud provider if the offering was better for our customers.

We’ve utilized c3.large nodes for both the Node.js deployment and then for the .NET Core deployment. Both sit as backends behind an nginx instance and are managed using scaling groups in Amazon EC2 sitting behind a standard AWS Elastic Load Balancing (ELB).

While we’re satisfied with AWS, we do review our decision each year and have looked at Azure and Google Cloud offerings.

#CloudHosting #WebServers #CloudStorage #LoadBalancerReverseProxy

See more
Traefik logo

Traefik

829
1.2K
93
The Cloud Native Edge Router
829
1.2K
+ 1
93
PROS OF TRAEFIK
  • 20
    Kubernetes integration
  • 18
    Watch service discovery updates
  • 14
    Letsencrypt support
  • 13
    Swarm integration
  • 12
    Several backends
  • 6
    Ready-to-use dashboard
  • 4
    Easy setup
  • 4
    Rancher integration
  • 1
    Mesos integration
  • 1
    Mantl integration
CONS OF TRAEFIK
  • 7
    Not very performant (fast)
  • 7
    Complicated setup

related Traefik posts

Gabriel Pa
Shared insights
on
TraefikTraefikNGINXNGINX
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
Howie Zhao
Full Stack Engineer at yintrust · | 6 upvotes · 125K views
Shared insights
on
cookiecuttercookiecutterTraefikTraefik
at

We use Traefik as the web server.

The reasons for choosing Traefik over Nginx are as follows:

  • Traefik built-in Let’s Encrypt and supports automatic renewal
  • Traefik automatically enables HTTP/2
  • Prometheus can be supported through simple Traefik configuration
  • cookiecutter django integrates Traefik's configuration by default
See more
HAProxy logo

HAProxy

2.4K
2.1K
561
The Reliable, High Performance TCP/HTTP Load Balancer
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PROS OF HAPROXY
  • 131
    Load balancer
  • 102
    High performance
  • 69
    Very fast
  • 58
    Proxying for tcp and http
  • 55
    SSL termination
  • 31
    Open source
  • 27
    Reliable
  • 20
    Free
  • 18
    Well-Documented
  • 12
    Very popular
  • 7
    Runs health checks on backends
  • 7
    Suited for very high traffic web sites
  • 6
    Scalable
  • 5
    Ready to Docker
  • 4
    Powers many world's most visited sites
  • 3
    Simple
  • 2
    Ssl offloading
  • 2
    Work with NTLM
  • 1
    Available as a plugin for OPNsense
  • 1
    Redis
CONS OF HAPROXY
  • 6
    Becomes your single point of failure

related HAProxy posts

Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

See more
John Kodumal

Over the past year, we've shifted our philosophy on managed services and have moved several critical parts of our infrastructure away from self-managed options. The most prominent was our shift away from HAProxy to AWS's managed application load balancers (ALBs).

As we scaled, managing our HAProxy fleet became a larger and larger burden. We spent a significant amount of time tuning our configuration files and benchmarking different Amazon EC2 instance types to maximize throughput.

Emerging needs like #DDoS protection and auto scaling turned into large projects that we needed to schedule urgently. Instead of continuing this investment, we chose to shift to managed ALB instances. This was a large project, but it quickly paid for itself as we've nearly eliminated the time spent managing load balancers. We also gained DDoS protection and auto scaling "for free".

See more
Envoy logo

Envoy

292
539
9
C++ front/service proxy
292
539
+ 1
9
PROS OF ENVOY
  • 9
    GRPC-Web
CONS OF ENVOY
    Be the first to leave a con

    related Envoy posts

    Noah Zoschke
    Engineering Manager at Segment · | 30 upvotes · 269.9K views

    We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. Behind the scenes the Config API is built with Go , GRPC and Envoy.

    At Segment, we build new services in Go by default. The language is simple so new team members quickly ramp up on a codebase. The tool chain is fast so developers get immediate feedback when they break code, tests or integrations with other systems. The runtime is fast so it performs great at scale.

    For the newest round of APIs we adopted the GRPC service #framework.

    The Protocol Buffer service definition language makes it easy to design type-safe and consistent APIs, thanks to ecosystem tools like the Google API Design Guide for API standards, uber/prototool for formatting and linting .protos and lyft/protoc-gen-validate for defining field validations, and grpc-gateway for defining REST mapping.

    With a well designed .proto, its easy to generate a Go server interface and a TypeScript client, providing type-safe RPC between languages.

    For the API gateway and RPC we adopted the Envoy service proxy.

    The internet-facing segmentapis.com endpoint is an Envoy front proxy that rate-limits and authenticates every request. It then transcodes a #REST / #JSON request to an upstream GRPC request. The upstream GRPC servers are running an Envoy sidecar configured for Datadog stats.

    The result is API #security , #reliability and consistent #observability through Envoy configuration, not code.

    We experimented with Swagger service definitions, but the spec is sprawling and the generated clients and server stubs leave a lot to be desired. GRPC and .proto and the Go implementation feels better designed and implemented. Thanks to the GRPC tooling and ecosystem you can generate Swagger from .protos, but it’s effectively impossible to go the other way.

    See more
    Joseph Irving
    DevOps Engineer at uSwitch · | 7 upvotes · 536.2K views
    Shared insights
    on
    KubernetesKubernetesEnvoyEnvoyGolangGolang
    at

    At uSwitch we wanted a way to load balance between our multiple Kubernetes clusters in AWS to give us added redundancy. We already had ingresses defined for all our applications so we wanted to build on top of that, instead of creating a new system that would require our various teams to change code/config etc.

    Envoy seemed to tick a lot of boxes:

    • Loadbalancing capabilities right out of the box: health checks, circuit breaking, retries etc.
    • Tracing and prometheus metrics support
    • Lightweight
    • Good community support

    This was all good but what really sold us was the api that supported dynamic configuration. This would allow us to dynamically configure envoy to route to ingresses and clusters as they were created or destroyed.

    To do this we built a tool called Yggdrasil using their Go sdk. Yggdrasil effectively just creates envoy configuration from Kubernetes ingress objects, so you point Yggdrasil at your kube clusters, it generates config from the ingresses and then envoy can loadbalance between your clusters for you. This is all done dynamically so as soon as new ingress is created the envoy nodes get updated with the new config. Importantly this all worked with what we already had, no need to create new config for every application, we just put this on top of it.

    See more
    JavaScript logo

    JavaScript

    351.3K
    267.5K
    8.1K
    Lightweight, interpreted, object-oriented language with first-class functions
    351.3K
    267.5K
    + 1
    8.1K
    PROS OF JAVASCRIPT
    • 1.7K
      Can be used on frontend/backend
    • 1.5K
      It's everywhere
    • 1.2K
      Lots of great frameworks
    • 897
      Fast
    • 745
      Light weight
    • 425
      Flexible
    • 392
      You can't get a device today that doesn't run js
    • 286
      Non-blocking i/o
    • 237
      Ubiquitousness
    • 191
      Expressive
    • 55
      Extended functionality to web pages
    • 49
      Relatively easy language
    • 46
      Executed on the client side
    • 30
      Relatively fast to the end user
    • 25
      Pure Javascript
    • 21
      Functional programming
    • 15
      Async
    • 13
      Full-stack
    • 12
      Setup is easy
    • 12
      Future Language of The Web
    • 12
      Its everywhere
    • 11
      Because I love functions
    • 11
      JavaScript is the New PHP
    • 10
      Like it or not, JS is part of the web standard
    • 9
      Expansive community
    • 9
      Everyone use it
    • 9
      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
    • 8
      For the good parts
    • 8
      No need to use PHP
    • 8
      Easy to hire developers
    • 7
      Agile, packages simple to use
    • 7
      Love-hate relationship
    • 7
      Photoshop has 3 JS runtimes built in
    • 7
      Evolution of C
    • 7
      It's fun
    • 7
      Hard not to use
    • 7
      Versitile
    • 7
      Its fun and fast
    • 7
      Nice
    • 7
      Popularized Class-Less Architecture & Lambdas
    • 7
      Supports lambdas and closures
    • 6
      It let's me use Babel & Typescript
    • 6
      Can be used on frontend/backend/Mobile/create PRO Ui
    • 6
      1.6K Can be used on frontend/backend
    • 6
      Client side JS uses the visitors CPU to save Server Res
    • 6
      Easy to make something
    • 5
      Clojurescript
    • 5
      Promise relationship
    • 5
      Stockholm Syndrome
    • 5
      Function expressions are useful for callbacks
    • 5
      Scope manipulation
    • 5
      Everywhere
    • 5
      Client processing
    • 5
      What to add
    • 4
      Because it is so simple and lightweight
    • 4
      Only Programming language on browser
    • 1
      Test
    • 1
      Hard to learn
    • 1
      Test2
    • 1
      Not the best
    • 1
      Easy to understand
    • 1
      Subskill #4
    • 1
      Easy to learn
    • 0
      Hard 彤
    CONS OF JAVASCRIPT
    • 22
      A constant moving target, too much churn
    • 20
      Horribly inconsistent
    • 15
      Javascript is the New PHP
    • 9
      No ability to monitor memory utilitization
    • 8
      Shows Zero output in case of ANY error
    • 7
      Thinks strange results are better than errors
    • 6
      Can be ugly
    • 3
      No GitHub
    • 2
      Slow

    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.

    See more
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M 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
    Git logo

    Git

    290.2K
    174.4K
    6.6K
    Fast, scalable, distributed revision control system
    290.2K
    174.4K
    + 1
    6.6K
    PROS OF GIT
    • 1.4K
      Distributed version control system
    • 1.1K
      Efficient branching and merging
    • 959
      Fast
    • 845
      Open source
    • 726
      Better than svn
    • 368
      Great command-line application
    • 306
      Simple
    • 291
      Free
    • 232
      Easy to use
    • 222
      Does not require server
    • 27
      Distributed
    • 22
      Small & Fast
    • 18
      Feature based workflow
    • 15
      Staging Area
    • 13
      Most wide-spread VSC
    • 11
      Role-based codelines
    • 11
      Disposable Experimentation
    • 7
      Frictionless Context Switching
    • 6
      Data Assurance
    • 5
      Efficient
    • 4
      Just awesome
    • 3
      Github integration
    • 3
      Easy branching and merging
    • 2
      Compatible
    • 2
      Flexible
    • 2
      Possible to lose history and commits
    • 1
      Rebase supported natively; reflog; access to plumbing
    • 1
      Light
    • 1
      Team Integration
    • 1
      Fast, scalable, distributed revision control system
    • 1
      Easy
    • 1
      Flexible, easy, Safe, and fast
    • 1
      CLI is great, but the GUI tools are awesome
    • 1
      It's what you do
    • 0
      Phinx
    CONS OF GIT
    • 16
      Hard to learn
    • 11
      Inconsistent command line interface
    • 9
      Easy to lose uncommitted work
    • 7
      Worst documentation ever possibly made
    • 5
      Awful merge handling
    • 3
      Unexistent preventive security flows
    • 3
      Rebase hell
    • 2
      When --force is disabled, cannot rebase
    • 2
      Ironically even die-hard supporters screw up badly
    • 1
      Doesn't scale for big data

    related Git posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.3M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more
    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 8.3M views

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

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

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

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

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

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

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

    See more
    GitHub logo

    GitHub

    279.8K
    244.1K
    10.3K
    Powerful collaboration, review, and code management for open source and private development projects
    279.8K
    244.1K
    + 1
    10.3K
    PROS OF GITHUB
    • 1.8K
      Open source friendly
    • 1.5K
      Easy source control
    • 1.3K
      Nice UI
    • 1.1K
      Great for team collaboration
    • 867
      Easy setup
    • 504
      Issue tracker
    • 486
      Great community
    • 482
      Remote team collaboration
    • 451
      Great way to share
    • 442
      Pull request and features planning
    • 147
      Just works
    • 132
      Integrated in many tools
    • 121
      Free Public Repos
    • 116
      Github Gists
    • 112
      Github pages
    • 83
      Easy to find repos
    • 62
      Open source
    • 60
      It's free
    • 60
      Easy to find projects
    • 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
      It integrates directly with Hipchat
    • 8
      Fast
    • 8
      Beautiful user experience
    • 7
      Easy to discover new code libraries
    • 6
      Smooth integration
    • 6
      Cloud SCM
    • 6
      Nice API
    • 6
      Graphs
    • 6
      Integrations
    • 6
      It's awesome
    • 5
      Quick Onboarding
    • 5
      Reliable
    • 5
      Remarkable uptime
    • 5
      CI Integration
    • 5
      Hands down best online Git service available
    • 4
      Uses GIT
    • 4
      Version Control
    • 4
      Simple but powerful
    • 4
      Unlimited Public Repos at no cost
    • 4
      Free HTML hosting
    • 4
      Security options
    • 4
      Loved by developers
    • 4
      Easy to use and collaborate with others
    • 3
      Ci
    • 3
      IAM
    • 3
      Nice to use
    • 3
      Easy deployment via SSH
    • 2
      Easy to use
    • 2
      Leads the copycats
    • 2
      All in one development service
    • 2
      Free private repos
    • 2
      Free HTML hostings
    • 2
      Easy and efficient maintainance of the projects
    • 2
      Beautiful
    • 2
      Easy source control and everything is backed up
    • 2
      IAM integration
    • 2
      Very Easy to Use
    • 2
      Good tools support
    • 2
      Issues tracker
    • 2
      Never dethroned
    • 2
      Self Hosted
    • 1
      Dasf
    • 1
      Profound
    CONS OF GITHUB
    • 53
      Owned by micrcosoft
    • 37
      Expensive for lone developers that want private repos
    • 15
      Relatively slow product/feature release cadence
    • 10
      API scoping could be better
    • 8
      Only 3 collaborators for private repos
    • 3
      Limited featureset for issue management
    • 2
      GitHub Packages does not support SNAPSHOT versions
    • 2
      Does not have a graph for showing history like git lens
    • 1
      No multilingual interface
    • 1
      Takes a long time to commit
    • 1
      Expensive

    related GitHub posts

    Johnny Bell

    I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

    I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

    I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

    Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

    Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

    With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

    If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

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    Russel Werner
    Lead Engineer at StackShare · | 32 upvotes · 2.2M views

    StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

    Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

    #StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

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    Python logo

    Python

    239.8K
    195.7K
    6.9K
    A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
    239.8K
    195.7K
    + 1
    6.9K
    PROS OF PYTHON
    • 1.2K
      Great libraries
    • 961
      Readable code
    • 846
      Beautiful code
    • 787
      Rapid development
    • 689
      Large community
    • 435
      Open source
    • 393
      Elegant
    • 282
      Great community
    • 272
      Object oriented
    • 220
      Dynamic typing
    • 77
      Great standard library
    • 59
      Very fast
    • 55
      Functional programming
    • 49
      Easy to learn
    • 45
      Scientific computing
    • 35
      Great documentation
    • 29
      Productivity
    • 28
      Easy to read
    • 28
      Matlab alternative
    • 23
      Simple is better than complex
    • 20
      It's the way I think
    • 19
      Imperative
    • 18
      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
    • 6
      Although practicality beats purity
    • 6
      Flat is better than nested
    • 6
      Great for tooling
    • 6
      Rapid Prototyping
    • 6
      Readability counts
    • 6
      High Documented language
    • 6
      I love snakes
    • 6
      Fast coding and good for competitions
    • 6
      There should be one-- and preferably only one --obvious
    • 6
      Now is better than never
    • 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
      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
      It is Very easy , simple and will you be love programmi
    • 3
      Many types of collections
    • 3
      If the implementation is easy to explain, it may be a g
    • 2
      Batteries included
    • 2
      Should START with this but not STICK with This
    • 2
      Powerful language for AI
    • 2
      Can understand easily who are new to programming
    • 2
      Flexible and easy
    • 2
      Good for hacking
    • 2
      A-to-Z
    • 2
      Because of Netflix
    • 2
      Only one way to do it
    • 2
      Better outcome
    • 1
      Sexy af
    • 1
      Slow
    • 1
      Securit
    • 0
      Ni
    • 0
      Powerful
    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 · 10.1M 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

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    Nick Parsons
    Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 3.5M 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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