Alternatives to kaniko logo

Alternatives to kaniko

Docker, Jib, Makisu, Skaffold, and JavaScript are the most popular alternatives and competitors to kaniko.
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What is kaniko and what are its top alternatives?

Kaniko is a tool used for building container images from a Dockerfile, without needing to have Docker or root access on the host machine. It is designed to work in Kubernetes and other container orchestration platforms. Kaniko features includes support for caching layers, multi-stage builds, and the ability to run as a non-root user. However, limitations of Kaniko include slower build times compared to Docker and issues with certain Dockerfile instructions.

  1. Buildah: Buildah is a tool for building OCI (Open Container Initiative) and Docker images. Key features include support for rootless builds, concurrent building, and mounting container images as writable file systems. Pros include fast build times and native Kubernetes integration, while cons may include a learning curve for users unfamiliar with OCI standards.
  2. img: Img is a standalone, Docker-compatible CLI for building container images with various features like image layer squashing, multi-stage builds, and build caching. Pros include lightweight and fast builds, while cons might include limited community support.
  3. Docker Buildx: Docker Buildx is a CLI plugin for extended build capabilities with Docker. It offers features such as multi-platform builds, parallel builds, and advanced build caching. Pros include seamless integration with Docker CLI, while cons could include complexity for beginners.
  4. Podman: Podman is a tool for managing pods, containers, and container images without requiring daemon dependencies. Key features include rootless builds, Kubernetes compatibility, and support for running systemd in containers. Pros include compatibility with Docker commands, while cons may include compatibility issues with certain Docker features.
  5. Jib: Jib is a tool from Google for building Docker and OCI images for Java applications. It offers features like layer optimizations, incremental builds, and integration with Maven and Gradle. Pros include fast builds and simplified Java image creation, while cons could include limited language support compared to Kaniko.
  6. BuildKit: BuildKit is a portable builder tool for building container images with support for advanced features like parallel builds, cache management, and distributed builds. Pros include speed and efficiency, while cons may include a more complex setup compared to Kaniko.
  7. Kubernetes Docker Integrator (KDI): KDI is a Kubernetes-native builder that uses Kubernetes Job to build container images in a cluster. Key features include cluster-based build management, efficient caching, and support for multi-node builds. Pros include scalability and build isolation, while cons may include setup overhead.
  8. imgpkg: Imgpkg is a tool for packaging and distributing OCI images. It offers features like image versioning, content-based grouping, and support for installing images directly to a Kubernetes cluster. Pros include efficient image distribution, while cons could include limited build capabilities compared to Kaniko.
  9. Bazel: Bazel is a build and test tool that can be used for building container images along with other types of projects. It offers features like declarative build rules, caching, and cross-language build support. Pros include reproducible builds and support for various languages, while cons may include a steeper learning curve.
  10. imgbuild: Imgbuild is a tool from the creator of Kaniko that focuses on fast and efficient container image building. Key features include layer caching, parallel builds, and simplified image configuration. Pros include speed and simplicity, while cons may include limited community adoption.

Top Alternatives to kaniko

  • 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 ...

  • Jib
    Jib

    Jib builds Docker and OCI images for your Java applications and is available as plugins for Maven and Gradle. ...

  • Makisu
    Makisu

    Uber's core infrastructure team developed a pipeline that quickly and reliably generates Dockerfiles and builds application code into Docker images for Apache Mesos and Kubernetes-based container ecosystems. Giving back to the growing stack of microservice technologies, we open sourced its core component, Makisu, to enable other organizations to leverage the same benefits for their own architectures (more here: https://eng.uber.com/makisu/). ...

  • Skaffold
    Skaffold

    Skaffold is a command line tool that facilitates continuous development for Kubernetes applications. You can iterate on your application source code locally then deploy to local or remote Kubernetes clusters. Skaffold handles the workflow for building, pushing and deploying your application. It can also be used in an automated context such as a CI/CD pipeline to leverage the same workflow and tooling when moving applications to production. ...

  • 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. ...

kaniko alternatives & related posts

Docker logo

Docker

171.3K
137.7K
3.9K
Enterprise Container Platform for High-Velocity Innovation.
171.3K
137.7K
+ 1
3.9K
PROS OF DOCKER
  • 823
    Rapid integration and build up
  • 691
    Isolation
  • 521
    Open source
  • 505
    Testa­bil­i­ty and re­pro­ducibil­i­ty
  • 460
    Lightweight
  • 218
    Standardization
  • 185
    Scalable
  • 106
    Upgrading / down­grad­ing / ap­pli­ca­tion versions
  • 88
    Security
  • 85
    Private paas environments
  • 34
    Portability
  • 26
    Limit resource usage
  • 17
    Game changer
  • 16
    I love the way docker has changed virtualization
  • 14
    Fast
  • 12
    Concurrency
  • 8
    Docker's Compose tools
  • 6
    Easy setup
  • 6
    Fast and Portable
  • 5
    Because its fun
  • 4
    Makes shipping to production very simple
  • 3
    Highly useful
  • 3
    It's dope
  • 2
    Very easy to setup integrate and build
  • 2
    HIgh Throughput
  • 2
    Package the environment with the application
  • 2
    Does a nice job hogging memory
  • 2
    Open source and highly configurable
  • 2
    Simplicity, isolation, resource effective
  • 2
    MacOS support FAKE
  • 2
    Its cool
  • 2
    Docker hub for the FTW
  • 2
    Super
  • 0
    Asdfd
CONS OF DOCKER
  • 8
    New versions == broken features
  • 6
    Unreliable networking
  • 6
    Documentation not always in sync
  • 4
    Moves quickly
  • 3
    Not Secure

related Docker posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.7M 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.
See more
Tymoteusz Paul
Devops guy at X20X Development LTD · | 23 upvotes · 8.7M 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
Jib logo

Jib

18
43
2
Containerize your Java application (by Google)
18
43
+ 1
2
PROS OF JIB
  • 2
    No docker files to maintain
  • 0
    Build is faster than Docker
  • 0
    Native
  • 0
    Coder friendly with Maven and Gradle plugins
CONS OF JIB
    Be the first to leave a con

    related Jib posts

    Makisu logo

    Makisu

    7
    23
    0
    🍣 Fast and flexible Docker image building tool, works in unprivileged containerized environments like Mesos & Kubernetes (by...
    7
    23
    + 1
    0
    PROS OF MAKISU
      Be the first to leave a pro
      CONS OF MAKISU
        Be the first to leave a con

        related Makisu posts

        Skaffold logo

        Skaffold

        86
        185
        0
        Easy and Repeatable Kubernetes Development
        86
        185
        + 1
        0
        PROS OF SKAFFOLD
          Be the first to leave a pro
          CONS OF SKAFFOLD
            Be the first to leave a con

            related Skaffold posts

            JavaScript logo

            JavaScript

            352.4K
            268.2K
            8.1K
            Lightweight, interpreted, object-oriented language with first-class functions
            352.4K
            268.2K
            + 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 · 10.9M 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

            291.4K
            174.8K
            6.6K
            Fast, scalable, distributed revision control system
            291.4K
            174.8K
            + 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 · 9.7M 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.
            See more
            Tymoteusz Paul
            Devops guy at X20X Development LTD · | 23 upvotes · 8.7M 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

            280.6K
            244.8K
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            Powerful collaboration, review, and code management for open source and private development projects
            280.6K
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            + 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
            • 483
              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
            • 54
              Owned by micrcosoft
            • 38
              Expensive for lone developers that want private repos
            • 15
              Relatively slow product/feature release cadence
            • 10
              API scoping could be better
            • 9
              Only 3 collaborators for private repos
            • 4
              Limited featureset for issue management
            • 3
              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

            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 · 2.5M 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

            240.6K
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            A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
            240.6K
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            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 · 10.9M 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 · 3.9M 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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