Alternatives to KVM logo

Alternatives to KVM

VirtualBox, Qemu, OpenVZ, Xen, and Docker are the most popular alternatives and competitors to KVM.
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228
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What is KVM and what are its top alternatives?

KVM, or Kernel-based Virtual Machine, is an open-source virtualization technology that allows users to create and manage virtual machines on Linux systems. Key features of KVM include hardware virtualization support, live migration capabilities, and integration with popular cloud platforms like OpenStack. However, KVM does have some limitations such as requiring a deep understanding of Linux and system administration for optimal use.

  1. VMware vSphere: VMware vSphere is a leading virtualization platform that offers advanced features such as high availability, fault tolerance, and distributed resource scheduling. Pros of VMware vSphere include its user-friendly interface and wide range of supported guest operating systems, while cons include its high cost compared to KVM.
  2. Microsoft Hyper-V: Microsoft Hyper-V is a built-in hypervisor for Windows Server that provides features like failover clustering and network virtualization. Pros of Hyper-V include its seamless integration with Windows systems, but cons include its compatibility limitations with non-Windows operating systems when compared to KVM.
  3. Xen Project: Xen Project is an open-source hypervisor that powers numerous cloud hosting services. Key features of Xen Project include paravirtualization support, efficient resource management, and security isolation. Pros of Xen Project include its lightweight footprint and agile performance, but cons include its steeper learning curve compared to KVM.
  4. Oracle VM VirtualBox: Oracle VM VirtualBox is a free and open-source virtualization tool that enables users to run multiple operating systems on a single machine. Pros of VirtualBox include its intuitive interface and easy setup process, while cons include its limited scalability compared to KVM.
  5. Proxmox Virtual Environment: Proxmox Virtual Environment is an open-source virtualization platform that combines KVM and LXC containers for efficient resource utilization. Pros of Proxmox include its user-friendly web management interface and built-in backup capabilities, while cons include its reliance on a subscription model for certain features.
  6. OpenVZ: OpenVZ is a container-based virtualization solution that offers lightweight virtualization for Linux systems. Key features of OpenVZ include fast container deployment and efficient resource sharing. Pros of OpenVZ include its low overhead and fast performance, while cons include its lack of hardware virtualization support compared to KVM.
  7. QEMU: QEMU is an open-source emulator and virtualizer that supports a wide range of guest operating systems and hardware architectures. Pros of QEMU include its versatility and compatibility with various platforms, but cons include its slower performance compared to KVM due to its emulation-based approach.
  8. Citrix Hypervisor: Citrix Hypervisor, formerly XenServer, is an enterprise-class virtualization solution that offers features such as storage multipathing and high availability. Pros of Citrix Hypervisor include its robust security features and centralized management console, while cons include its higher cost compared to KVM.
  9. LXD: LXD is a container-based virtualization solution that focuses on system containers for improved performance and security. Key features of LXD include live migration support, image management, and network flexibility. Pros of LXD include its high density of containers per host and fast startup times, but cons include its limited support for legacy applications compared to KVM.
  10. oVirt: oVirt is an open-source virtualization platform that is based on KVM technology and offers features like virtual machine management and live migration. Pros of oVirt include its strong community support and comprehensive feature set, while cons include its complexity for smaller deployments compared to KVM.

Top Alternatives to KVM

  • VirtualBox
    VirtualBox

    VirtualBox is a powerful x86 and AMD64/Intel64 virtualization product for enterprise as well as home use. Not only is VirtualBox an extremely feature rich, high performance product for enterprise customers, it is also the only professional solution that is freely available as Open Source Software under the terms of the GNU General Public License (GPL) version 2. ...

  • Qemu
    Qemu

    When used as a machine emulator, it can run OSes and programs made for one machine (e.g. an ARM board) on a different machine (e.g. your own PC). By using dynamic translation, it achieves very good performance. When used as a virtualizer, it achieves near native performance by executing the guest code directly on the host CPU. it supports virtualization when executing under the Xen hypervisor or using the KVM kernel module in Linux. When using KVM, it can virtualize x86, server and embedded PowerPC, 64-bit POWER, S390, 32-bit and 64-bit ARM, and MIPS guests. ...

  • OpenVZ
    OpenVZ

    Virtuozzo leverages OpenVZ as its core of a virtualization solution offered by Virtuozzo company. Virtuozzo is optimized for hosters and offers hypervisor (VMs in addition to containers), distributed cloud storage, dedicated support, management tools, and easy installation. ...

  • Xen
    Xen

    It is a hypervisor using a microkernel design, providing services that allow multiple computer operating systems to execute on the same computer hardware concurrently. It was developed by the Linux Foundation and is supported by Intel. ...

  • 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 ...

  • LXC
    LXC

    LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers. ...

  • 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. ...

KVM alternatives & related posts

VirtualBox logo

VirtualBox

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    Open-source
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    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M 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 · 8.9M 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
    Qemu logo

    Qemu

    96
    128
    3
    A generic and open source machine emulator and virtualizer
    96
    128
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    3
    PROS OF QEMU
    • 1
      Performance
    • 1
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    • 1
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    CONS OF QEMU
      Be the first to leave a con

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      OpenVZ logo

      OpenVZ

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          Xen logo

          Xen

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              Docker logo

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                Standardization
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                Private paas environments
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              • 26
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              • 17
                Game changer
              • 16
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              • 14
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              • 12
                Concurrency
              • 8
                Docker's Compose tools
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                Docker hub for the FTW
              • 2
                Super
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              • 8
                New versions == broken features
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              • 3
                Not Secure

              related Docker posts

              Simon Reymann
              Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M 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 · 8.9M 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
              LXC logo

              LXC

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              CONS OF LXC
                Be the first to leave a con

                related LXC posts

                Tymoteusz Paul
                Devops guy at X20X Development LTD · | 23 upvotes · 8.9M 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
                JavaScript logo

                JavaScript

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                  Non-blocking i/o
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                  Ubiquitousness
                • 191
                  Expressive
                • 55
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                • 49
                  Relatively easy language
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                  Executed on the client side
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                • 25
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                  Functional programming
                • 15
                  Async
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                  Full-stack
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                  Setup is easy
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                  Future Language of The Web
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                  Its everywhere
                • 11
                  Because I love functions
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                  JavaScript is the New PHP
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                  Like it or not, JS is part of the web standard
                • 9
                  Expansive community
                • 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
                • 0
                  HORRIBLE DOCUMENTS, faulty code, repo has bugs

                related JavaScript posts

                Zach Holman

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

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

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

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

                See more
                Conor Myhrvold
                Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 11.2M 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
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                  Easy branching and merging
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                  Compatible
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                related Git posts

                Simon Reymann
                Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

                Our whole DevOps stack consists of the following tools:

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

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

                • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
                • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
                • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
                • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
                • Scalability: All-in-one framework for distributed systems.
                • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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                Tymoteusz Paul
                Devops guy at X20X Development LTD · | 23 upvotes · 8.9M 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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