Alternatives to Deployer logo

Alternatives to Deployer

Octopus Deploy, Capistrano, Jenkins, Ansible, and phing are the most popular alternatives and competitors to Deployer.
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What is Deployer and what are its top alternatives?

A deployment tool written in PHP with support for popular frameworks out of the box
Deployer is a tool in the Continuous Deployment category of a tech stack.
Deployer is an open source tool with 9.4K GitHub stars and 1.4K GitHub forks. Here’s a link to Deployer's open source repository on GitHub

Top Alternatives to Deployer

  • Octopus Deploy
    Octopus Deploy

    Octopus Deploy helps teams to manage releases, automate deployments, and operate applications with automated runbooks. It's free for small teams. ...

  • Capistrano
    Capistrano

    Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows. ...

  • Jenkins
    Jenkins

    In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project. ...

  • Ansible
    Ansible

    Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use. ...

  • phing
    phing

    It is not GNU make; it's a PHP project build system or build tool based on Apache Ant. You can do anything with it that you could do with a traditional build system like GNU make, and its use of simple XML build files and extensible PHP 'task' classes make it an easy-to-use and highly flexible build framework. ...

  • Envoy
    Envoy

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

  • AWS CodePipeline
    AWS CodePipeline

    CodePipeline builds, tests, and deploys your code every time there is a code change, based on the release process models you define. ...

  • Google Cloud Build
    Google Cloud Build

    Cloud Build lets you build software quickly across all languages. Get complete control over defining custom workflows for building, testing, and deploying across multiple environments such as VMs, serverless, Kubernetes, or Firebase. ...

Deployer alternatives & related posts

Octopus Deploy logo

Octopus Deploy

387
431
114
A single place to release, deploy and operate your software
387
431
+ 1
114
PROS OF OCTOPUS DEPLOY
  • 30
    Powerful
  • 25
    Simplicity
  • 19
    Easy to learn
  • 15
    .Net oriented
  • 14
    Easy to manage releases and rollback
  • 7
    Allows multitenancy
  • 4
    Nice interface
CONS OF OCTOPUS DEPLOY
  • 4
    Poor UI
  • 2
    Config & variables not versioned (e.g. in git)
  • 2
    Management of Config

related Octopus Deploy posts

Oliver Burn

We recently added new APIs to Jira to associate information about Builds and Deployments to Jira issues.

The new APIs were developed using a spec-first API approach for speed and sanity. The details of this approach are described in this blog post, and we relied on using Swagger and associated tools like Swagger UI.

A new service was created for managing the data. It provides a REST API for external use, and an internal API based on GraphQL. The service is built using Kotlin for increased developer productivity and happiness, and the Spring-Boot framework. PostgreSQL was chosen for the persistence layer, as we have non-trivial requirements that cannot be easily implemented on top of a key-value store.

The front-end has been built using React and querying the back-end service using an internal GraphQL API. We have plans of providing a public GraphQL API in the future.

New Jira Integrations: Bitbucket CircleCI AWS CodePipeline Octopus Deploy jFrog Azure Pipelines

See more
Shared insights
on
Octopus DeployOctopus DeployJenkinsJenkins

What is the difference between Jenkins deployment and Octopus Deploy? Please suggest which is better?

See more
Capistrano logo

Capistrano

1.3K
620
234
A remote server automation and deployment tool written in Ruby
1.3K
620
+ 1
234
PROS OF CAPISTRANO
  • 123
    Automated deployment with several custom recipes
  • 63
    Simple
  • 23
    Ruby
  • 11
    Release-folders with symlinks
  • 9
    Multistage deployment
  • 2
    Cryptic syntax
  • 2
    Integrated rollback
  • 1
    Supports aws
CONS OF CAPISTRANO
    Be the first to leave a con

    related Capistrano posts

    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 2.5M views

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

    See more
    Kir Shatrov
    Engineering Lead at Shopify · | 13 upvotes · 132.1K views

    Shipit, our deployment tool, is at the heart of Continuous Delivery at Shopify. Shipit is an orchestrator that runs and tracks progress of any deploy script that you provide for a project. It supports deploying to Rubygems, Pip, Heroku and Capistrano out of the box. For us, it's mostly kubernetes-deploy or Capistrano for legacy projects.

    We use a slightly tweaked GitHub flow, with feature development going in branches and the master branch being the source of truth for the state of things in production. When your PR is ready, you add it to the Merge Queue in ShipIt. The idea behind the Merge Queue is to control the rate of code that is being merged to master branch. In the busy hours, we have many developers who want to merge the PRs, but at the same time we don't want to introduce too many changes to the system at the same time. Merge Queue limits deploys to 5-10 commits at a time, which makes it easier to identify issues and roll back in case we notice any unexpected behaviour after the deploy.

    We use a browser extension to make Merge Queue play nicely with the Merge button on GitHub:

    Both Shipit and kubernetes-deploy are open source, and we've heard quite a few success stories from companies who have adopted our flow.

    #BuildTestDeploy #ContainerTools #ApplicationHosting #PlatformAsAService

    See more
    Jenkins logo

    Jenkins

    49.6K
    41.8K
    2.2K
    An extendable open source continuous integration server
    49.6K
    41.8K
    + 1
    2.2K
    PROS OF JENKINS
    • 521
      Hosted internally
    • 464
      Free open source
    • 314
      Great to build, deploy or launch anything async
    • 243
      Tons of integrations
    • 210
      Rich set of plugins with good documentation
    • 110
      Has support for build pipelines
    • 72
      Open source and tons of integrations
    • 65
      Easy setup
    • 62
      It is open-source
    • 54
      Workflow plugin
    • 11
      Configuration as code
    • 10
      Very powerful tool
    • 9
      Continuous Integration
    • 9
      Many Plugins
    • 8
      Git and Maven integration is better
    • 8
      Great flexibility
    • 7
      100% free and open source
    • 6
      Slack Integration (plugin)
    • 6
      Github integration
    • 5
      Easy customisation
    • 5
      Self-hosted GitLab Integration (plugin)
    • 4
      Docker support
    • 4
      Pipeline API
    • 3
      Platform idnependency
    • 3
      Excellent docker integration
    • 3
      Fast builds
    • 3
      Hosted Externally
    • 2
      Customizable
    • 2
      AWS Integration
    • 2
      It's Everywhere
    • 2
      JOBDSL
    • 2
      Can be run as a Docker container
    • 2
      It`w worked
    • 1
      Easily extendable with seamless integration
    • 1
      Build PR Branch Only
    • 1
      NodeJS Support
    • 1
      PHP Support
    • 1
      Ruby/Rails Support
    • 1
      Universal controller
    • 1
      Loose Coupling
    CONS OF JENKINS
    • 12
      Workarounds needed for basic requirements
    • 9
      Groovy with cumbersome syntax
    • 7
      Plugins compatibility issues
    • 6
      Lack of support
    • 6
      Limited abilities with declarative pipelines
    • 4
      No YAML syntax
    • 3
      Too tied to plugins versions

    related Jenkins posts

    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 5.3M views

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

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

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

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

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

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

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

    See more
    Thierry Schellenbach

    Releasing new versions of our services is done by Travis CI. Travis first runs our test suite. Once it passes, it publishes a new release binary to GitHub.

    Common tasks such as installing dependencies for the Go project, or building a binary are automated using plain old Makefiles. (We know, crazy old school, right?) Our binaries are compressed using UPX.

    Travis has come a long way over the past years. I used to prefer Jenkins in some cases since it was easier to debug broken builds. With the addition of the aptly named “debug build” button, Travis is now the clear winner. It’s easy to use and free for open source, with no need to maintain anything.

    #ContinuousIntegration #CodeCollaborationVersionControl

    See more
    Ansible logo

    Ansible

    16.2K
    13.1K
    1.3K
    Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine
    16.2K
    13.1K
    + 1
    1.3K
    PROS OF ANSIBLE
    • 280
      Agentless
    • 207
      Great configuration
    • 196
      Simple
    • 174
      Powerful
    • 152
      Easy to learn
    • 67
      Flexible
    • 54
      Doesn't get in the way of getting s--- done
    • 34
      Makes sense
    • 30
      Super efficient and flexible
    • 27
      Powerful
    • 11
      Dynamic Inventory
    • 8
      Backed by Red Hat
    • 7
      Works with AWS
    • 6
      Cloud Oriented
    • 6
      Easy to maintain
    • 4
      Simple
    • 4
      Because SSH
    • 4
      Multi language
    • 4
      Easy
    • 4
      Procedural or declarative, or both
    • 4
      Simple and powerful
    • 3
      Vagrant provisioner
    • 3
      Consistency
    • 2
      Fast as hell
    • 2
      Merge hash to get final configuration similar to hiera
    • 2
      Debugging is simple
    • 2
      Masterless
    • 2
      Well-documented
    • 1
      Certified Content
    • 1
      Manage any OS
    • 1
      Work on windows, but difficult to manage
    CONS OF ANSIBLE
    • 8
      Dangerous
    • 5
      Hard to install
    • 3
      Doesn't Run on Windows
    • 3
      Bloated
    • 3
      Backward compatibility
    • 2
      No immutable infrastructure

    related Ansible posts

    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 5.3M views

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

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

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

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

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

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

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

    See more
    Sebastian Gębski

    Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

    See more
    phing logo

    phing

    21
    9
    0
    A PHP project build system or build tool based on ​Apache Ant
    21
    9
    + 1
    0
    PROS OF PHING
      Be the first to leave a pro
      CONS OF PHING
        Be the first to leave a con

        related phing posts

        Envoy logo

        Envoy

        265
        480
        8
        C++ front/service proxy
        265
        480
        + 1
        8
        PROS OF ENVOY
        • 8
          GRPC-Web
        CONS OF ENVOY
          Be the first to leave a con

          related Envoy posts

          Joseph Irving
          DevOps Engineer at uSwitch · | 7 upvotes · 176.6K views
          Shared insights
          on
          KubernetesKubernetesEnvoyEnvoyGolangGolang
          at

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

          Envoy seemed to tick a lot of boxes:

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

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

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

          See more
          Shared insights
          on
          EnvoyEnvoyHAProxyHAProxyTraefikTraefikNGINXNGINX

          We are looking to configure a load balancer with some admin UI. We are currently struggling to decide between NGINX, Traefik, HAProxy, and Envoy. We will use a load balancer in a containerized environment and the load balancer should flexible and easy to reload without changes in case containers are scaled up.

          See more
          AWS CodePipeline logo

          AWS CodePipeline

          516
          813
          30
          Continuous delivery service for fast and reliable application updates
          516
          813
          + 1
          30
          PROS OF AWS CODEPIPELINE
          • 13
            Simple to set up
          • 8
            Managed service
          • 4
            GitHub integration
          • 3
            Parallel Execution
          • 2
            Automatic deployment
          • 0
            Manual Steps Available
          CONS OF AWS CODEPIPELINE
          • 2
            No project boards
          • 1
            No integration with "Power" 365 tools

          related AWS CodePipeline posts

          Khauth György
          CTO at SalesAutopilot Kft. · | 12 upvotes · 480.4K views

          I'm the CTO of a marketing automation SaaS. Because of the continuously increasing load we moved to the AWSCloud. We are using more and more features of AWS: Amazon CloudWatch, Amazon SNS, Amazon CloudFront, Amazon Route 53 and so on.

          Our main Database is MySQL but for the hundreds of GB document data we use MongoDB more and more. We started to use Redis for cache and other time sensitive operations.

          On the front-end we use jQuery UI + Smarty but now we refactor our app to use Vue.js with Vuetify. Because our app is relatively complex we need to use vuex as well.

          On the development side we use GitHub as our main repo, Docker for local and server environment and Jenkins and AWS CodePipeline for Continuous Integration.

          See more
          Oliver Burn

          We recently added new APIs to Jira to associate information about Builds and Deployments to Jira issues.

          The new APIs were developed using a spec-first API approach for speed and sanity. The details of this approach are described in this blog post, and we relied on using Swagger and associated tools like Swagger UI.

          A new service was created for managing the data. It provides a REST API for external use, and an internal API based on GraphQL. The service is built using Kotlin for increased developer productivity and happiness, and the Spring-Boot framework. PostgreSQL was chosen for the persistence layer, as we have non-trivial requirements that cannot be easily implemented on top of a key-value store.

          The front-end has been built using React and querying the back-end service using an internal GraphQL API. We have plans of providing a public GraphQL API in the future.

          New Jira Integrations: Bitbucket CircleCI AWS CodePipeline Octopus Deploy jFrog Azure Pipelines

          See more
          Google Cloud Build logo

          Google Cloud Build

          515
          167
          2
          Continuously build, test, and deploy.
          515
          167
          + 1
          2
          PROS OF GOOGLE CLOUD BUILD
          • 1
            GCP easy integration
          • 1
            Container based
          CONS OF GOOGLE CLOUD BUILD
          • 2
            Vendor lock-in

          related Google Cloud Build posts

          Emanuel Evans
          Senior Architect at Rainforest QA · | 19 upvotes · 1M views

          We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

          We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

          Read the blog post to go more in depth.

          See more

          I use Google Cloud Build because it's my first foray into the CICD world(loving it so far), and I wanted to work with something GCP native to avoid giving permissions to other SaaS tools like CircleCI and Travis CI.

          I really like it because it's free for the first 120 minutes, and it's one of the few CICD tools that enterprises are open to using since it's contained within GCP.

          One of the unique things is that it has the Kaniko cache, which speeds up builds by creating intermediate layers within the docker image vs. pushing the full thing from the start. Helpful when you're installing just a few additional dependencies.

          Feel free to checkout an example: Cloudbuild Example

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