What is GitLab and what are its top alternatives?
Top Alternatives to GitLab
- 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. ...
- Bitbucket
Bitbucket gives teams one place to plan projects, collaborate on code, test and deploy, all with free private Git repositories. Teams choose Bitbucket because it has a superior Jira integration, built-in CI/CD, & is free for up to 5 users. ...
- 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. ...
- Gogs
The goal of this project is to make the easiest, fastest and most painless way to set up a self-hosted Git service. With Go, this can be done in independent binary distribution across ALL platforms that Go supports, including Linux, Mac OS X, and Windows. ...
- 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. ...
- Azure DevOps
Azure DevOps provides unlimited private Git hosting, cloud build for continuous integration, agile planning, and release management for continuous delivery to the cloud and on-premises. Includes broad IDE support. ...
- Bamboo
Focus on coding and count on Bamboo as your CI and build server! Create multi-stage build plans, set up triggers to start builds upon commits, and assign agents to your critical builds and deployments. ...
- GitLab CI
GitLab offers a continuous integration service. If you add a .gitlab-ci.yml file to the root directory of your repository, and configure your GitLab project to use a Runner, then each merge request or push triggers your CI pipeline. ...
GitLab alternatives & related posts
GitHub
- Open source friendly1.8K
- Easy source control1.5K
- Nice UI1.3K
- Great for team collaboration1.1K
- Easy setup867
- Issue tracker504
- Great community486
- Remote team collaboration483
- Great way to share451
- Pull request and features planning442
- Just works147
- Integrated in many tools132
- Free Public Repos121
- Github Gists116
- Github pages112
- Easy to find repos83
- Open source62
- It's free60
- Easy to find projects60
- Network effect56
- Extensive API49
- Organizations43
- Branching42
- Developer Profiles34
- Git Powered Wikis32
- Great for collaboration30
- It's fun24
- Clean interface and good integrations23
- Community SDK involvement22
- Learn from others source code20
- Because: Git16
- It integrates directly with Azure14
- Standard in Open Source collab10
- Newsfeed10
- It integrates directly with Hipchat8
- Fast8
- Beautiful user experience8
- Easy to discover new code libraries7
- Smooth integration6
- Cloud SCM6
- Nice API6
- Graphs6
- Integrations6
- It's awesome6
- Quick Onboarding5
- Reliable5
- Remarkable uptime5
- CI Integration5
- Hands down best online Git service available5
- Uses GIT4
- Version Control4
- Simple but powerful4
- Unlimited Public Repos at no cost4
- Free HTML hosting4
- Security options4
- Loved by developers4
- Easy to use and collaborate with others4
- Ci3
- IAM3
- Nice to use3
- Easy deployment via SSH3
- Easy to use2
- Leads the copycats2
- All in one development service2
- Free private repos2
- Free HTML hostings2
- Easy and efficient maintainance of the projects2
- Beautiful2
- Easy source control and everything is backed up2
- IAM integration2
- Very Easy to Use2
- Good tools support2
- Issues tracker2
- Never dethroned2
- Self Hosted2
- Dasf1
- Profound1
- Owned by micrcosoft54
- Expensive for lone developers that want private repos38
- Relatively slow product/feature release cadence15
- API scoping could be better10
- Only 3 collaborators for private repos9
- Limited featureset for issue management4
- Does not have a graph for showing history like git lens3
- GitHub Packages does not support SNAPSHOT versions2
- No multilingual interface1
- Takes a long time to commit1
- Expensive1
related GitHub posts
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.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
Bitbucket
- Free private repos904
- Simple setup397
- Nice ui and tools348
- Unlimited private repositories341
- Affordable git hosting240
- Integrates with many apis and services123
- Reliable uptime119
- Nice gui87
- Pull requests and code reviews85
- Very customisable58
- Mercurial repositories16
- SourceTree integration14
- JIRA integration12
- Track every commit to an issue in JIRA10
- Deployment hooks8
- Best free alternative to Github8
- Automatically share repositories with all your teammates7
- Compatible with Mac and Windows7
- Source Code Insight6
- Price6
- Login with Google5
- Create a wiki5
- Approve pull request button5
- Customizable pipelines4
- #2 Atlassian Product after JIRA4
- Also supports Mercurial3
- Unlimited Private Repos at no cost3
- Continuous Integration and Delivery3
- Academic license program2
- Multilingual interface2
- Teamcity2
- Open source friendly2
- Issues tracker2
- IAM2
- IAM integration2
- Mercurial Support2
- Not much community activity19
- Difficult to review prs because of confusing ui17
- Quite buggy15
- Managed by enterprise Java company10
- CI tool is not free of charge8
- Complexity with rights management7
- Only 5 collaborators for private repos6
- Slow performance4
- No AWS Codepipelines integration2
- No more Mercurial repositories1
- No server side git-hook support1
related Bitbucket posts
I use GitLab when building side-projects and MVPs. The interface and interactions are close enough to those of GitHub to prevent cognitive switching costs between professional and personal projects hosted on different services.
GitLab also provides a suite of tools including issue/project management, CI/CD with GitLab CI, and validation/landing pages with GitLab Pages. With everything in one place, on an #OpenSourceCloud GitLab makes it easy for me to manage much larger projects on my own, than would be possible with other solutions or tools.
It's petty I know, but I can also read the GitLab code diffs far more easily than diffs on GitHub or Bitbucket...they just look better in my opinion.
A bit difference in GitHub and GitLab though both are Version Control repository management services which provides key component in the software development workflow. A decision of choosing GitHub over GitLab is major leap extension from code management, to deployment and monitoring alongside looking beyond the code base hosting provided best fitted tools for developer communities.
- Authentication stages - With GitLab you can set and modify people’s permissions according to their role. In GitHub, you can decide if someone gets a read or write access to a repository.
- Built-In Continuous Integrations - GitLab offers its very own CI for free. No need to use an external CI service. And if you are already used to an external CI, you can obviously integrate with Jenkins, etc whereas GitHub offers various 3rd party integrations – such as Travis CI, CircleCI or Codeship – for running and testing your code. However, there’s no built-in CI solution at the moment.
- Import/Export Resources - GitLab offers detailed documentation on how to import your data from other vendors – such as GitHub, Bitbucket to GitLab. GitHub, on the other hand, does not offer such detailed documentation for the most common git repositories. However, GitHub offers to use GitHub Importer if you have your source code in Subversion, Mercurial, TFS and others.
Also when it comes to exporting data, GitLab seems to do a pretty solid job, offering you the ability to export your projects including the following data:
- Wiki and project repositories
- Project uploads
- The configuration including webhooks and services
- Issues with comments, merge requests with diffs and comments, labels, milestones, snippets, and other project entities.
GitHub, on the other hand, seems to be more restrictive when it comes to export features of existing GitHub repositories. * Integrations - #githubmarketplace gives you an essence to have multiple and competitive integrations whereas you will find less in the GitLab.
So go ahead with better understanding.
- Hosted internally523
- Free open source469
- Great to build, deploy or launch anything async318
- Tons of integrations243
- Rich set of plugins with good documentation211
- Has support for build pipelines111
- Easy setup68
- It is open-source66
- Workflow plugin53
- Configuration as code13
- Very powerful tool12
- Many Plugins11
- Continuous Integration10
- Great flexibility10
- Git and Maven integration is better9
- 100% free and open source8
- Github integration7
- Slack Integration (plugin)7
- Easy customisation6
- Self-hosted GitLab Integration (plugin)6
- Docker support5
- Pipeline API5
- Fast builds4
- Platform idnependency4
- Hosted Externally4
- Excellent docker integration4
- It`w worked3
- Customizable3
- Can be run as a Docker container3
- It's Everywhere3
- JOBDSL3
- AWS Integration3
- Easily extendable with seamless integration2
- PHP Support2
- Build PR Branch Only2
- NodeJS Support2
- Ruby/Rails Support2
- Universal controller2
- Loose Coupling2
- Workarounds needed for basic requirements13
- Groovy with cumbersome syntax10
- Plugins compatibility issues8
- Lack of support7
- Limited abilities with declarative pipelines7
- No YAML syntax5
- Too tied to plugins versions4
related Jenkins posts
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.
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
- Self-hosted github like service36
- Very low memory footprint31
- Easy to install / update29
- Lightweight (low minimal req.) runs on Raspberry pi17
- Single binary deploy no dependencies16
- Open source14
- Cross platform (MacOS, Windows, Linux ...)12
- Wiki11
- Issue tracker10
- Great UI3
- LDAP Support3
related Gogs posts
I installed Gogs after a few repos I planned to use on GitHub disappeared without explanation, and after Microsoft's acquisition of same, it made me think about the over-centralization of community-developed software. A self-hosted solution that enables easy point-and-click mirroring of important repositories for my projects, both in-house and 3rd-party, ensures I won't be bitten by upstream catastrophes. (So far, Microsoft's stewardship has been fine, but always be prepared). It's also a very nice way to host one's own private repos before they're ready for prime-time on github.
Gogs is written in Go and is easy to install and configure, IMHO much more so than GitLab, though it's of course less feature-rich; the only major feature I wish Gogs had is an integrated code review tool, but the web plugin hypothes.is https://stackshare.io/hypothes-is/hypothes-is is quite suitable as a code review tool. Set up a group for each code review, and just highlight lines to add comments in pull request pages of Gogs.
- Distributed version control system1.4K
- Efficient branching and merging1.1K
- Fast959
- Open source845
- Better than svn726
- Great command-line application368
- Simple306
- Free291
- Easy to use232
- Does not require server222
- Distributed27
- Small & Fast22
- Feature based workflow18
- Staging Area15
- Most wide-spread VSC13
- Role-based codelines11
- Disposable Experimentation11
- Frictionless Context Switching7
- Data Assurance6
- Efficient5
- Just awesome4
- Github integration3
- Easy branching and merging3
- Compatible2
- Flexible2
- Possible to lose history and commits2
- Rebase supported natively; reflog; access to plumbing1
- Light1
- Team Integration1
- Fast, scalable, distributed revision control system1
- Easy1
- Flexible, easy, Safe, and fast1
- CLI is great, but the GUI tools are awesome1
- It's what you do1
- Phinx0
- Hard to learn16
- Inconsistent command line interface11
- Easy to lose uncommitted work9
- Worst documentation ever possibly made7
- Awful merge handling5
- Unexistent preventive security flows3
- Rebase hell3
- When --force is disabled, cannot rebase2
- Ironically even die-hard supporters screw up badly2
- Doesn't scale for big data1
related Git posts
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.
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.
Azure DevOps
- Complete and powerful56
- Huge extension ecosystem32
- Azure integration27
- Flexible and powerful26
- One Stop Shop For Build server, Project Mgt, CDCI26
- Everything I need. Simple and intuitive UI15
- Support Open Source13
- Integrations8
- GitHub Integration7
- Cost free for Stakeholders6
- One 4 all6
- Crap6
- Project Mgmt Features6
- Runs in the cloud5
- Agent On-Premise(Linux - Windows)3
- Aws integration2
- Link Test Cases to Stories2
- Jenkins Integration2
- GCP Integration1
- Still dependant on C# for agents8
- Half Baked5
- Many in devops disregard MS altogether5
- Not a requirements management tool4
- Jack of all trades, master of none4
- Capacity across cross functional teams not visibile4
- Poor Jenkins integration3
- Tedious for test plan/case creation2
- Switching accounts is impossible1
related Azure DevOps posts
Visual Studio Azure DevOps Azure Functions Azure Websites #Azure #AzureKeyVault #AzureAD #AzureApps
#Azure Cloud Since Amazon is potentially our competitor then we need a different cloud vendor, also our programmers are microsoft oriented so the choose were obviously #Azure for us.
Azure DevOps Because we need to be able to develop a neww pipeline into Azure environment ina few minutes.
Azure Kubernetes Service We already in #Azure , also need to use K8s , so let's use AKS as it's a manged Kubernetes in the #Azure
I use Azure DevOps because for me it gradually walk me from private Git repositories to simplest free option for CI/CD pipelines at the time. I spend 0$ initially to manager CI/CD for my small private projects. No need to go into two different places to setup integration, once I have git repository, I could deploy projects. Right now this is not the case since CI/CD is default for me, so I use it now from memories of old good days. I'm not yet need complexity on the projects, so I don't even consider other options with "more choices". I carefully limit my set of options during development, that's why Azure DevOps (VSTS)
- Integrates with other Atlassian tools10
- Great notification scheme4
- Great UI2
- Has Deployment Projects1
- Expensive6
- Low community support1
- Bad UI1
- Bad integration with docker1
related Bamboo posts
We were using a hosted version of Redmine to track defects and user stories originally. We migrated to Jira.
Jira was an easy decision for a number of reasons:
- It's much more "Scrum ready" straight out of the box
- It's so much easier to keep a track of progress (I love the reporting)
- It natively encourages you to adhere to Scrum/Agile/Kanban practices
- Atlassian has a fantastic DevOps ecosystem when considering the likes of Confluence and Bamboo etc
- So many integrations!
- Its UI is so intuitive which makes it an absolute pleasure to use!
I know there are alot of other tools in this space but not even considering anything else at the moment. Love Jira!
I am choosing a DevOps toolset for my team. GitLab is open source and quite cloud-native. Jenkins has a very popular environment system but old-style technicals. Bamboo is very nice but integrated only with Atlassian products.
- Robust CI with awesome Docker support22
- Simple configuration13
- All in one solution9
- Source Control and CI in one place7
- Integrated with VCS on commit5
- Free and open source5
- Easy to configure own build server i.e. GitLab-Runner5
- Hosted internally2
- Built-in Docker Registry1
- Built-in support of Review Apps1
- Pipeline could be started manually1
- Enable or disable pipeline by using env variables1
- Gitlab templates could be shared across logical group1
- Easy to setup the dedicated runner to particular job1
- Built-in support of Kubernetes1
- Works best with GitLab repositories2
related GitLab CI posts
I have got a small radio service running on Node.js. Front end is written with React and packed with Webpack . I use Docker for my #DeploymentWorkflow along with Docker Swarm and GitLab CI on a single Google Compute Engine instance, which is also a runner itself. Pretty unscalable decision but it works great for tiny projects. The project is available on https://fridgefm.com
We use GitLab CI because of the great native integration as a part of the GitLab framework and the linting-capabilities it offers. The visualization of complex pipelines and the embedding within the project overview made Gitlab CI even more convenient. We use it for all projects, all deployments and as a part of GitLab Pages.
While we initially used the Shell-executor, we quickly switched to the Docker-executor and use it exclusively now.
We formerly used Jenkins but preferred to handle everything within GitLab . Aside from the unification of our infrastructure another motivation was the "configuration-in-file"-approach, that Gitlab CI offered, while Jenkins support of this concept was very limited and users had to resort to using the webinterface. Since the file is included within the repository, it is also version controlled, which was a huge plus for us.