What is TeamCity and what are its top alternatives?
Top Alternatives to TeamCity
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. ...
Appveyor
AppVeyor aims to give powerful Continuous Integration and Deployment tools to every .NET developer without the hassle of setting up and maintaining their own build server. ...
Hudson
It monitors the execution of repeated jobs, such as building a software project or jobs run by cron. Among those things, currently it focuses on the two jobs ...
Octopus Deploy
Octopus Deploy helps teams to manage releases, automate deployments, and operate applications with automated runbooks. It's free for small teams. ...
FinalBuilder
With FinalBuilder you don't need to edit xml, or write scripts. Visually define and debug your build scripts, then schedule them with windows scheduler, or integrate them with Continua CI, Jenkins or any other CI Server. ...
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
GitLab offers git repository management, code reviews, issue tracking, activity feeds and wikis. Enterprises install GitLab on-premise and connect it with LDAP and Active Directory servers for secure authentication and authorization. A single GitLab server can handle more than 25,000 users but it is also possible to create a high availability setup with multiple active servers. ...
CircleCI
Continuous integration and delivery platform helps software teams rapidly release code with confidence by automating the build, test, and deploy process. Offers a modern software development platform that lets teams ramp. ...
TeamCity alternatives & related posts
- Hosted internally520
- Free open source463
- Great to build, deploy or launch anything async313
- Tons of integrations243
- Rich set of plugins with good documentation208
- Has support for build pipelines108
- Open source and tons of integrations71
- Easy setup63
- It is open-source61
- Workflow plugin54
- Configuration as code11
- Very powerful tool10
- Many Plugins9
- Git and Maven integration is better8
- Great flexibility8
- Continuous Integration6
- Slack Integration (plugin)6
- Github integration6
- Easy customisation5
- Self-hosted GitLab Integration (plugin)5
- 100% free and open source4
- Docker support4
- Excellent docker integration3
- Fast builds3
- Platform idnependency3
- Pipeline API2
- Customizable2
- Can be run as a Docker container2
- It`w worked2
- Hosted Externally2
- AWS Integration2
- JOBDSL2
- It's Everywhere2
- NodeJS Support1
- PHP Support1
- Ruby/Rails Support1
- Universal controller1
- Easily extendable with seamless integration1
- Build PR Branch Only1
- Workarounds needed for basic requirements12
- Groovy with cumbersome syntax7
- Plugins compatibility issues6
- Limited abilities with declarative pipelines6
- Lack of support5
- No YAML syntax4
- Too tied to plugins versions2
related Jenkins posts
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
















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.
Appveyor
- Github integration20
- Simple, reliable & powerful18
- Hosted11
- YML-based configuration11
- Nuget support10
- Windows support6
- Automatic deployment4
- Free for open source4
- Great product, responsive people, free for open-source3
- Easy PowerShell support2
- Easy handling of secret keys2
- Advanced build workers available1
- Remote Desktop into Build Worker1
- Complex user interface1
- Poor documentation1
related Appveyor posts
I recommend using Travis CI and/or Appveyor in all projects.
Projects using these tools have given me confidence to know that I don't cause any breaking changes. Travis CI and Appveyor have functionality to test components of a project across multiple installation projects to ensure that modifications don't break a project. These tools integrate easily with GitHub and are useful in open source projects that must review contributions from many different people.
related Hudson posts
- Powerful29
- Simplicity25
- Easy to learn19
- .Net oriented15
- Easy to manage releases and rollback14
- Allows multitenancy7
- Nice interface4
- Poor UI4
- Config & variables not versioned (e.g. in git)2
- Management of Config2
related Octopus Deploy posts
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
What is the difference between Jenkins deployment and Octopus Deploy? Please suggest which is better?
- No way to undo actions in the editor1
- Hard to solve merge conflicts1
related FinalBuilder posts
- Integrates with other Atlassian tools10
- Great notification scheme4
- Great UI2
- Has Deployment Projects1
- Expensive4
related Bamboo posts
- Self hosted488
- Free416
- Has community edition331
- Easy setup234
- Familiar interface234
- Includes many features, including ci129
- Nice UI105
- Good integration with gitlabci79
- Simple setup52
- Has an official mobile app32
- Free private repository30
- Continuous Integration24
- Open source, great ui (like github)16
- Slack Integration14
- Full CI flow9
- Free and unlimited private git repos8
- User, group, and project access management is simple8
- Intuitive UI7
- All in one (Git, CI, Agile..)7
- Built-in CI6
- Both public and private Repositories4
- Mattermost Chat client3
- Integrated Docker Registry3
- It's fully integrated2
- Unlimited free repos & collaborators2
- I like the its runners and executors feature2
- CI2
- So easy to use2
- One-click install through DigitalOcean2
- It's powerful source code management tool2
- Excellent2
- Build/pipeline definition alongside code2
- Security and Stable2
- Issue system2
- Free private repos2
- Low maintenance cost due omnibus-deployment2
- On-premises2
- Powerful Continuous Integration System1
- Powerful software planning and maintaining tools1
- Groups of groups1
- Kubernetes integration with GitLab CI1
- Review Apps feature1
- Built-in Docker Registry1
- Dockerized1
- Beautiful1
- Wounderful1
- Opensource1
- Because is the best remote host for git repositories1
- Not Microsoft Owned1
- Full DevOps suite with Git1
- Many private repo1
- Native CI1
- HipChat intergration1
- Kubernetes Integration1
- Published IP list for whitelisting (gl-infra#434)1
- Great for team collaboration1
- It includes everything I need, all packaged with docker1
- Multilingual interface1
- The dashboard with deployed environments1
- Supports Radius/Ldap & Browser Code Edits0
- Slow ui performance25
- Introduce breaking bugs every release6
- Insecure (no published IP list for whitelisting)5
- Review Apps feature0
- Built-in Docker Registry0
related GitLab posts
I have mixed feelings on GitHub as a product and our use of it for the Zulip open source project. On the one hand, I do feel that being on GitHub helps people discover Zulip, because we have enough stars (etc.) that we rank highly among projects on the platform. and there is a definite benefit for lowering barriers to contribution (which is important to us) that GitHub has such a dominant position in terms of what everyone has accounts with.
But even ignoring how one might feel about their new corporate owner (MicroSoft), in a lot of ways GitHub is a bad product for open source projects. Years after the "Dear GitHub" letter, there are still basic gaps in its issue tracker:
- You can't give someone permission to label/categorize issues without full write access to a project (including ability to merge things to master, post releases, etc.).
- You can't let anyone with a GitHub account self-assign issues to themselves.
- Many more similar issues.
It's embarrassing, because I've talked to GitHub product managers at various open source events about these things for 3 years, and they always agree the thing is important, but then nothing ever improves in the Issues product. Maybe the new management at MicroSoft will fix their product management situation, but if not, I imagine we'll eventually do the migration to GitLab.
We have a custom bot project, http://github.com/zulip/zulipbot, to deal with some of these issues where possible, and every other large project we talk to does the same thing, more or less.
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.
- Github integration223
- Easy setup175
- Fast builds151
- Competitively priced94
- Slack integration72
- Docker support54
- Awesome UI44
- Great customer support33
- Ios support18
- Hipchat integration14
- SSH debug access12
- Free for Open Source11
- Bitbucket integration5
- Mobile support5
- AWS CodeDeploy integration4
- Nodejs support4
- Great support3
- YAML configuration3
- Free for Github private repo3
- Clojure2
- Simple, clean UI2
- Clojurescript2
- OSX support2
- Continuous Deployment2
- Android support1
- Autoscaling1
- Fair pricing1
- All inclusive testing1
- Helpful documentation1
- Japanese in rspec comment appears OK1
- Favorite1
- Build PR Branch Only1
- Really easy to use1
- Unstable1
- So circular1
- Easy setup, easy to understand, fast and reliable1
- Parallel builds for slow test suites1
- Easy setup. 2.0 is fast!1
- Parallelism1
- Extremely configurable1
- Easy to deploy to private servers1
- Works1
- Unstable9
- Scammy pricing structure6
- Aggressive Github permissions0
related CircleCI 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.
We actually started out on Travis CI, but we've migrated our main builds to CircleCI, and it's been a huge improvement.
The reason it's been a huge improvement is that Travis CI has a fundamentally bad design for their images, where they start with a standard base Linux image containing tons of packages (several versions of postgres, every programming language environment, etc). This is potentially nice for the "get builds for a small project running quickly" use case, but it's a total disaster for a larger project that needs a decent number of dependencies and cares about the performance and reliability of their build.
This issue is exacerbated by their networking infrastructure being unreliable; we usually saw over 1% of builds failing due to transient networking errors in Travis CI, even after we added retries to the most frequently failing operations like apt update
or pip install
. And they never install Ubuntu's point release updates to their images. So doing an apt update
, apt install
, or especially apt upgrade
would take forever. We ended up writing code to actually uninstall many of their base packages and pin the versions of hundreds of others to get a semi-fast, semi-reliable build. It was infuriating.
The CircleCI v2.0 system has the right design for a CI system: we can customize the base image to start with any expensive-to-install packages we need for our build, and we can update that image if and when we want to. The end result is that when migrating, we were able to delete all the hacky optimizations mentioned above, while still ending up with a 50% faster build latency. And we've also had 5-10x fewer issues with networking-related flakes, which means one doesn't have to constantly check whether a build failure is actually due to an issue with the code under test or "just another networking flake".