Codecov聽vs聽Jenkins

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Codecov vs Jenkins: What are the differences?

Developers describe Codecov as "Hosted coverage reports with awesome features to enhance your CI workflow". Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security. On the other hand, Jenkins is detailed as "An extendable open source continuous integration server". 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.

Codecov can be classified as a tool in the "Code Coverage" category, while Jenkins is grouped under "Continuous Integration".

Some of the features offered by Codecov are:

  • Beautiful Reports
  • Pull Request Comments
  • Interactive Commit Graphs

On the other hand, Jenkins provides the following key features:

  • Easy installation
  • Easy configuration
  • Change set support

"More stable than coveralls" is the primary reason why developers consider Codecov over the competitors, whereas "Hosted internally" was stated as the key factor in picking Jenkins.

Jenkins is an open source tool with 13.2K GitHub stars and 5.43K GitHub forks. Here's a link to Jenkins's open source repository on GitHub.

According to the StackShare community, Jenkins has a broader approval, being mentioned in 1753 company stacks & 1479 developers stacks; compared to Codecov, which is listed in 49 company stacks and 28 developer stacks.

- No public GitHub repository available -

What is Codecov?

Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

What is 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.
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What are some alternatives to Codecov and Jenkins?
Code Climate
After each Git push, Code Climate analyzes your code for complexity, duplication, and common smells to determine changes in quality and surface technical debt hotspots.
Coveralls
Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.
SonarQube
SonarQube provides an overview of the overall health of your source code and even more importantly, it highlights issues found on new code. With a Quality Gate set on your project, you will simply fix the Leak and start mechanically improving.
Codacy
Codacy is an automated code review tool for Scala, Java, Ruby, JavaScript, PHP, Python, CoffeeScript and CSS. It's continuous static analysis without the hassle. Save time in Code Reviews. Tackle your technical debt
uberalls
Code coverage metric storage service. Provide coverage metrics on differentials with Phabricator and Jenkins, just like Coveralls does for GitHub and TravisCI.
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Decisions about Codecov and Jenkins
Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD | 15 upvotes 351.4K views
Vagrant
Vagrant
VirtualBox
VirtualBox
Ansible
Ansible
Elasticsearch
Elasticsearch
Kibana
Kibana
Logstash
Logstash
TeamCity
TeamCity
Jenkins
Jenkins
Slack
Slack
Apache Maven
Apache Maven
Vault
Vault
Git
Git
Docker
Docker
CircleCI
CircleCI
LXC
LXC
Amazon EC2
Amazon EC2

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

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

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

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

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

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

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

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Joshua Dean K眉pper
Joshua Dean K眉pper
CEO at Scrayos UG (haftungsbeschr盲nkt) | 6 upvotes 45.4K views
atScrayos UG (haftungsbeschr盲nkt)Scrayos UG (haftungsbeschr盲nkt)
GitLab CI
GitLab CI
GitLab
GitLab
GitLab Pages
GitLab Pages
Jenkins
Jenkins

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.

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Sebastian G臋bski
Sebastian G臋bski
CTO at Shedul/Fresha | 4 upvotes 254.8K views
atFresha EngineeringFresha Engineering
CircleCI
CircleCI
Jenkins
Jenkins
Git
Git
GitHub
GitHub
New Relic
New Relic
AppSignal
AppSignal
Sentry
Sentry
Logentries
Logentries

Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).

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Jenkins
Jenkins

I'd recommend to go with Jenkins .

It allows a lot of flexibility and additional plugins that provide extra features, quite often not possible to find elsewhere unless you want to spend time on providing that by yourself.

One of key features are pipelines that allow to easily chain different jobs even across different repos / projects.

The only downside is you have to deploy it by yourself.

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Tim Abbott
Tim Abbott
Founder at Zulip | 4 upvotes 15.4K views
atZulipZulip
Codecov
Codecov
Coveralls
Coveralls

We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

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How developers use Codecov and Jenkins
Avatar of Kalibrr
Kalibrr uses JenkinsJenkins

All of our pull requests are automatically tested using Jenkins' integration with GitHub, and we provision and deploy our servers using Jenkins' interface. This is integrated with HipChat, immediately notifying us if anything goes wrong with a deployment.

Avatar of Wirkn Inc.
Wirkn Inc. uses JenkinsJenkins

Jenkins is our go-to devops automation tool. We use it for automated test builds, all the way up to server updates and deploys. It really helps maintain our homegrown continuous-integration suite. It even does our blue/green deploys.

Avatar of B霉i Thanh
B霉i Thanh uses JenkinsJenkins
  • Continuous Deploy
  • Dev stage: autodeploy by trigger push request from 'develop' branch of Gitlab
  • Staging and production stages: Build and rollback quicly with Ansistrano playbook
  • Sending messages of job results to Chatwork.
Avatar of AngeloR
AngeloR uses JenkinsJenkins

Currently serves as the location that our QA team builds various automated testing jobs.

At one point we were using it for builds, but we ended up migrating away from them to Code Pipelines.

Avatar of Trusted Shops GmbH
Trusted Shops GmbH uses JenkinsJenkins

We use Jenkins to schedule our Browser and API Based regression and acceptance tests on a regular bases. We use additionally to Jenkins GitlabCI for unit and component testing.

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