Jenkins vs Puppet Labs: What are the differences?
Jenkins: 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; Puppet Labs: Server automation framework and application. Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.
Jenkins and Puppet Labs are primarily classified as "Continuous Integration" and "Server Configuration and Automation" tools respectively.
Some of the features offered by Jenkins are:
- Easy installation
- Easy configuration
- Change set support
On the other hand, Puppet Labs provides the following key features:
- Insight- Puppet Enterprise's event inspector gives immediate and actionable insight into your environment, showing you what changed, where and how by classes, nodes and resources.
- Discovery- Puppet Enterprise delivers a dynamic and fully-pluggable discovery service that allows you to take advantage of any data source or real-time query results to quickly locate, identify and group cloud nodes.
- Provisioning- Automatically provision and configure bare metal, virtual, and private or public cloud capacity, all from a single pane. Save time getting your cloud projects off the ground by reusing the same configuration modules you set up for your physical deployments.
"Hosted internally" is the primary reason why developers consider Jenkins over the competitors, whereas "Devops" was stated as the key factor in picking Puppet Labs.
Jenkins and Puppet Labs are both open source tools. Jenkins with 13.2K GitHub stars and 5.43K forks on GitHub appears to be more popular than Puppet Labs with 5.34K GitHub stars and 2.1K GitHub forks.
Instacart, Lyft, and Twitch are some of the popular companies that use Jenkins, whereas Puppet Labs is used by Twitch, PayPal, and Salesforce. Jenkins has a broader approval, being mentioned in 1753 company stacks & 1479 developers stacks; compared to Puppet Labs, which is listed in 181 company stacks and 48 developer stacks.
What is Jenkins?
What is Puppet Labs?
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By 2014, the DevOps team at Lyft decided to port their infrastructure code from Puppet to Salt. At that point, the Puppet code based included around "10,000 lines of spaghetti-code,” which was unfamiliar and challenging to the relatively new members of the DevOps team.
“The DevOps team felt that the Puppet infrastructure was too difficult to pick up quickly and would be impossible to introduce to [their] developers as the tool they’d use to manage their own services.”
To determine a path forward, the team assessed both Ansible and Salt, exploring four key areas: simplicity/ease of use, maturity, performance, and community.
They found that “Salt’s execution and state module support is more mature than Ansible’s, overall,” and that “Salt was faster than Ansible for state/playbook runs.” And while both have high levels of community support, Salt exceeded expectations in terms of friendless and responsiveness to opened issues.
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 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.
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).
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.
Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.
For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.
For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.
Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.
I'm using puppet to configure my servers. This makes it really simple to ensure that I have the same environment. There is a bit of a learning curve, but the repeatability definitely makes it worth the effort. I found puppet to be a little easier to pick up relative to chef, but I've used both. They're both great solutions.
I really like that there are a lot of modules available on the puppet forge that are being actively maintained.
We provision all servers with puppet. We have one central Puppet server which uses puppet modules referenced by a Puppetfile. Those puppet modules are partly from forge and partly self written.
All modules which are self written, have to be tested using rspec-puppet and beaker.
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.
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.
- 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.
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.
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.
Opstax uses puppet for role/profile based configuration management and the distribution of small/static code.
Configures or servers and allows us to be region independent we have 5 regions across the globe.