Codacy聽vs聽Jenkins

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Codacy vs Jenkins: What are the differences?

Developers describe Codacy as "Automated Code Review". 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. 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.

Codacy and Jenkins are primarily classified as "Code Review" and "Continuous Integration" tools respectively.

Some of the features offered by Codacy are:

  • Monitoring of Technical Debt
  • Automated Code Review
  • New and Fixed Issues per commit

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

  • Easy installation
  • Easy configuration
  • Change set support

"Automated code review" is the primary reason why developers consider Codacy over the competitors, whereas "Hosted internally" was stated as the key factor in picking Jenkins.

Jenkins is an open source tool with 13.3K GitHub stars and 5.48K 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 1774 company stacks & 1526 developers stacks; compared to Codacy, which is listed in 44 company stacks and 23 developer stacks.

- No public GitHub repository available -

What is 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

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 Codacy and Jenkins?
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.
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.
Better Code Hub
Better Code Hub runs the first analysis of any GitHub repository with the default configuration. This default configuration is based on the programming languages reported by GitHub and supported by Better Code Hub. Better Code Hub further uses heuristics and commonly used conventions.
Codecov
Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.
codebeat
codebeat helps you prioritize issues and identify quick wins. It provides immediate and continuous feedback on complexity and duplication
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Decisions about Codacy and Jenkins
Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD | 13 upvotes 263.5K views
Amazon EC2
Amazon EC2
LXC
LXC
CircleCI
CircleCI
Docker
Docker
Git
Git
Vault
Vault
Apache Maven
Apache Maven
Slack
Slack
Jenkins
Jenkins
TeamCity
TeamCity
Logstash
Logstash
Kibana
Kibana
Elasticsearch
Elasticsearch
Ansible
Ansible
VirtualBox
VirtualBox
Vagrant
Vagrant

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 36.5K views
atScrayos UG (haftungsbeschr盲nkt)Scrayos UG (haftungsbeschr盲nkt)
Jenkins
Jenkins
GitLab Pages
GitLab Pages
GitLab
GitLab
GitLab CI
GitLab CI

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 241.1K views
atFresha EngineeringFresha Engineering
Logentries
Logentries
Sentry
Sentry
AppSignal
AppSignal
New Relic
New Relic
GitHub
GitHub
Git
Git
Jenkins
Jenkins
CircleCI
CircleCI

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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Ganesa Vijayakumar
Ganesa Vijayakumar
Full Stack Coder | Module Lead | 15 upvotes 383.7K views
SonarQube
SonarQube
Codacy
Codacy
Docker
Docker
Git
Git
Apache Maven
Apache Maven
Amazon EC2 Container Service
Amazon EC2 Container Service
Microsoft Azure
Microsoft Azure
Amazon Route 53
Amazon Route 53
Elasticsearch
Elasticsearch
Solr
Solr
Amazon RDS
Amazon RDS
Amazon S3
Amazon S3
Heroku
Heroku
Hibernate
Hibernate
MySQL
MySQL
Node.js
Node.js
Java
Java
Bootstrap
Bootstrap
jQuery Mobile
jQuery Mobile
jQuery UI
jQuery UI
jQuery
jQuery
JavaScript
JavaScript
React Native
React Native
React Router
React Router
React
React

I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

As per my work experience and knowledge, I have chosen the followings stacks to this mission.

UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

Happy Coding! Suggestions are welcome! :)

Thanks, Ganesa

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Codacy
Codacy
codebeat
codebeat
SonarQube
SonarQube

It is very important to have clean code. To be sure that the code quality is not really bad I use a few tools. I love SonarQube with many relevant hints and deep analysis of code. codebeat isn't so detailed, but it can find complexity issues and duplications. Codacy cannot find more bugs then your IDE. The winner for me is SonarQube that shows me really relevant bugs in my code.

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How developers use Codacy 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.

Avatar of GREGORY NICHOLAS
GREGORY NICHOLAS uses CodacyCodacy

for automated code review, static analysis.

Avatar of scott hutchinson
scott hutchinson uses CodacyCodacy

Real time AI for code reviews

Avatar of InstaGIS
InstaGIS uses CodacyCodacy

Review our code quality

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