Alternatives to Gerrit Code Review

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.

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.

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.

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.

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.

Our whole Vue.js frontend stack (incl. SSR) consists of the following tools:

• Nuxt.js consisting of Vue CLI, Vue Router, vuex, Webpack and Sass (Bundler for HTML5, CSS 3), Babel (Transpiler for JavaScript),
• Vue Styleguidist as our style guide and pool of developed Vue.js components
• Vuetify as Material Component Framework (for fast app development)
• TypeScript as programming language
• Apollo / GraphQL (incl. GraphiQL) for data access layer (https://apollo.vuejs.org/)
• ESLint, TSLint and Prettier for coding style and code analyzes
• Jest as testing framework
• Google Fonts and Font Awesome for typography and icon toolkit
• NativeScript-Vue for mobile development

The main reason we have chosen Vue.js over React and AngularJS is related to the following artifacts:

• Empowered HTML. Vue.js has many similar approaches with Angular. This helps to optimize HTML blocks handling with the use of different components.
• Detailed documentation. Vue.js has very good documentation which can fasten learning curve for developers.
• Adaptability. It provides a rapid switching period from other frameworks. It has similarities with Angular and React in terms of design and architecture.
• Awesome integration. Vue.js can be used for both building single-page applications and more difficult web interfaces of apps. Smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.
• Large scaling. Vue.js can help to develop pretty large reusable templates.
• Tiny size. Vue.js weights around 20KB keeping its speed and flexibility. It allows reaching much better performance in comparison to other frameworks.

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.

Our whole Vue.js frontend stack (incl. SSR) consists of the following tools:

• Nuxt.js consisting of Vue CLI, Vue Router, vuex, Webpack and Sass (Bundler for HTML5, CSS 3), Babel (Transpiler for JavaScript),
• Vue Styleguidist as our style guide and pool of developed Vue.js components
• Vuetify as Material Component Framework (for fast app development)
• TypeScript as programming language
• Apollo / GraphQL (incl. GraphiQL) for data access layer (https://apollo.vuejs.org/)
• ESLint, TSLint and Prettier for coding style and code analyzes
• Jest as testing framework
• Google Fonts and Font Awesome for typography and icon toolkit
• NativeScript-Vue for mobile development

The main reason we have chosen Vue.js over React and AngularJS is related to the following artifacts:

• Empowered HTML. Vue.js has many similar approaches with Angular. This helps to optimize HTML blocks handling with the use of different components.
• Detailed documentation. Vue.js has very good documentation which can fasten learning curve for developers.
• Adaptability. It provides a rapid switching period from other frameworks. It has similarities with Angular and React in terms of design and architecture.
• Awesome integration. Vue.js can be used for both building single-page applications and more difficult web interfaces of apps. Smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.
• Large scaling. Vue.js can help to develop pretty large reusable templates.
• Tiny size. Vue.js weights around 20KB keeping its speed and flexibility. It allows reaching much better performance in comparison to other frameworks.

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.

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

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.

Our whole Vue.js frontend stack (incl. SSR) consists of the following tools:

• Nuxt.js consisting of Vue CLI, Vue Router, vuex, Webpack and Sass (Bundler for HTML5, CSS 3), Babel (Transpiler for JavaScript),
• Vue Styleguidist as our style guide and pool of developed Vue.js components
• Vuetify as Material Component Framework (for fast app development)
• TypeScript as programming language
• Apollo / GraphQL (incl. GraphiQL) for data access layer (https://apollo.vuejs.org/)
• ESLint, TSLint and Prettier for coding style and code analyzes
• Jest as testing framework
• Google Fonts and Font Awesome for typography and icon toolkit
• NativeScript-Vue for mobile development

The main reason we have chosen Vue.js over React and AngularJS is related to the following artifacts:

• Empowered HTML. Vue.js has many similar approaches with Angular. This helps to optimize HTML blocks handling with the use of different components.
• Detailed documentation. Vue.js has very good documentation which can fasten learning curve for developers.
• Adaptability. It provides a rapid switching period from other frameworks. It has similarities with Angular and React in terms of design and architecture.
• Awesome integration. Vue.js can be used for both building single-page applications and more difficult web interfaces of apps. Smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.
• Large scaling. Vue.js can help to develop pretty large reusable templates.
• Tiny size. Vue.js weights around 20KB keeping its speed and flexibility. It allows reaching much better performance in comparison to other frameworks.

The continuous integration process for our Rails backend app starts by opening a GitHub pull request. This triggers a CircleCI build and some Code Climate checks.

The CircleCI build is a workflow that runs the following jobs:

• check for security vulnerabilities with Brakeman
• check code quality with RuboCop
• run RSpec tests in parallel with the knapsack gem, and output test coverage reports with the simplecov gem
• upload test coverage to Code Climate

Code Climate checks the following:

• code quality metrics like code complexity
• test coverage minimum thresholds

The CircleCI jobs and Code Climate checks above have corresponding GitHub status checks.

Once all the mandatory GitHub checks pass and the code+functionality have been reviewed, developers can merge their pull request into our Git master branch. Code is then ready to deploy!

#ContinuousIntegration