Alternatives to SVN (Subversion)

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.

Application and Data: Since my personal website ( https://alisoueidan.com ) is a SPA I've chosen to use Vue.js, as a framework to create it. After a short skeptical phase I immediately felt in love with the single file component concept! I also used vuex for state management, which makes working with several components, which are communicating with each other even more fun and convenient to use. Of course, using Vue requires using JavaScript as well, since it is the basis of it.

For markup and style, I used Pug and Sass, since they’re the perfect match to me. I love the clean and strict syntax of both of them and even more that their structure is almost similar. Also, both of them come with an expanded functionality such as mixins, loops and so on related to their “siblings” (HTML and CSS). Both of them require nesting and prevent untidy code, which can be a huge advantage when working in teams. I used JSON to store data (since the data quantity on my website is moderate) – JSON works also good in combo with Pug, using for loops, based on the JSON Objects for example.

To send my contact form I used PHP, since sending emails using PHP is still relatively convenient, simple and easy done.

DevOps: Of course, I used Git to do my version management (which I even do in smaller projects like my website just have an additional backup of my code). On top of that I used GitHub since it now supports private repository for free accounts (which I am using for my own). I use Babel to use ES6 functionality such as arrow functions and so on, and still don’t losing cross browser compatibility.

Side note: I used npm for package management. 🎉

*Business Tools: * I use Asana to organize my project. This is a big advantage to me, even if I work alone, since “private” projects can get interrupted for some time. By using Asana I still know (even after month of not touching a project) what I’ve done, on which task I was at last working on and what still is to do. Working in Teams (for enterprise I’d take on Jira instead) of course Asana is a Tool which I really love to use as well. All the graphics on my website are SVG which I have created with Adobe Illustrator and adjusted within the SVG code or by using JavaScript or CSS (SASS).

I've been excited about Git ever since it got a built-in UI. It's the perfect combination of a really solid, simple data model, which allows an experienced user to predict precisely what a Git subcommand will do, often without needing to read the documentation (see the slides linked from the attached article for details). Most important to me as the lead developer of a large open source project (Zulip) is that it makes it possible to build a really clean, clear development history that I regularly use to understand details of our code history that are critical to making correct changes.

And it performs really, really well. In 2014, I managed Dropbox's migration from Mercurial to Git. And just switching tools made just about every common operation (git status, git log, git commit etc.) 2-10x faster than with Mercurial. It makes sense if you think about it, since Git was designed to perform well with Linux, one of the largest open source projects out there, but it was still a huge productivity increase that we got basically for free.

If you're learning Git, I highly recommend reading the other sections of Zulip's Git Guide; we get a lot of positive feedback from developers on it being a useful resource even for their projects unrelated to Zulip.

I already use DVC to keep track and store my datasets in my machine learning pipeline. I have also started to use MLflow to keep track of my experiments. However, I still don't know whether to use DVC for my model files or I use the MLflow artifact store for this purpose. Or maybe these two serve different purposes, and it may be good to do both! Can anyone help, please?