tutorial

All the ways you can deploy a web application on google cloud platform

Google Cloud Platform (GCP) offers a wide range of tools and services that can be used to deploy web applications. The platform provides flexibility and scalability, making it a popular choice for developers. In this post, we will discuss all the ways you can deploy a web application on GCP, including Compute Engine, Kubernetes Engine, App Engine, and Cloud Run. Compute Engine Compute Engine is a virtual machine (VM) that allows you to deploy and run your own applications on GCP.

Docker Compose

is a tool for defining and running multi-container Docker applications. With Compose, you use a YAML file to configure your application’s services. Then, with a single command, you create and start all the services from your configuration. Using Compose is a great way to simplify the development, testing, and deployment of your applications. It allows you to focus on writing code, rather than spending time on the intricacies of configuring and connecting multiple containers.

Thoughts of IDEs

Ok, we are, my second post, I never thought I would reach this milestone. Jokes aside, we are here to a brief post to talk about Text Editors on steroids. IDEs. Web applications versus Native applications I will say the hard truth here. Web based OSes applications are the worst performing ones we have nowadays. We need to state that first. All those apps have to span a “small” browser inside theirs apps to display content, or use some sort of HTML to native code conversion, and none of them have resolved the problem.

Terminal like a pro

It is my first post, or, in programming language, it means, a hello world post. So, let’s talk about on how to tweak your terminal to make it look like the picture above. Let’s dive in. To summarize, we need to tie together a couple of solutions, Nerd Fonts, Oh-My-ZSH, bash history, auto-completions, syntax highlight and interactive-cd plugins, powerlevel9k theme, and iTerm2 (for macOS users). {:class=“img-fluid”} Install Iterm2 This section is only intended for macOS users, so if you are using any Linux distro, you can skip ahead to the next section safely.

Developing with NextJS

Next.js is a popular framework for building server-rendered React applications. It is easy to get started with and offers a number of features that make it a great choice for building web applications, including automatic code splitting, optimized performance, and easy integration with other tools and libraries. One way to start developing an application using Next.js is to use Docker and Docker Compose. Docker allows you to run your application in a containerized environment, which makes it easy to deploy and manage.

Developing with Postgres

PostgreSQL, also known as Postgres, is a powerful and feature-rich open-source relational database management system. It is a popular choice for many developers and organizations, thanks to its robust set of features and excellent performance. If you’re new to Postgres, one of the easiest ways to get started is by using Docker and Docker Compose. Docker allows you to run applications in containers, which are lightweight and portable environments that include everything the application needs to run.

Unraveling the Mysteries of Golang: Understanding How Golang Projects are Built and How They Work

Golang, also known as Go, is a popular programming language that has been gaining traction over the years. It was created in 2007 by Google’s Robert Griesemer, Rob Pike, and Ken Thompson, with the aim of being a simple, fast, and efficient language that can handle modern software development needs. One of the unique features of Golang is its ability to handle concurrency with ease, making it ideal for building large-scale distributed systems.

The Power of Python for Data Science: A Comprehensive Guide

Data Science has emerged as a critical field in today’s digital age, with organizations leveraging large amounts of data to make informed decisions. Python has become a popular tool for Data Scientists, providing them with the ability to analyze, manipulate, and visualize data in a concise and efficient way. In this article, we will explore the reasons why Python is a popular choice for Data Science, its libraries and tools, and its applications in various industries.

Unleashing the Power of Julia in Parallel Computing and Concurrency

Parallel computing and concurrency have become essential in today’s world of computing, where the processing of vast amounts of data is common. Julia is a high-level, dynamic programming language that is gaining popularity in the scientific computing community. It is known for its speed and performance, making it ideal for scientific computing tasks. In this article, we will explore the power of Julia in parallel computing and concurrency, its benefits, and its applications.