Hello and welcome to the first entry in my devlog series about snixr, a link shortening service I am building in Go. In this series, I’ll share my journey of building snixr from scratch and the lessons I learned along the way. Let’s dive in!
🌩️ Cloud Native
One of the coolest things about snixr is that it’s cloud-native! But what does that even mean? Think of it like this: building and deploying applications in a way that’s optimized for the cloud environment 🌩️. And we achieve that by using Docker - a platform for containerizing applications.
Now, what exactly are containers, you ask? They’re like little bundles of software that contain everything your app needs to run, from the code to the dependencies. By packaging up snixr and its dependencies into a container, we can easily deploy it on any cloud platform that supports Docker, from AWS to Google Cloud. No more worrying about compatibility issues! 🎉
But where did cloud-native even come from? Well, it all started with the rise of cloud computing ☁️. As more and more businesses began moving their apps to the cloud, they realized that the traditional way of building and deploying apps just wouldn’t cut it. Enter cloud-native - an approach to building and running apps that takes full advantage of the cloud environment, with all its flexibility and scalability. And that’s exactly what we’re doing with snixr.
🐹 Go
Another crucial aspect of building a fast and scalable link shortening service is choosing the right programming language. For snixr, I chose Go for its speed, efficiency, and concurrency support. Go’s built-in concurrency primitives make it easy to write highly parallelized code that can handle a large number of requests with minimal overhead.
📦 Redis
To store the shortened links and their associated URLs, we need a fast and scalable database. For snixr, I chose Redis, an in-memory data store that’s lightning-fast and highly available. Redis is perfect for this use case because it can handle a large number of read and write requests per second without breaking a sweat.
🔍 Algorithmic Complexity
One of the most important factors in building a link shortening service is the algorithm used to generate the shortened links. While other services may generate random strings of characters, I decided to use a custom algorithm based on SHA-256 hashes. This provides a more secure and predictable way of generating short links with a low chance of collisions.
💻 Code Snippets
To deploy our snixr app, we’ll be using Docker, a powerful tool for creating, deploying, and running applications. In our Dockerfile, we start by defining the parent image we’ll be using, in this case golang:1.20-alpine. We set the working directory to /app and copy our code into the container. Then we move into the cmd/snixr directory and build the app with the go build command. Finally, we expose port 3000 and define the command to run when the container starts with CMD ["./snixr"].
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Using Docker for our deployment allows us to package our application and its dependencies into a single image that can be easily deployed on any system that has Docker installed. This makes it a great choice for cloud-native applications 🐳🌩️. Additionally, by using a lightweight Alpine-based image, we ensure that our image is as small and efficient as possible.
🚀 Ready to launch snixr!
In this first devlog post, we’ve covered the basics of what snixr is and why we’re building it. We’ve also taken a look at the importance of cloud-native technologies like Docker for making snixr easy to deploy and scale, and how Go and Redis provide us with the performance we need to create a blazingly fast link shortening service.
Now that we’ve got a solid foundation in place, it’s time to take snixr to the next level. In the next devlog post, we’ll dive into the details of how we’re optimizing our code and architecture to create the fastest link shortening service possible. So stay tuned, and get ready to launch your links to the stratosphere with snixr! 🚀