Articles

There are four main kind of operations when working with a database: Create, Read, Update and Delete (CRUD). However, databases are usually not exposed directly to the clients. Instead, those operations are performed by a server side application with a client-facing API. The most common type of APIs nowadays are based on HTTP. An HTTP API can be built with complete freedom. However, guidelines for best-practice HTTP API design have been created. An API following those guidlines is called a REST (or RESTful) API.

GitLab provides a great number of tools needed for the DevOps cycle of an application. In this guide, we'll install a GitLab instance on our own server and configure it to fit our DevOps needs. Here, we will use a fresh install of Ubuntu 18.04 as a base.

The Nvidia Jetson Nano constitutes a low cost platform for AI applications, ideal for edge computing.However, due to the architecture of its CPU, deploying applications to the SBC can be challenging. In this guide, we'll install and configure K3s, a lightweight kubernetes distribution made specifically for edge devices. Once done we'll build and deploy an TensorFlow model in the K3s cluster.

Flask can be seen as the equivalent of Express for Python. However, although an express application is basically production ready, a Flask app outputs the following when executed by itself:

Let’s imagine that you’ve just finished training your new TensorFlow model and want to start using it in your application(s). One obvious way to do so is to simply import it in the source code of every application that uses it. However, it might be more versatile to keep your model in one place as standalone and simply have applications exchange data with it through API calls. This article will go through the steps of building such a system and deploy the result to Kubernetes.