Qovery offers a streamlined, powerful platform for developers. Its goal is to simplify DevOps processes and enhance the overall developer experience. For those new to Qovery or considering adopting it, there's a simple way to test its capabilities on your local machine. Using the "qovery demo up" command, you can create a non-production environment to explore Qovery's features without any complicated setups. Here is a step-by-step guide to help you get started.

As AI and machine learning workloads continue to grow in complexity and size, the need for efficient and scalable infrastructure becomes more important than ever. In this tutorial, I will show you how to deploy AI applications on AWS Elastic Kubernetes Service (EKS) with Karpenter from scratch, leveraging GPU resources for high-performance computing.

Kubernetes annotations are key-value pairs attached to Kubernetes objects, providing a flexible way to extend the functionality of your Kubernetes resources without altering their internal specifications. These annotations serve as a tool to store additional metadata to tailor behavior, orchestrate tools, and interact seamlessly with third-party utilities that complement your Kubernetes environment.

In the last years, Kubernetes has grown tremendously and is considered by most companies to be the best platform to run applications today. In simple words, Kubernetes is an open-source container orchestration platform that allows you to run and manage containerized applications at scale. In this article, I will explain how you can run Kubernetes on AWS in 3 different ways. But before getting down the road, let me explain why it does make sense to run Kubernetes on AWS.

Ephemeral environments are temporary, isolated, but self-contained deployment environments crucial for development and testing within software projects. While I already discussed the basics and benefits of Ephemeral Environments, today I will go through the practical steps of implementing ephemeral environments in your CI/CD pipeline using Kubernetes. I will start with how you can do it with Kubernetes native tools, and how you can automate the ephemeral environments in your CI/CD.

The motivation behind automating Kubernetes deployments stems from the need to accelerate development cycles, minimize manual errors, and achieve consistent deployments. In today’s application development where container orchestration is a crucial aspect, automating the Kubernetes deployment is inevitable. Despite challenges such as maintaining security and handling complex dependencies, automation remains a powerful solution.

Kubernetes is a powerful tool for deploying and managing containerized applications. However, managing its clusters is a critical but challenging task for many organizations. Today, we will discuss the benefits of managing multiple clusters, and the challenges they present, and offer a quick technical guide on managing these clusters efficiently.

The emergence of Ephemeral Environments poses a compelling question: What can organizations expect from adopting this transformative approach? What are the hurdles they may face along the way? And what results can they anticipate? These are the questions I will address in this article as we explore why Ephemeral Environments are garnering attention and what makes them so pivotal for engineering teams today. Let's go!

Providing the best support for our customers has always been at the core of our company since day one, and it is something that will never change. In the infrastructure space, one downtime can be critical and have a huge business impact. Having the best support is key to running a business with confidence. Today, we are glad to introduce our new support plans, allowing us to provide best-in-class support and scale with the increasing number of clients using our product.

AWS Elastic Beanstalk streamlines the deployment and management of applications in the cloud, offering developers an easy way to deploy services without worrying about the underlying infrastructure. However, while it simplifies many aspects of cloud deployment, it also presents challenges, including limited customization and potential vendor lock-in, which might not suit all project needs or scalability requirements.