We are delighted to announce the release of Rancher Desktop 1.11.0! This update comes with new features, Snapshots and the Container Dashboard, along with other important bug fixes.

Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It allows you to create and manage clusters of machines, called Kubernetes clusters, to run your applications in a scalable and highly available manner. Kubernetes clusters provide a distributed and scalable platform for running containerized workloads.

Google Cloud Platform (GCP) and Microsoft Azure are two of the leading cloud computing platforms, offering a wide range of services for businesses of all sizes. When choosing a cloud platform, it is important to consider factors such as pricing, features, performance, etc. This article will compare different services of GCP with Azure, including pricing models. We will provide a summary of the comparison in the form of a table at the end of the article.

In the world of Kubernetes, where applications are encapsulated within containers and seamlessly distributed across diverse clusters of computers, the enigmatic Kubernetes scheduler takes centre stage. Think of it as the orchestra conductor of your Kubernetes cluster, orchestrating a symphony of resources to ensure seamless operations. This unassuming yet powerful component leverages a sophisticated algorithm to perform the intricate dance of optimizing resource allocation.

At Qovery, we're consistently pushing boundaries to enhance developer experiences. One of our standout achievements has been accelerating deployment times, a feat we're incredibly proud of. Today, we'd like to pull back the curtain and share how we've sped up deployments by a staggering 30% through our innovative Container Image Mirroring.

In the earlier days of the internet, organizations faced resource allocation challenges when running applications on physical servers. They initially resorted to running individual applications on separate physical servers, which was costly and not scalable. As the internet continued to evolve, organizations sought more efficient ways to manage their applications and workloads.

Incompatible hardware is a common cause of application failures for distributed teams. Most teams depend on containerization tools like Docker to prevent these failures. But is there any way to automate the deployment of Docker images more efficiently and intuitively? In this article, I will show you how simple it is to do this by combining CircleCI and Microsoft Azure to build a CI/CD pipeline for a Dockerized Spring Boot project.