Operations | Monitoring | ITSM | DevOps | Cloud

Service Meshes have been gaining a lot of popularity lately, more so amongst Spring and Java developers who wish to address cross cutting concerns. But, are you wondering what exactly are Service Meshes? What are some of the popular types out there? And most importantly, what kind of problems do they actually solve? Well, look no further! This blog is here to provide you with the answers you seek.

Before attending Icinga Berlin in May this year, Daniel Bodky and Markus Opolka from our partner NETWAYS developed the very first Icinga Kubernetes Helm Charts and released it in an alpha version. If you have ever wanted to deploy an entire Icinga stack in your Kubernetes cluster, now is your chance. I also want to highlight Daniel’s talk again on how Icinga can run on Kubernetes and the challenges involved.

Fleet, also known as “Continuous Delivery” in Rancher, deploys application workloads across multiple clusters. However, most applications need configuration and credentials. In Kubernetes, we store confidential information in secrets. For Fleet’s deployments to work on downstream clusters, we need to create these secrets on the downstream clusters themselves.

In this article, we will deploy a clustered Prometheus setup that integrates Thanos. It is resilient against node failures and ensures appropriate data archiving. The setup is also scalable. It can span multiple Kubernetes clusters under the same monitoring umbrella. Finally, we will visualize and monitor all our data in accessible and beautiful Grafana dashboards.

Have you heard about eBPF? It’s the technology that’s set to transform the Kubernetes landscape. In this article, we’ll explore what eBPF is and why it’s poised to become the next big thing in Kubernetes. But here’s the catch – despite its game-changing potential, it seems that few people are truly aware of its impact. Let’s delve into the details and discover why you should care.

Kubernetes has emerged as the go-to platform for container orchestration, empowering organizations to efficiently deploy and manage applications at scale. As the demands on applications continue to grow, scaling Kubernetes becomes essential to ensure high availability, optimal performance, and seamless expansion. Today, we will delve into the intricacies of scaling Kubernetes on AWS, exploring best practices, popular tools, performance optimization strategies, cost considerations, and future trends.

If you are looking into the cloud-native world, then the chances of coming across the term “Kubernetes” is high. Kubernetes, also known as K8s, is an open-source system that has the primary responsibility of being a container orchestrator. This has quickly become a lifeline for managing our containerized applications through creating automated deployments.

Building Docker images efficiently is crucial for developers and organizations seeking streamlined development and deployment processes, and it’s a real topic for the 50k developers on Qovery; a few weeks ago, a topic was even open on our forum about it. In this article, we will explore three valuable tips gathered along the way to improve the build time of your Dockerfiles, allowing you to optimize your workflow and save valuable time.