Operations | Monitoring | ITSM | DevOps | Cloud

Most Kubernetes deployments live on the cloud. According to the CNCF, while 63 percent of companies use AWS for Kubernetes, 29 percent are deploying Kubernetes on Azure, and the number is rapidly growing. Microsoft Azure provides mature Kubernetes tools, primarily the Azure Kubernetes Service (AKS). In this post, we’ll show you how to run your first Kubernetes cluster on AKS, and how to manage enterprise Kubernetes deployments on AKS with Rancher.

eBPF is a hot topic right now; most of the infrastructure-focused conferences and events have included talks on eBPF over the past year, which is creating a lot of interest in the technology. You might be wondering what eBPF is. eBPF stands for “extended Berkeley Packet Filter” which is a feature in modern Linux kernels that allows you to write mini-programs that are attached to low-level hooks in the Linux kernel, that execute based on certain events (e.g. filtering network traffic).

What is Podman? Well, we will start by saying that Podman is a container engine developed by RedHat, and yes, if you thought about Docker when reading container engine, you are on the right track. Podman wants to be the alternative to the well-known container Docker engine, but you may wonder: what does RedHat offer through Podman? Why should I switch to Podman? Is Podman the replacement for Docker or just another competitor?

Rancher is the enterprise computing platform to run Kubernetes on-premises, in the cloud and at the edge. It’s an excellent platform to get started with containers or for those who are struggling to scale up their Kubernetes operations in production. However, in a world increasingly dominated by public infrastructure providers like Google Cloud, it’s reasonable to ask how Rancher adds value to services like Google’s Kubernetes Engine (GKE).

Editor’s note: Rancher Labs’ William Jimenez provides an introduction to CIS Scan. Then Saiyam Pathak takes over with a hands-on demo. Cluster security is critical to any successful Kubernetes strategy. Recent research by AimPoint revealed that 44 percent of respondents had delayed application production due to security concerns around Kubernetes containers. Yet securing Kubernetes is a complex machine with many moving parts, integrations and knobs and levers.

As a system administrator, you will need to monitor your containers for a wide array of reasons. Between analyzing the health of your containers, avoiding resource constraints, and collecting, parsing, and visualizing data, one could easily get lost.

In this blog post, you’ll learn how to create a reusable Sysdig Secure image scanning task, for Tekton pipelines and Openshift clusters, that can be deployed in many pipelines. As a DevOps engineer, you want to deliver applications fast but keeping compliance with security standards like CIS, PCI DSS or NIST 800-190, GDPR can be an arduous task. You might implement image scanning in your CI/CD pipelines to detect and resolve issues such as known vulnerabilities and incorrect configurations.

Recently the leadership at Rancher Labs challenged all of us to think about ways we can contribute to the community during this current crisis. Coming up with ways to help in such an overwhelming situation is quite daunting. Since most needs are medical related, finding ways to apply software isn’t obvious. When I heard about Folding@home’s (FAH) efforts to reprioritize their computing resources toward COVID-19 research, I was immediately curious.

AWS Fargate allows you to run applications in Amazon Elastic Container Service without having to manage the underlying infrastructure. With Fargate, you can define containerized tasks, specify the CPU and memory requirements, and launch your applications without spinning up EC2 instances or manually managing a cluster. Datadog has proudly supported Fargate since its launch, and we have continued to collaborate with AWS on best practices for managing serverless container tasks.

Hasura is an open source engine that connects to your databases & microservices and auto-generates a production-ready GraphQL backend. By using Hasura in conjunction with Qovery, you get a blazing fast, auto-scallable and extensible solution to quickly build your applications.