Today I am very excited to announce that Rancher Labs’ Project Longhorn has been accepted by the Cloud Native Computing Foundation as a sandbox project. Many Kubernetes users still find it challenging to run stateful workloads and manage persistent storage. Longhorn aims to help you manage stateful workloads in Kubernetes by providing a solution for persistent storage that you can easily deploy, use, and manage.
We’re excited today to release the Sysdig 2019 Container Usage Report. Continued momentum for Kubernetes and greater adoption of cloud-native architectures are changing not just usage patterns, but processes and organizational structures as well. One of the surprising insights this year is the 2X increase in the number of containers that live for less than five minutes. As services grow more dynamic, cloud teams are recognizing the need to integrate security into their DevOps processes.
In this blog post, you’ll learn how to setup image scanning for Azure Pipelines using Sysdig Secure DevOps Platform. Azure DevOps gives teams tools like version control, reporting, project management, automated builds, lab management, testing, and release management. Azure Pipelines automates the execution of CI/CD tasks, like building the container images when a commit is pushed to your git repository or performing vulnerability scanning on the container image.
Since Kubernetes was open sourced by Google in 2014, it has steadily grown in popularity to become nearly synonymous with Docker orchestration. Kubernetes is being widely adopted by forward-thinking organizations such as Box and GitHub for a number of reasons: its active community, rapid development, and of course its ability to schedule, automate, and manage distributed applications on dynamic container infrastructure.
The k3s project was started by Darren Shepherd, Chief Architect at Rancher 7 months ago and has already become one of the most popular Kubernetes options on the CNCF Landscape by number of GitHub stars. To put this into context, k3s is more popular than OpenShift by IBM/Red Hat and only Rancher Kubernetes itself is more popular than k3s. Now stars are indicative of interest and popularity only and that should be noted.
“How do I enable GitOps for my network policies?” That is a common question we hear from security teams. Getting started with Kubernetes is relatively simple, but moving production workloads to Kubernetes requires alignment from all stakeholders – developers, platform engineering, network engineering, security. Most security teams already have a high-level security blueprint for their data centers.
Amazon ECS allows you to easily run containers in AWS in units called tasks. Groups of identical tasks are called services, and groups of services running on the same infrastructure are called clusters. Since it is critical to the health of your application, properly monitoring ECS is a top priority for most teams. In this blog post, we will go over how Blue Matador monitors ECS tasks automatically and without configuration.
Over the last few years, we have seen a significant shift with companies moving away from developing heavy, monolithic applications and instead adopting new approaches like microservices and even serverless applications. These allow companies to work in a faster and more agile way. Speed and agility are important when a task like deploying a new piece of code to production multiple times a day is normal behavior for a modern environment.
Windows Support went GA for Kubernetes in version 1.14 and represented years of work. This has been the effort of excellent engineers from companies including Microsoft, Pivotal, VMWare, RedHat, and the now-defunct Apprenda, among others. I’ve been a lurker and occasional contributor to the sig-windows community going back to my days with Apprenda, and I’ve continued to follow it in my current role with Rancher Labs.
What is the bare minimum you need to build, test and run your Java application in Docker container? The recipe: Create a separate Docker image for each step and optimize the way you are running it. I started working with Java in 1998, and for a long time, it was my main programming language. It was a long love–hate relationship. During my work career, I wrote a lot of code in Java. Despite that fact, I don’t think Java is usually the right choice for microservices.
