The latest News and Information on Containers, Kubernetes, Docker and related technologies.
Codefresh is an awesome platform for doing GitOps deployments to Kubernetes. Starting last year, the Codefresh team has been adding rich integrations with Argo CD and Argo Rollouts, GitOps observability dashboards, and more. Codefresh pipelines, in particular, have played an integral role in our customers’ progressive delivery workflows by allowing them to orchestrate all of the testing, analysis, and rollback activities that work in conjunction with Argo CD synchronization.
With everything going on in the world, it seems like a lifetime ago that we started talking about the Splunk Operator for Kubernetes, which enables customers to easily deploy, scale, and manage Splunk Enterprise on their choice of cloud environment. During that time, we’ve heard from an increasing number of on-premise and public cloud Bring-Your-Own-License Splunk customers that containerization and Kubernetes are an important part of their current and future deployment plans.
Codefresh is a DevOps automation platform with Kubernetes and Docker native tools and features. You can create powerful pipelines and utilize the provided dashboards by connecting different Kubernetes clusters and registries to receive further insights into your deployments. Additionally, by enabling GitOps for your repositories you can reach the highest level of confidence in your Kubernetes deployments.
Welcome to another monthly update on what’s new from Sysdig. Ramadan Kareem to all observing the holy month of Ramadan. Our team continues to work hard to bring great new features to all of our customers, automatically and for free! This last month was a big month for security with our release of Cloud Security Posture Management (CSPM), and we had lots of fun designing and releasing our new Cloud Chaos game!
In this video with with Kohsuke Kawaguchi (KK) from Launchable and Viktor Farcic we talk about testing K8s applications. Do we really need to write all the tests every time we make a change to the source code or make a release? That could take minutes or even hours. Wouldn’t it be better to run only the tests related to the changes we are making or the phase of the lifecycle of an application? Is the future of testing in AI and ML?
Whether running on the public cloud or a private cloud, the use of containers is ingrained in today’s devops oriented workflows. Having workloads set up to run under the mandated compliance requirements is thus necessary to fully exploit the potential of containers. This article focuses on how to build and run containers that comply with the US and Canada government FIPS140-2 data protection standard.
During the next five weeks, our team will work to improve the overall experience of Qovery. We gathered all your feedback (thank you to our wonderful community 🙏), and we decided to make significant changes to make Qovery a better place to deploy and manage your apps. This series will reveal all the changes and features you will get in the next major release of Qovery. Let's go!
