When monitoring highly distributed applications, which might rely on hundreds of services and infrastructure components across multiple cloud-based and on-premise environments, identifying problems and pinpointing the origin of an issue can be challenging. Even if you already have robust monitoring and alerts, your infrastructure and applications will likely change over time, which may make it difficult to reliably detect irregular behavior.

Rancher 2.4 is here – with new under-the-hood changes that pave the way to supporting up to 1 million clusters. That’s probably the most exciting capability in the new version. But you might ask: why would anyone want to run thousands of Kubernetes clusters – let alone tens of thousands, hundreds of thousands or more? At Rancher Labs, we believe the future of Kubernetes is multi-cluster and fully heterogeneous.

In the last month, we’ve seen one of the most dramatic movements in economic activity ever recorded. Many business owners are clutched in the grips of mandatory closures and uncertainty of the future, for their business and for their employees. The tech world has been hit less hard — at least for now. Remote work is second nature to many of us and offering our products in the digital space means we are open for business.

As your organization gets more comfortable with Kubernetes in development, you’ll want to prepare to adopt it in production. But mastering Kubernetes in dev does not necessarily translate into mastering it in prod. There are many additional components that must be configured and fine tuned to ensure reliable, self-healing production clusters. In this blog, we’ll walk through the key elements of a Kubernetes production setup.

The Vanilla framework has a history of being released very infrequently. Sometimes it has been months between releases, which made the upgrade process often hard and time-consuming. One of the reasons for that was a manual and a quite time-consuming release process. Over several weeks earlier this year, we’ve been working on various improvements that helped us release more frequently and reliably.

In part 1 we will talk about the industrial applications and benefits that 5G and fast compute at the edge in the form of ‘smart cell towers’ will bring to AI products. In part 2 we will go deeper into how you can benefit from this new opportunity. Part 3 will focus on the key technical barriers that 5G and Edge compute remove for AI applications.

People working in digital enterprises will have no doubt noticed that customers have an insatiable appetite for new features and updates, with next to zero tolerance if digital services are performing poorly – or not at all. To thrive and survive in the digital era, it’s become an imperative for organizations to innovate at an unprecedented pace.

Kubernetes offers scalability and reliability for your container-based applications. Combine this with GKE, and you now eliminate the need to install or operate clusters on your own. A huge plus to using GKE is that you now will be running Kubernetes in a GCP environment, therefore you can utilize all the handy integrations Google has to offer. Codefresh simplifies the process even more, by automating the process of getting your code built, tested, and deployed.

There are many reasons why you may want to use Artifactory as your Maven repository. For example, it allows tagging Maven artifacts with custom properties, so that they can later be found based on specific criteria. It stores build metadata about your artifacts, and allows controlling the repositories used by the Maven build, without modifying the pom file. In this post, I’d like to focus on one specific advantage, Maven deployments in Jenkins.