Incident classification is a standardized way of organizing incidents with established categories. Incidents can include outages caused by errors in code, hardware failures, resource deficits — anything that disrupts normal operations. Each new incident should fit into a category dependent on the areas of the service affected, and in a ranking of the severity of the incident. Each of these classifications should have an established response procedure associated with it.

Reinventing any technology is an interminable process. When it comes to legacy infrastructure and virtualization, Nutanix took the giant leap to hyper-converged infrastructure (HCI). Dating back to 2009, Nutanix brought in HCI with the vision to invent a better way to build and manage data centers.

Over the past few years, NGINX users have naturally gravitated toward Grafana, and vice versa. These days, it’s not uncommon to see these two open source tools used together in the wild. And for good reason. F5, which acquired NGINX last year, is prioritizing building visibility across the entire product set, to make it easy for customers to quickly gain the insights that they need. Meanwhile, Grafana has evolved into the primary visualization and analysis tool in the open source market.

Most web apps can benefit from a background queue, often used to process error-prone or time-consuming side jobs. These background jobs can vary from sending emails, to updating caches, to performing core business logic. As any background queueing system scales the number of jobs it needs to process, the pool of workers processing those jobs needs to scale as well.

In our latest two-part series blog, Gigi Sayfan, author of “Mastering Kubernetes”, discusses managing complex infrastructure on AWS with an eye towards SLOs (service level objectives). Though there are many ways to discuss the management of infrastructure, in this two-part series, he covers SLOs for AWS, Observability on AWS, Quotas Limits, and Optimizing cost on AWS and in the second part, he uses the lens of Kubernetes to compare and contrast compute infrastructure on AWS with Kubernetes.

Rancher and SAP have been working on a dedicated verification of SAP Data Intelligence 3 (SAP DI) on Rancher Kubernetes Engine (RKE) cluster and Longhorn storage platform. This blog will guide you on how to properly install SAP DI on an RKE cluster.

I’m excited to announce that Rancher has signed a definitive agreement to be acquired by SUSE. Rancher is the most widely used enterprise Kubernetes platform. SUSE is the largest independent open source software company and a leader in enterprise Linux. By combining Rancher and SUSE, we not only gain massive engineering resources to further strengthen our market-leading product, we are also able to preserve our unique 100% open source business model.

Talking about competition can be hard. It’s understandable. Product positioning can be touchy subjects especially when those use cases overlap. In the DevOps space, event-driven architectures are certainly not a new concept. Companies like Netflix, LinkedIn, and Facebook have in-house tools built specifically for this type of automation. However, Relay’s mission is make it easy for everyone to build event-driven workflows – not the Netflix-es of the world.

Over the past two decades, two trends have completely reshaped the IT landscape: cloud computing and microservices. With cloud computing, organizations of all sizes can provision infrastructure and run applications on a global scale within minutes. And with microservices, these organizations can deploy highly scalable distributed workloads just as quickly.

The movies are filthy with examples of artificial intelligence. Some, like the first Terminator, are evil. Some, like the Star Wars droids, work for the good guys. And so many of them are flatly iconic—Blade Runner (both of them), 2001: A Space Odyssey, War Games, Westworld (the movie and the HBO series), Matrix[i] … the list keeps going and going. We aren’t at the point yet when we can get R2 to talk the Millennium Falcon—or the data center—and find out what’s wrong.