Operations | Monitoring | ITSM | DevOps | Cloud

It’s a metaphor that would have been impossible to decode even a decade ago: a Command and Control environment where essential data flows as quickly and intuitively as a map on Uber or Lyft. It’s a way of imagining efficient access to up-to-the-minute mission-relevant information, so that any sensor can make useful intelligence available to any device or effect, on a single screen, in time to make a difference.

When the coronavirus pandemic hit Asia-Pacific back in January, no one knew what to expect. As the first region to grapple with the questions and uncertainties that the virus presented, leaders had to process the new reality and spring into action at record speed. While navigating the shifting landscape has been a unique journey for all organizations, a few things have proven to be consistent.

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.

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.

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.

IT professionals are now adapting to a remote environment and learning to manage a distributed, homebound workforce. From a technical standpoint, the process of setting up a remote workforce is well-known. For this blog post let’s dive into one step of the process, which is arguably the most important, user experience monitoring.