IoT is slowly, quietly taking over the world. A few years ago, self-ordering fridges, driverless cars, and fully automated homes seemed like the stuff of dreams. And while the technology exists, rollout and adoption is slower than anticipated, amidst security and privacy concerns. That said, IoT is the future, and growth is steady, as the challenges of building and maintaining hundreds of thousands of devices per vendor are getting solved.

With the economies of many countries heading towards recession, increasing regulations, growing security threats and increasing costs, financial services firms need practical solutions, now more than ever. Many of the financial technology firms (‘fintechs’) and mobile app-based challenger banks have taken advantage of modern application architectures and DevOps practices that are associated with cloud native technologies.

If you want to put yourself ahead of your competition, you must improve and lower operating costs as much as possible. And, as business owners, you should always be on the lookout for ways to reduce the operating costs without sacrificing the quality of your offering. The same is true with legacy apps! I guess it’s on the higher side for legacy apps because they are not only outdated but can also hamper innovation at all fronts.

Since 2018, Watchdog has provided automatic anomaly detection to notify you of performance issues in your applications. Earlier this year, we introduced Watchdog for Infra, enhancing Watchdog to also monitor your infrastructure. We’re pleased to announce the latest enhancements to Watchdog, which now provides more visibility and greater context around the full scope of each application issue.

As part of Rancher 2.5, we are excited to introduce a new, simpler way to install Rancher called RancherD. RancherD is a single binary you can launch on a host to bring up a Kubernetes cluster bundled with a deployment of Rancher itself. This means you just have one thing to manage: RancherD. Configuration and upgrading are no longer two-step processes where you first have to deal with the underlying Kubernetes cluster and then deal with the Rancher deployment.

Amazon EKS is the most popular managed Kubernetes solution. DevOps teams can quickly spin up clusters in the cloud and get started with Kubernetes in a few clicks. As organizations embrace Kubernetes in the cloud, the challenge becomes managing clusters across multiple regions or accounts. At that point, organizations struggle to visualize all of their clusters.

Despite the lockdown restrictions of the last six months, I'm delighted to announce that we've released Rancher 2.5 on schedule today. This latest release represents another major milestone of Rancher's "Computing Everywhere" strategy by delivering management capabilities that match the extraordinary popularity of Amazon EKS and our lightweight Kubernetes distribution, K3s.

The ability of Kubernetes to easily deploy and manage containerized software has given organizations tremendous capabilities in their cloud services, with clusters multiplying into the hundreds or thousands and extending out to the edge for any number of purposes. But its growing popularity has also led to challenges in managing complexity in an environment that is conducive to cluster sprawl.

In this article, you will learn how to add inline image scanning to a Google Cloud Build pipeline using the Sysdig Secure DevOps platform. We will show you how to create a basic workflow to build your container image, scan the image, and push it to a registry. We will also customize scanning policies to stop the build if a high-risk vulnerability is detected.

In a recently published Network World article, "How to Consolidate Network Management Tools," the author wrote about how "enterprise IT shops are getting serious about winnowing the tools they use for network capacity planning, monitoring, event correlation, configuration management and more." In the article, the key problem statement was offered by industry analyst firm EMA: "The problem is that having a patchwork of multiple, siloed tools can be expensive and leads to ‘fragmented workloads, ineffi