Top 3 gotchas in AWS, and how network observability helps you avoid them As you transition apps and services to the cloud, whether fully public or hybrid, the networking component quickly gets complicated. Your team not only has to manage on-premises networking, but also cloud networks now - which requires a different approach to handle things like VPCs and connectivity back to on-prem environments and other clouds. Poor performance and high costs can quickly hinder cloud projects from being successful.

It's easy to get caught flat-footed on things like collecting logs and metrics at cloud-scale, making sense of cloud network performance and health using old-school data like port numbers and IP addresses, and automating processes like troubleshooting and remediation when you don't own the underlying infrastructure.

This eBook contains 7 tips to help you run your data center smoothly and effortlessly scale while minimizing incidents and operational costs.

This white paper discusses some inherent issues in current AIOps tools and how preventive healing systems are bridging the gaps left by them. Why AIOps tools are not enough How preventive healing systems fill in the gap

SAP creates some of the world's most popular products for managing information, with more than 400 million users worldwide. But SAP connectivity presents one of the biggest security risks for your company. In this ebook, we will consider some of the steps you can take to secure your SAP systems: we'll explore how SAP systems can be compromised, plus we will investigate some of the ways to prevent this from happening.

Running SAP systems in the cloud can provide a litany of benefits to users at every level of the organization. However, many hidden, unexpected and expensive challenges can quickly arise before, during and after migrating mission-critical SAP systems to the cloud. In this white paper you'll discover the three main challenges plaguing both Enterprise IT operations and Managed Service Providers (MSPs) today, and learn how to overcome them.

Big data stacks are being moved to the cloud, enabling enterprises to get the most value from the information they own. But as demand for big data grows, enterprises must enhance the performance of their cloud assets. Faced with the complexity of cloud environments, most enterprises resort to scaling up their whole cloud infrastructure, adding more compute, and running more processes.

There has been an ongoing surge of companies beginning to run Spark on Kubernetes. In our recently published 2021 Big Data on Kubernetes Report, we discovered that 63% of today's enterprises are running Spark on Kubernetes. The same report found that nearly 80% of organizations embrace Kubernetes to optimize the utilization of compute resources and reduce their cloud expenses. However, running Spark on Kubernetes is not without complications and problems.