By now, most of us know that migrating workloads to the cloud isn’t like simply moving software from one server to another—especially in a complex enterprise infrastructure with many interdependent services and components. There are a lot of things that can go wrong: technical public cloud provisioning issues, security and compliance challenges, lack of cloud skills, wrong public cloud service provider (CSP) selection, unexpected costs, and more.
The phone rings. Your email pings. Your marketing team just told you about a flood of messages on social media and through live chat that there’s a service outage. You thought your Monday morning would be calm and relaxed since people are just returning from the weekend. How do you start researching all of these incoming tickets? How do you know which ones to handle first? Is this just a hardware failure, or are you about to embark on a security incident investigation like Log4j?
For DevOps teams, delivering quality software has long required reconciling a major tension: In a perfect world, you’d catch every issue in each new release of your application before you deployed the release into production. But in the real world, doing so is tricky, not least because it’s hard to collect data about application performance before the application is actually deployed.
In the present age of cloud-native everything, it can be easy to forget that some applications still run on-premises. But they do and managing the performance of on-premises apps is just as important as monitoring those that run in the cloud. With that reality in mind, here’s a primer on how to approach on-premises application performance monitoring as part of a broader cloud-native performance optimization strategy.
One of the first things you’ll learn when you start managing application performance in Kubernetes is that doing so is, in a word, complicated. No matter how well you’ve mastered performance monitoring for conventional applications, it’s easy to find yourself lost inside a Kubernetes cluster.
