Ready to deploy an AppD application agent to OpenShift? These detailed examples show you how. There are several ways to instrument an application on OpenShift with an AppDynamics application agent. The most straightforward way is to embed the agent into the main application image.
In an earlier blog in our series on monitoring applications deployed to the Pivotal Cloud Foundry (PCF) platform, my colleague Jeff Holmes described how AppDynamics provides an intuitive and user-friendly dashboard for a single view of all your key performance indicators for system health and availability. This broke new ground and has been warmly welcomed by our many customers who rely on PCF to run their business applications.
Kubernetes and OpenShift are powerful and flexible. They’re also complex to setup, monitor and maintain at scale. Here’s a sneak peek into what we monitor in OpenShift, as well as some hard-earned advice on how our strategy might benefit your own environments.
Here’s how AppDynamics enabled a large investment bank to improve system performance, track trades in real time, search for trade IDs to quickly find the root cause of issues, and proactively manage SLAs.
Serverless or Function-as-a-Service (FaaS) design patterns have been picking up steam. With the recent release of KNative from Google Cloud, let’s take a closer look at the serverless movement.
Business leaders have lost faith in IT, which must reinvent itself as a leader driving innovation. By implementing a valuable, new technological shift with the right tools in place, IT can become a key business partner with groundbreaking ideas that drive success.
Total visibility is crucial to monitoring the database environments that support your most critical applications. That’s why AppDynamics recently released a number of updates to our Database Visibility functionality. Not only do we now support monitoring Couchbase, but we also added snapshot correlation, support for custom cluster configuration, and enhancements to our ability to collect and track custom database metrics.
Serverless compute services such as AWS Lambda offer many advantages to their customers, most notably the ability to reduce costs and minimise infrastructure. But serverless can also bring trade-offs that give rise to application performance issues.
Everybody uses third-party code. It saves time and money, increases agility, and lets you leverage the domain expertise of developers outside your company. But how do you monitor it?
