In this blog I will show some best practices for instrumenting Docker containers, using docker-compose with a few popular AppDynamics application agent types. The goal here is to avoid rebuilding your application containers in the event of an agent upgrade, or having to hard-code AppDynamics configuration into your container images. In my role as a DevOps engineer working on AppDynamics’ production environments, I use these techniques to simplify our instrumented container deployments.

At AppDynamics, we are firm believers in demonstrating the value of our platform as quickly as possible. Many of our customers are able to address critical performance issues within minutes of getting their application instrumented. Below is an example of how we use AppDynamics with a fictional customer, AD-Betting, to analyze and troubleshoot the company’s business environment soon after AppD is up and running.

New users of APM software often believe their company has hundreds of critical business transactions that must be monitored. But that’s not the case. In my role as Professional Services Consultant (EMEA) at AppDynamics, I’ve worked at dozens of customer sites, and the question of “What to monitor?” is always foremost in new users’ minds.

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.