Those who work with NewRelic logs for Java applications probably know that the user of an agent might be the most flexible and convenient way to collect log data and gather different application metrics, like CPU and memory usage and execution time. However, to run a Java application with the agent, we need access to an application execution unit (like a jar or Docker image) and control an execution runtime (e.g., an image with JVM on Kubernetes). Having such access, we can set up Java command line arguments, including necessary configurations for the agent.

Though, Azure Cloud-managed services, such as Azure Data Factory (ADF) or Logic Apps, do not have “tangible” executed artifacts nor execution environments. Such services are fully managed, and their execution runtimes are virtual. For these services, Azure suggests using Insights and Monitor to collect logs, metrics, and events to create alerts. But if your company has a separate solution for centralized log collection, like NewRelic, it could be a challenge to integrate managed services with an external logging framework.

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