At Logentries, we feel strongly about the power of log data and the unparalleled role that logs can play in effective end-to-end system monitoring. Yet we feel it also important to recognize how other monitoring approaches can further supplement a log monitoring solution to provide even greater, actionable insight into system performance. One such approach is Application Performance Management (APM) and today we’re excited to announce our first APM Community Pack.
While log data provides a more comprehensive overview of system health than traditional Application Performance Management, an APM tool can offer insights into an issue’s root cause at the code level. Logentries’ new APM Community Pack leverages a new extension recently added to our Python library that gives developers the ability to calculate important metrics related to any function they choose to measure.
Using the Logentries’ new APM Community helps to easily analyze the effect of function execution on overall system performance.
Using the new Pack, developers can do things like identify low performing functions, reveal memory leaks and monitor remaining system resources.
With this new level of insight, developers can spend less time searching for answers and more time writing good, clean code.
The recent APM updates to our Python library also enable users to extend the functionality of the library. For example, a developer could now decide to add network or disk statistics to their logs and measure network load generation by function. Developers could also create a counter to measure the number of method calls over time.
The Logentries Python APM Community Pack is available for free and takes only seconds to install. Visit community.logentries.com/packs/python to get started today.