Introducing Logentries’ Python APM Community Pack

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News: Introducing Logentries’ Python APM Community Pack

  1. 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 librarythat 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.

     

    https://blog.logentries.com/2015/08/apm-community-pack/

     

  2. http://www.autoletics.com/posts/beyond-metrics-logging-metered-software-memories

    In this article I propose a different approach to application performance monitoring that is far more efficient, effective, extensible and eventual than traditional legacy approaches based on metrics and event logging. Instead of seeing logging and metrics as primary datasources for monitoring solutions we should instead see them as a form of human inquiry over some software execution behavior that is happening or has happened. With this is mind it becomes clear that logging and metrics do not serve as a complete, contextual and comprehensive representation of software execution behavior.