Flowmon APM collects information for all users and user transactions at any given moment. It tracks interactions between users and application servers as well as application and database servers.

The collected metrics are then correlated and provide information about which element along the application delivery chain is causing delays and where bottlenecks may lie.

The main performance metrics are Application Response Time measuring the delay caused by the application and Transport Time which represents a delay introduced on the network level.

Network and application delay metrics

• Application Response Time (ART) - Time difference between the last packet of the request (from client to server) and the first packet of the response (from server to client).  Request and response refer to transactions on the application layer.
• Transport Time (TT) - Time difference between the first and last packet of the request (in case of client-to-server communication) or the first and last packet of the response (in case of server-to-client communication). Request and response refer to transactions on the application layer.

The data is expanded by additional transaction details such as the full SQL statement and full URLs, as well as size, IP address, session ID, username, browser information and server status code. This provides plenty of information for troubleshooting and optimization.

The system computes one main metric, which is the APM index. It is derived from the Application Response Time for all transactions and expresses the fulfilment of the user-defined SLA as a percentage score. It’s a quick and easy way to get a global view of the application’s performance and to know when the SLA is not being met. Additional metrics are available, including response time of 99% and 95% from the transactions, median as well as multitudes of SLAs.

Flowmon APM contains the Transaction Generator, which simulates user behavior and reports on SLA. Its main purpose is the automated testing of business-critical HTTP and HTTPS applications.

The module executes a set of test scenarios (Selenium) over defined time plans. The outcome is an SLA report (availability), scenario result (success/failure), and more data to provide an excellent early-warning system that works in off-peak times.

All this information is displayed on the dashboard - a highly customizable information space with detailed widgets and drill-down options all in a single view. Different dashboards can be created for each application or user, complete with adjustable user permissions.

The dashboard also features alerting capabilities and the option to set up regular reports to always stay informed on application status and degradations.