Even a medium-sized website can be extremely complex. Django might be one of the hundreds of applications and services running and interacting with each other. In the same way that the heartbeat and other vital signs can be constantly monitored to assess the health of the human body, so are various metrics collected, analyzed, and presented in most production systems.

While logging keeps track of various events, such as the arrival of a web request or an exception, monitoring usually refers to collecting key information periodically, such as memory utilization, or network latency. However, differences get blurred at the application level, for example, while monitoring database query performance, which might very well be collected from logs.

Monitoring also helps with the early detection of problems. Unusual patterns, such as spikes or a gradually increasing load, can be signs of bigger underlying problems, such as memory leak. A good monitoring system can alert site owners of problems before they happen.

Monitoring tools usually need a backend service (sometimes called agents) to collect the statistics and frontend service to display dashboards or generate reports. Popular data collection backends include StatsD and Monit. This data can be passed to frontend tools, such as Graphite.

There are several hosted monitoring tools, such as New Relic and Status.io, which are easier to set up and use.

Measuring performance is another important role of monitoring. As we will soon see in a later section, any proposed optimization must be carefully measured and monitored before getting implemented.