About Metrics

In the simplest of terms, a metric is something that can be measured or quantified. It can be a physical item, such as the number of users who perform a specific action. It can also be data related to system performance, such as transactions latency, bandwidth, CPU, temperature, or data related to business activities, such as the number of purchases measured by the time of day, the day of the week, etc. Business metrics might include the number of users who log in during a specific period of time, or the amount of time a user spends on a page or using an application. Typically, a metric can change over time so that what is normal on one day of the week or at certain hours will be different when measured on another day or at another time.

Every organization can generate metrics that can be monitored over a period of time to create a recognizable pattern. When studying that pattern, an overall level of consistent behavior can be mapped.

In reality, organizations can literally have hundreds of thousands of metrics that can be grouped together to identify not just when the overall organization if functioning properly, but when something unexpected and potentially dangerous occurs.

Monitoring metrics is important because it allows you to quantify elements of your organization, website, business, or operation and then determine when there is an inconsistency, an anomaly. Identifying the anomaly is the first step to fixing a potential problem to get the application or service back up to running as expected.

Some of the real-world uses you will find for visualizing your metrics are:

  • Measuring the number of users clicking on an ad.
  • Investigating influences in changed ecommerce returns.
  • Viewing average user time on page.

Example:

An online banking system uses Anodot to monitor transactions such as number of users, number of transfers, amounts transferred regularly, and many other standard functions.

Their metrics stream would include:

# of Users

# of transfers

Average transfer amounts

# Successes/failures rates of transactions 

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