Nonlinear time series are generated by nonlinear dynamic equations. nonlinear time series dataĪ linear time series is one where, for each data point X t, that data point can be viewed as a linear combination of past or future values or differences. Common data examples could be anything from heart rate to the unit price of store goods.
The goal of tracing is to follow a program’s flow and data progression.
Over the colored bands in the traces chart below, you can see examples of time series data. Traces (a list of the subroutine calls that an application performs during execution) are also time series data. For example, in networking, an event log helps provide information about network traffic, usage and other conditions. Log data is an important contextual source to triage and resolve issues. Every executable file produces a log file where all activities are noted.
DEFINE GRAPHICAL ANALYSIS SOFTWARE
Logs are a registry of events, processes, messages and communication between software applications and the operating system. In addition to being captured at regular time intervals, time series data can be captured whenever it happens - regardless of the time interval, such as in logs. Remember that monitoring data is time series data.Īnother familiar example of time series data is patient health monitoring, such as in an electrocardiogram (ECG), which monitors the heart’s activity to show whether it is working normally. The cluster monitoring example below, depicting disk ops write and usage data, would be familiar to Network Operation Center teams.
This can be tracked over the short term (such as a security’s price on the hour over the course of a business day) or the long term (such as a security’s price at close on the last day of every month over the course of five years). In investing, a time series tracks the movement of data points, such as a security’s price over a specified period of time with data points recorded at regular intervals. In the next chart below, note time as the axis over which stock price changes are measured. Notice how time - depicted at the bottom of the below chart - is the axis. The best way to understand time series is to start exploring with some sample data in InfluxDB Cloud. Time series data could also be server metrics, application performance monitoring, network data, sensor data, events, clicks and many other types of analytics data. Weather records, economic indicators and patient health evolution metrics - all are time series data.
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