This blog post describes the basics of time series analysis in Azure Data Explorer.
Azure Data Explorer (ADX) is a service designed for fast data exploration. It provides instant insights into large datasets to analyze performance, identify trends and anomalies, and troubleshoot problems.
The collection of telemetry data is performed from cloud services or IoT devices. The analysis can be performed on sets of time series for selected metrics to find a deviation in the pattern of the metrics relative to their typical baseline patterns.
ADX provides native support for the creation, editing, and analysis of time series in near real-time.
First, the original telemetry table is partitioned and transformed to a set of time series using the make-series operator. ADX provides then the following capabilities for the analysis:
The complete set of functions for the time series analysis is available in the Microsoft documentation section.
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The following time series analysis discovers periodic patterns and decreasing trends with series_periods_detect and series_fit_line functions:
In the above query 18,339 time series of web service traffic are analyzed and extracted with a periodic pattern.