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An Introduction to Microsoft Azure Anomaly Detection Service
What is Anomaly Detection?
Anomaly detection is the process of finding the outliers of a dataset, which are the items that do not belong. These anomalies might highlight unusual network traffic, simplify identify data for cleaning, or unveil a sensor on the fritz, prior to analysis. In simple words, it is a process of finding an unusual point or pattern in a dataset. Anomaly is also referred to as outlier. It is a part of the data cleansing process.
In today’s world of distributed systems, tracking and monitoring the performance of a system is a necessity. With several thousand things to watch, anomaly detection can help figure out where the error is occurring, thereby improving root cause analysis and quickly bringing notice to tech support. Anomaly detection helps track and identify the root cause of chaos engineering by identifying the outliers and informing the tech support to act.
Anomaly detection is mainly used in enterprise IT for:
- Intrusion Detection
- Ecosystem Disturbances
- Data Cleansing
- Event Detection in Sensor Networks
- Fraud Detection
