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monitors-overview.mdx

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title Anomaly Detection Monitors
sidebarTitle Monitors overview

import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx'; import AutomatedMonitorsIntro from '/snippets/cloud/features/anomaly-detection/automated-monitors-intro.mdx'; import AutomatedMonitorsCards from '/snippets/cloud/features/anomaly-detection/automated-monitors-cards.mdx';

ML-powered anomaly detection monitors automatically identify outliers and unexpected patterns in your data. These are useful to detect issues such as incomplete data, delays, a drop in a specific dimension or a spike in null values.

Elementary offers two types of monitors:

  • Automated Monitors - Out-of-the-box monitors activated automatically, that query metadata only.
  • Opt-in Monitors - Monitors that query raw data and require configuration.

Automated monitors

Opt-in monitors

Coming soon

Monitor test results

Each monitor returns a test result, that is one of the following four results:

  • Passed - The test passed, no anomaly was detected.
  • Warning - An anomaly was detected, and the test is configured to warn severity.
  • Fail - An anomaly was detected, and the test is configured to fail severity.
  • No data - The monitor does not have enough data or an accurate model to monitor. Reach out to our support team to fix this.