What is Amazon Lookout for Metrics? - Amazon Lookout for Metrics

What is Amazon Lookout for Metrics?

Amazon Lookout for Metrics is a service that finds anomalies in your data, determines their root causes, and enables you to quickly take action. Built from the same technology used by Amazon.com, Amazon Lookout for Metrics reflects 20 years of expertise in anomaly detection and machine learning.

In Lookout for Metrics, you create detectors that monitor data to find anomalies. You configure the detector with a datasource and choose the values that it monitors (the dataset's measures). The detector can monitor all values of a measure overall, or use other data to sort measures into groups. For example, you can choose to monitor the availability of an application worldwide, or use a location field in your data as a dimension to monitor availability separately in each AWS Region or Availability Zone. Each combination of measure and dimension value is called a metric.

To gain an understanding of your data and better find anomalies, a detector uses your data to learn. When you create a detector, you choose an interval from between 5 minutes and 1 day, which determines how often the detector imports data and finds anomalies. Depending on the interval that you choose, a detector spends between a few hours and a few days learning about your data. To speed up the learning process, you can provide historical data. You can also use historical data to run a detector in backtest mode to see how well it works on your data.

When Lookout for Metrics finds an anomaly, it gives it a severity score to indicate how unexpected it is, based on the detector's understanding of your data. When multiple metrics are affected by an anomaly, the detector collects them in a group. To send anomaly alerts when high severity anomalies occur, you can add alerts to the detector. Alerts can run a Lambda function or send a notification to an Amazon SNS topic. Anomaly alerts summarize all affected metrics for an anomaly, which reduces the amount of similar alerts that it sends.

Lookout for Metrics can monitor data from many different domains, stored in many different formats. In addition to monitoring operational metrics for emergent issues, you can find anomalies in sales data, marketing data, and customer engagement metrics.

Lookout for Metrics integrates with other services to provide additional datasources and alert channels. Lookout for Metrics supports the following services as datasources.

  • Amazon S3 – Read metrics data from text objects in a bucket. Supports using historical data for training and testing a detector.

  • Amazon CloudWatch – Analyze CloudWatch metrics sent by an AWS service, AWS resource, or an application.

  • Amazon Relational Database Service (Amazon RDS) – Analyze items in a relational database. The following database engines are supported:

    • Amazon Aurora

    • MySQL

    • PostgreSQL

    • MariaDB

    • Microsoft SQL Server

  • Amazon Redshift – Analyze items in a Amazon Redshift data warehouse.

  • Amazon AppFlow – Analyze data flow from a web service with an Amazon AppFlow data flow. The following services are supported:

    • Salesforce

    • Marketo

    • Dynatrace

    • Singular

    • Zendesk

    • Servicenow

    • Infor Nexus

    • Trendmicro

    • Veeva

    • Google Analytics

    • Amplitude

To get started with Lookout for Metrics and learn more about the service, continue to Getting started with Lookout for Metrics.

Are You a First-Time User of Lookout for Metrics?

If you are a first-time user of Lookout for Metrics, we recommend that you start with the following pages:

  1. Getting started –Get started with Lookout for Metrics.

  2. Key terms and concepts – Learn about the key terms and concepts of Lookout for Metrics.

  3. API reference – Familiarize yourself with the Lookout for Metrics API actions and data types.