Amazon Machine Learning

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Overview

AWS Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology.

Enable this integration to see in Datadog all your Machine Learning metrics.

Setup

Installation

If you haven’t already, set up the Amazon Web Services integration first.

Metric collection

  1. In the AWS integration page, ensure that ML is enabled under the Metric Collection tab.
  2. Install the Datadog - AWS Machine Learning integration.

Log collection

Enable logging

Configure AWS Machine Learning to send logs either to a S3 bucket or to CloudWatch.

Note: If you log to a S3 bucket, make sure that amazon_machine_learning is set as Target prefix.

Send logs to Datadog

  1. If you haven’t already, set up the Datadog Forwarder Lambda function.

  2. Once the Lambda function is installed, manually add a trigger on the S3 bucket or CloudWatch log group that contains your AWS Machine Learning logs in the AWS console:

Data Collected

Metrics

aws.ml.predict_count
(count)		The number of observations received by Amazon ML.
aws.ml.predict_failure_count
(count)		The number of invalid or malformed observations received by Amazon ML.

Each of the metrics retrieved from AWS are assigned the same tags that appear in the AWS console, including but not limited to host name, security-groups, and more.

Events

The AWS Machine Learning integration does not include any events.

Service Checks

The AWS Machine Learning integration does not include any service checks.

Troubleshooting

Need help? Contact Datadog support.

Further reading

Más enlaces, artículos y documentación útiles:

Best practices for monitoring ML models in productionBLOG more more