On October 7, 2026, AWS will discontinue support for Amazon Lookout for Equipment. After October 7, 2026, you will no longer be able to access the Lookout for Equipment console or resources. For more information, [see the following](https://aws.amazon.com/blogs/machine-learning/preserve-access-and-explore-alternatives-for-amazon-lookout-for-equipment/). 

# Monitoring Amazon Lookout for Equipment
<a name="monitoring-overview"></a>

Monitoring is an important part of maintaining the reliability, availability, and performance of Lookout for Equipment and your other Amazon Web Services solutions. Amazon Web Services provides the following monitoring tools to watch Lookout for Equipment, report when something is wrong, and take automatic actions when appropriate:
+ *Amazon CloudWatch* monitors your AWS resources and the applications you run on AWS in real time. You can collect and track metrics, create customized dashboards, and set alarms that notify you or take actions when a specified metric reaches a threshold that you specify. For example, you can have CloudWatch track CPU usage or other metrics of your Amazon EC2 instances and automatically launch new instances when needed. For more information, see the [Amazon CloudWatch User Guide](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/).
+ *Amazon CloudWatch Logs* enables you to monitor, store, and access your log files from Amazon EC2 instances, CloudTrail, and other sources. CloudWatch Logs can monitor information in the log files and notify you when certain thresholds are met. You can also archive your log data in highly durable storage. For more information, see the [Amazon CloudWatch Logs User Guide](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/).
+ *AWS CloudTrail* captures API calls and related events made by or on behalf of your AWS account and delivers the log files to an Amazon S3 bucket that you specify. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred. For more information, see the [AWS CloudTrail User Guide](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/).

*Amazon EventBridge* is a serverless event bus service that makes it easy to connect your applications with data from a variety of sources. EventBridge delivers a stream of real-time data from your own applications, Software-as-a-Service (SaaS) applications, and AWS services and routes that data to targets such as Lambda. This enables you to monitor events that happen in services, and build event-driven architectures. For more information, see the [Amazon EventBridge User Guide](https://docs.aws.amazon.com/eventbridge/latest/userguide/).

# Monitoring Lookout for Equipment with Amazon CloudWatch
<a name="monitoring-cloudwatch"></a>

You can monitor Lookout for Equipment using CloudWatch, which collects raw data and processes it into readable, near real-time metrics. These statistics are kept for 15 months, so that you can access historical information and gain a better perspective on how your web application or service is performing. You can also set alarms that watch for certain thresholds, and send notifications or take actions when those thresholds are met. For more information, see the [Amazon CloudWatch User Guide](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/).

The Lookout for Equipment service reports the following metrics in the `AWS/lookoutequipment` namespace.


| Metric | Description | 
| --- | --- | 
|  `InferenceSucceeded`  |  If the value is `1`, the inference succeeded. If the value is `0`, the inference failed. ModelName: The name of the model. InferenceSchedulerName: Name of the inference scheduler  | 
|  `InferenceFailed`  |  If the value is `1`, the inference failed. If the value is `0`, the inference succeeded. ModelName: The name of the model. InferenceSchedulerName: Name of the inference scheduler  | 
|  `InferenceInvalidInput`  |  If the value is `1`, you've provided an invalid value for the inference. ModelName: The name of the model. InferenceSchedulerName: Name of the inference scheduler  | 

The following dimensions are supported for the Lookout for Equipment metrics.


|  ModelName  |  The name of the ML model that you've trained to monitor your equipment.  | 
| --- | --- | 
|  InferenceSchedulerName  |  The inference scheduler schedules the times when your model monitors your equipment.  |