Skip to main content
Amazon Lookout for Equipment is no longer available to new customers as of October 17, 2024. For alternatives we recommend exploring our blog post.

Amazon Lookout for Equipment Resources

Amazon Lookout for Equipment uses industrial data from your equipment to detect potential failures so you can take action, such as performing maintenance before a breakdown, to avoid unplanned downtime.

Documentation

User guide

The user guide provides a conceptual overview of Amazon Lookout for Equipment, offers detailed instructions for using various features, and includes a complete API reference for developers.</p><p><a href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/amazon-lookout-for-equipment-ug.pdf">PDF</a></p>

HTML

Getting started sample

This getting started sample can be used to develop hands-on experience on how to query the Amazon Lookout for Equipment API. Use this content to get started with ingesting data, building models, and building nice visualizations to review your model results.

GitHub

Getting started with Lookout for Equipment console 

This getting started focuses solely on the Lookout for Equipment console. This will walk you through an end-to-end journey using Lookout for Equipment from ingesting the data to deploying an anomaly detection model. All of this, without writing a single line of code!

GitHub

Amazon CloudWatch Custom Widgets dashboard

Do you need non-developers to review your model and inference results? What about using CloudWatch custom widgets to build beautiful dashboards for any internal user? This repo comes with a CloudFormation template you just need to deploy before following this Read Me note.

GitHub

Python SDK

Dedicated to Python developers, the Amazon Lookout for Equipment Python SDK is an open-source library that allows data scientists and software developers to build, train, and deploy anomaly detection models for industrial time-series data using Amazon Lookout for Equipment. This library, available from the PyPI package repository, allows you to ingest data, train models, and display beautiful visualization you can incorporate with a few Python lines of code. Read the full documentation and check out a short example illustrated in a concise notebook.

Documentation

Lookout for Equipment demo

The AWS Samples GitHub repository for Amazon Lookout for Equipment contains examples illustrating how you can start building your anomaly detection application for your industrial assets. The examples are in Jupyter notebooks and contain detailed commentaries and explanations, making it easy to understand how to use the service. They include step-by-step guidance for configuring the Boto3 API for Lookout for Equipment and invoking various APIs for preparing the data, creating a dataset, training a model, evaluating a model, and scheduling an inferencer. You can also find helper functions for visualizing your time-series data.

GitHub

Lookout for Equipment Installation Instructions

Lookout for Equipment Installation Instructions The Lookout for Equipment Web App is an application you can deploy in your own account with a simple CloudFormation template. This application will help you assess quickly if your industrial data contains any historical anomaly of interest. After you upload a dataset containing sensor measurements from your industrial equipment or manufacturing process, the app will guide you to train an anomaly detection model. You will then be able to visualize your model results and deploy it, making it ready to receive your shop floor live data. This application also includes an operational dashboard to visualize your live results.

GitHub

Videos

Choose the cloud provider with proven experience in industrial operations

From accelerating design to optimizing operations to reinventing supply chains, AWS helps leading industrial customers transform their business with the most comprehensive set of cloud services and solutions, and an extensive partner network, while taking advantage of the highest standards for privacy and data security. Learn about how Volkswagen Group, Carrier, INVISTA, Vector and Georgia-Pacific are all building on AWS.
Learn more about AWS for Industrial »

Choose the cloud provider with proven experience in industrial operations

From accelerating design to optimizing operations to reinventing supply chains, AWS helps leading industrial customers transform their business with the most comprehensive set of cloud services and solutions, and an extensive partner network, while taking advantage of the highest standards for privacy and data security. Learn about how Volkswagen Group, Carrier, INVISTA, Vector and Georgia-Pacific are all building on AWS.

"Volkswagen logo with text in black."
Carrier logo with white text inside a blue oval.
The official logo of Invista, featuring a stylized icon and the word 'INVISTA' in uppercase letters.
Logo featuring a stylized 'V' with a blue to green gradient design next to the word 'vector' in dark blue text, on a transparent background.
"Georgia-Pacific logo with 'GP' inside a blue triangle."