AWS IoT Analytics Discontinuedsince 2017
[Ended Dec 15, 2025] Managed service that collected, processed, and analyzed IoT device data. AWS officially recommends migrating to Kinesis, S3, Timestream for InfluxDB, and Athena
What It Does
[Discontinued] AWS IoT Analytics reached end of support on December 15, 2025. The following describes the service as it worked at the time. AWS IoT Analytics is a managed service for collecting, processing, storing, and analyzing the massive volumes of message data sent from IoT devices. It automatically processes data filtering, transformation, and enrichment (joining with external data) through pipelines and stores the results in an analytics data store. You can run ad-hoc analysis with SQL queries or perform advanced analysis using Jupyter Notebooks.
Use Cases
Used for trend analysis of sensor data from factory production lines, optimization analysis of HVAC and lighting data in smart buildings, statistical processing of soil and weather data in agricultural IoT, and driving pattern analysis of vehicle telematics data.
Everyday Analogy
Think of it like a factory's quality control department. It receives inspection data from each stage of the production line, removes unnecessary data, cross-references it against baseline values, and generates analysis reports. It automates the work of extracting meaningful information from mountains of raw data.
End of Support and Migration Paths
AWS IoT Analytics reached its end of support on December 15, 2025, and had stopped accepting new customers in July 2024. The console and service resources are no longer accessible. The official AWS migration guide maps each capability to alternative services: Amazon Kinesis Data Streams or Amazon Data Firehose for data collection, Amazon Managed Service for Apache Flink or Data Firehose with Lambda for processing, Amazon S3 or Amazon Timestream for InfluxDB for storage, and AWS Glue with Amazon Athena for analysis. This page remains available as a historical reference and migration guide.
What Is AWS IoT Analytics?
AWS IoT Analytics is a service for efficiently analyzing the large volumes of data generated by IoT devices. IoT devices send a wide variety of data at high frequency - temperature, humidity, vibration, location, and more. This raw data often contains noise and missing values, making it unsuitable for analysis as-is. IoT Analytics provides an end-to-end pipeline from data collection to cleansing, transformation, storage, and analysis, making it easy to put IoT data to work.
Data Processing with Pipelines
IoT Analytics pipelines let you apply multiple processing steps to messages received through channels (data entry points). You can remove unnecessary fields, convert data types, fill in missing values, apply custom transformations using Lambda functions, and join with external data from DynamoDB or S3 (enrichment). Processed data is stored in a data store and can be analyzed with SQL queries. Since data can be sent directly from IoT Core's rule engine, integration with devices is straightforward.
Analysis and Visualization
Data stored in the data store can be extracted as datasets using SQL queries. Datasets support scheduled execution, enabling automatic generation of daily or hourly reports. Additionally, a managed Jupyter Notebook environment is integrated, allowing you to perform statistical analysis and build machine learning models using Python. Analysis results can be visualized on dashboards by integrating with QuickSight.
Things to Watch Out For
- Support ended on December 15, 2025. The console, APIs, and stored data are no longer accessible; workloads that were not migrated must be rebuilt on the alternative stack (Kinesis Data Streams / Data Firehose + S3 / Timestream for InfluxDB + Glue / Athena)
- New customer sign-ups closed in July 2024. This page is kept as a historical reference to support migration decisions
References (Official AWS Resources)
The primary sources for this page are the official AWS website and documentation. Check the official pages below for the latest specifications and pricing.
If this page and the official documentation disagree, treat the official documentation as authoritative.
