AWS IoT Analytics Now Supports Channel and Data Stores in Your Own Amazon S3 Buckets
You can now create IoT Analytics Channel and Data Stores in an Amazon S3 bucket in your AWS Account. This lets you easily integrate your IoT Analytics data with your existing data lake, manage the lifecycle of the data according to your S3 bucket policies, and use the data with a downstream application for further processing or presentation to end-users. Previously, your IoT Analytics data could only be used with an S3 bucket managed by the IoT Analytics service. With this feature, and the recently added support for sending IoT Analytics data set content to your Amazon S3 bucket, you now have the flexibility to use S3 buckets in your AWS account for both your IoT Analytics data and materialized views of it.
You can now create IoT Analytics Channel and Data Stores in an Amazon S3 bucket in your AWS Account. This lets you easily integrate your IoT Analytics data with your existing data lake, manage the lifecycle of the data according to your S3 bucket policies, and use the data with a downstream application for further processing or presentation to end-users. Previously, your IoT Analytics data could only be used with an S3 bucket managed by the IoT Analytics service. With this feature, and the recently added support for sending IoT Analytics data set content to your Amazon S3 bucket, you now have the flexibility to use S3 buckets in your AWS account for both your IoT Analytics data and materialized views of it.
To get started, go to the IoT Analytics console. Create a new Channel or Data Store and select Customer Managed Stores as your storage type. Select an existing S3 bucket or create a new S3 bucket as a storage for your IoT data. Enter a Bucket key prefix to attach to the S3 objects that will be created for your IoT data. Save the Channel or Data Store to start sending the IoT data to the S3 bucket you selected.
To learn more about IoT Analytics, visit our product page. Standard Amazon S3 storage pricing applies for content stored in your S3 bucket.