Best Practice 11.2 – Use device hardware with sufficient capacity to meet your data retention requirements while disconnected
Store important messages durably offline and, once reconnected, send those messages to the cloud. Device hardware should have capabilities to store data locally for a finite period of time to prevent any loss of information.
Recommendation 11.2.1 – Leverage device edge software capabilities for storing data locally
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Using AWS IoT Greengrass for device software can help collect, process, and export data streams, including when devices are offline.
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Messages collected on the device are queued and processed in FIFO order.
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By default, the AWS IoT Greengrass Core stores unprocessed messages destined for AWS Cloud targets in memory.
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Configure AWS IoT Greengrass to cache messages to the local file system so that they persist across core restarts.
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AWS IoT Greengrass stream manager makes it easier and more reliable to transfer high-volume IoT data to the AWS Cloud.
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The ETL with AWS IoT Extract, Transform, Load with AWS IoT Greengrass Solution Accelerator
helps to quickly set up an edge device with AWS IoT Greengrass to perform extract, transform, and load (ETL) functions on data gathered from local devices before being sent to AWS. -
Consider using AWS IoT SiteWise for data coming from disparate industrial equipment
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The AWS IoT SiteWise connector sends local equipment data in AWS IoT SiteWise. You can use this connector to collect data from multiple OPC Unified Architecture (UA) servers and publish it to AWS IoT SiteWise.
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AWS IoT SiteWise connector with AWS IoT Greengrass can cache data locally in the event of intermittent network connectivity.
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You can configure the maximum disk buffer size used for caching data. If the cache size exceeds the maximum disk buffer size, the connector discards the earliest data from the queue.
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