AWS takes IoT beyond data analytics, into management
12 October 2015 | 0
AWS Internet of Things (IoT) presents devices in two ways: the devices themselves, aka “things,” and virtualised representations, or “thing shadows.” The latter lets the user pre-emptively set the state of devices without requiring a network connection; once a disconnected thing reconnects, it attempts to sync with its shadow and apply any changes pushed (a function natively supported in the MQTT protocol). Devices can also be tracked through a registry.
Amazon surrounds these features with a few additions that, while not explicitly IoT-related, can fall under the heading. A new function for Amazon’s Kinesis Analytics allows SQL queries to run against streaming data — for instance, as part of a time-series processing job. The service is set to include many prebuilt functions, such as moving averages or totals.
In terms of construction, the heart of AWS IoT is not drastically different from that of other web service back ends. The fact that it is Amazon makes the difference, what with so many customers already building on top of Amazon’s application, data-storage, and data-ingestion frameworks. Anyone already on Amazon’s cloud has one fewer reason to bother with other IoT integrators. Contrast that with Salesforce IoT Cloud, which limits its appeal to existing Salesforce customers, whereas nearly everyone is a potential AWS customer.
There is a case to be made for why IoT and public clouds like Amazon’s complement each other: a measure of built-in security, elasticity, and a geographically distributed architecture that works with the devices themselves. It was inevitable that Amazon would become a centre of gravity, but now it remains to be seen if its device-management-plus-data-collection approach pulls people in.
Serdar Yegulalp, IDG News Service