Emerging IoT Ecosystems: Matches Made in the Cloud

Michael Schofield
Emerging IoT Ecosystems: Matches Made in the Cloud


The major cloud providers are jumping on the Internet of Things (IoT) trend as it moves from concept to reality. The last few months of 2015 saw a spate of major IoT announcements from the likes of Amazon, Microsoft, Google and others.

IoT and the cloud are perfect for each other, as IoT data often comes in huge, unpredictable floods. The need to store, analyze and draw conclusions from big data volumes cries out for copious, scalable storage and compute power-a scenario made for the cloud. Global reach is also a critical requirement, because it’s important for organizations gathering information from widely dispersed jet engines, refrigerators, connected cars, urban sensors and other “things.”

Many leading cloud providers and enterprises have begun offering entire IoT processing ecosystems to fulfill the gathering, transport, storage and analytical needs of just about any IoT player and developer.

Amazon‘s AWS IoT service offers a platform for just about any IoT need. Its components include a lightweight communications protocol to transport information from networked devices through an AWS Device Gateway and Rules Engine to collection points, which can be anything from AWS’s Simple Storage Service to DynamoDB or Kinesis, depending on the need. AWS Device Shadows communicates with devices when they’re offline to get information on the last reported state and reconfigure a future state.

Microsoft‘s Azure IoT Suite takes a similar ecosystem approach as AWS, with tools for capturing, integrating, analyzing and reporting information via the cloud. It includes the Event Hubs service bus, DocumentDB, HD Insight and other similar Azure services.

Google‘s solution takes a more “do-it-yourself” approach, according to this blog by Kurt Marko of MarkoInsights, letting customers stitch together an ecosystem with Big Query, the Cloud Pub/Sub message bus and Firebase.

GE‘s approach diverges from the others because it has a more targeted, decentralized approach to its GE Predix Cloud for industrial data. Rather than offering a few mega data centers, Predix plans to disperse data center infrastructure across North America and the world in a larger number of Equinix colocation centers and focus on fast, reliable communications with its customers. In this way, data collection will be closer to widely dispersed sources, and it will be easier to comply with local data sovereignty requirements. GE also adds its deep engineering expertise in manufacturing turbines, locomotives and jet engines to help organizations get started analyzing useful data from these types of devices quickly.

All of these cloud providers make their services available via the Equinix Cloud Exchange, which enables enterprises to directly connect to multiple clouds and networks in the same location. There’s a definite advantage to harnessing global colocation centers to reduce latency and amp up performance, not only ingesting the data close to the source for real-time analytics, but colocating with partner providers, customers and suppliers for direct, high-speed interconnections. The performance and security advantages of an enclosed, regulated architecture with direct connections are hard to beat. Enterprises benefit as well, as they enhance their choice of cloud providers and other partners by colocating their own infrastructure and taking advantage of services like the Equinix Cloud Exchange to build flexible, hybrid/multi-cloud architectures. Equinix is at the Intersection of where networks and cloud meet and where IOT is evolving.

Subscribe to the Equinix Blog