As the Internet of Things (IoT) landscape continues to mature, major cloud providers have responded by creating IoT-specific offerings for their platforms. The scope of cloud IoT offerings covers a huge swath of the IoT solution space, extending from software installed on the actual devices themselves all the way to identification of trends in IoT data and automated responses.
When thinking about IoT, it is important to recognize that each IoT implementation is specific to the industry and business that’s building it. It’s more accurate to talk about your IoT instead of the IoT. With that said, there are significant advantages to be gained by leveraging the IoT service offerings of cloud platforms into your IoT implementation.
In this article, we will provide a summary of the cloud IoT offerings provided by Amazon’s AWS, Microsoft’s Azure, and Google’s GCP (Google Cloud Platform).
Brief History of Cloud IoT Offerings
Azure was first on the scene, publishing their Azure IoT Suite in March 2015, demonstrating their experience building business-oriented platforms by providing the best analytics visualization capabilities out of the group. Additionally, Microsoft leverages their deep experience with operating systems into Windows 10 IoT. AWS was a close second to provide a cloud IoT offering (December 2015). The power of the AWS IoT offering is its seamless integration with AWS’ robust and mature cloud solutions.
Google is a bit of a laggard, publishing their cloud IoT offering two years after Azure and AWS (September 2017).
IoT Solution Components
IoT solutions are complex and require many moving parts to work together as a whole to achieve business value. An IoT solution must have the following solution components.
Solution Component
Description
Sensors
Hardware that performs measurements.
Remote device management
Perform device firmware updates, factory resets, and reboots.
IoT OS
Local operating system for connected devices.
Edge computing
Perform a limited set of cloud computing tasks directly on local hardware installed near the IoT devices.
Transmit data
Send data to the cloud. Solutions must account for poor connectivity and low data rates.
Store data
Store continuous feeds of sensor data for later analysis.
Stream data
Stream sensor data through near-real-time processing.
Response to events
Machine learning algorithms to detect patterns in sensor data and automatically identify anomalies and correlations.
Remote commands
Send messages to devices and execute commands remotely.
Comparison of the Offering
Each of these cloud platforms have similar IoT offerings. The following shows the major components of an IoT and identifies the specific cloud offerings:
Purpose
Azure
AWS
GCP
Sensors
—
—
—
Remote device management
Azure IoT Hub
AWS Device Management
Cloud IoT Core
IoT OS
Windows 10 IoT
Amazon FreeRTOS
Android Things
Edge computing
IoT Edge
Greengrass
—
Transmit data
Azure IoT Hub
AWS IoT Core
Cloud IoT Core
Store data
Blob Storage
DynamoDB
Bigtable
Stream data
Stream Analytics
Kinesis
DataFlow
Response to events
Azure Machine Learning
SageMaker, AWS Machine Learning
Cloud Machine Learning
Remote commands
IoT Hub
AWS IoT Core
Cloud IoT Core
In summary, all three providers have significant capabilities. The one notable difference is that Google lacks edge computing.
Need Some Help?
As you can see, there are a lot of issues to consider and problems to solve to develop your IoT solution. If you need help determining which platform best fits your IoT needs, Credera would love to engage you on this topic. Feel free to reach out to us at findoutmore@credera.com.