Comparison Of IoT Services From AWS, Azure, And GCP
By Kumarasenthil Muthuvel, Information Technology Leader
The field technologies industry is ripe for cloud adoption leveraging the IoT infrastructure of the major cloud service providers like Amazon Web Services, Azure, and Google Cloud Platform. For example, with the transportation and logistics industry, IoT technology and services can be of immense help to effectively manage the fleet from a centralized location.
Consider a scenario where several trucks are en route to deliver goods across North America each carrying different categories of goods – refrigerated, dry, and hazardous. Upon installing the IoT sensors to different systems in the vehicles, one can efficiently manage any incidents in real-time as they occur and take corrective action to alert service teams, resolve failures in the vehicle’s systems, reroute, plan for backup trucks and drivers – all from a centralized remote location.
In its simplest form, an Internet of Things (IoT) platform can have three layers – the Perception layer, Network layer, and Processing layer. The Perception layer represents the hardware devices or “things”. These “things” are usually electronic sensors and Actuators. Sensors capture signals from the real world, convert them into machine understandable digital formats, feed them into the IoT control center. If Sensors are the entry point of an IoT process, Actuators can be considered as the result or outcome of the IoT process. Actuators receive electrical input and convert that into a physical action on the target device.
The Network layer comprises the data transmission networks and the gateways. While the transmission network reliably transmits data between “things” and the IoT control center, gateways conform the transmission protocol.
Coming out of the Processing layer, application developers can add the fourth layer, called the Application layer, to make sense of the processed data and build business-specific applications. Message Queueing Telemetry Transport (MQTT) is the IoT protocol widely used. The Message Queuing Telemetry Transport is a lightweight, publish-subscribe network protocol that transports messages between devices.
This article discusses in detail the IoT services offered by the three major cloud service providers – Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP). While the central element of the IoT service offerings is connectivity, ingestion and, processing, each of the cloud service providers differ substantially in how the services are packaged and priced. AWS leads the market with comparatively more managed services while Azure and GCP follows.
Amazon Web Services
AWS IoT Core: AWS IoT Core, as the name suggests, is the core service in the IoT offerings from AWS. AWS IoT Core connects billions of IoT devices to AWS Cloud and is a fully managed service meaning there is no need to provision and manage servers. AWS IoT Core natively integrates with other AWS services like AWS Lambda, Amazon Kinesis, Amazon S3, Amazon Sagemaker, Amazon DynamoDB, CloudWatch, Aws CloudTrail, Amazon QuickSight.
AWS IoT Device Defender: AWS IoT Device Defender is another fully managed service that helps secure the fleet of IoT devices. AWS IoT Device Defender continuously monitors key metrics from the devices for any deviations. Configurations can be set and monitored for any unusual behavior. AWS IoT Device Defender is integrated with other AWS services natively to take corrective action following an incident.
AWS IoT Device Management: AWS IoT Device Management is another useful service offering through which a large fleet of IoT devices can be managed easily. With AWS IoT Device Management, the fleet of devices can be updated for their firmware after being deployed to the field.
FreeRTOS: FreeRTOS is an open-source, real-time operating system for microcontrollers that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage. Distributed freely under the MIT open-source license, FreeRTOS includes a kernel and a growing set of software libraries suitable for use across industry sectors and applications. This includes securely connecting your small, low-power devices to AWS Cloud services like AWS IoT Core or more powerful edge devices running AWS IoT Greengrass. FreeRTOS is built with an emphasis on reliability and ease of use and offers the predictability of long-term support releases. FreeRTOS includes IoT reference integrations, which are pre-integrated FreeRTOS projects ported to microcontroller-based evaluation boards that demonstrate end to end connectivity to the cloud, and pre-configured demos that can help you quickly get started with a project.
AWS IoT Greengrass: AWS IoT Greengrass is an IoT open-source edge runtime and cloud service that helps you build, deploy, and manage device software. AWS IoT Greengrass lets you quickly and easily build intelligent device software. AWS IoT Greengrass enables local processing, messaging, data management, ML inference, and offers pre-built components to accelerate application development. AWS IoT Greengrass also provides a secure way to seamlessly connect your edge devices to any AWS service as well as to third-party services.
AWS IoT Analytics: AWS IoT Analytics is a fully managed service that makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data. IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third-party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield.
AWS IoT SiteWise: AWS IoT SiteWise is a multi-site service offering from AWS. With AWS IoT SiteWise, you can gather data reliably from multiple facilities, structure it, and make it accessible and understandable—without developing additional software.
AWS IoT Events: AWS IoT Events is a fully managed service that makes it easy to detect and respond to events from IoT sensors and applications.
AWS IoT Things Graph: AWS IoT Things Graph is a service that makes it easy to visually connect different devices and web services to build IoT applications.
Azure IoT Central: Azure IoT Central is the SaaS offering from Azure that bridges the gap between IoT data and business applications. There are pre-configured templates for healthcare, energy, retail, and government sectors.
Azure IoT Hub: Azure IoT Hub is a managed PaaS backend solution that acts as a central message hub between IoT applications and devices. Customers requiring more customizations can choose to use Azure IoT Hub.
Azure IoT Edge: Azure IoT Edge is built on Azure IoT Hub and is a fully managed service. By moving certain lightweight workloads to the edge of the network, companies can design near real-time processing of events.
Azure Sphere: Azure Sphere is a secured, high-level application platform with built-in communication and security features for internet-connected devices.
Azure Digital Twins: Azure Digital Twins enables us to create comprehensive models of the physical environment. We can model the relationships and interactions between people, spaces, and devices. For example, we can predict maintenance needs for a factory, analyze real-time energy requirements, or optimize the use of available space.
Google Cloud IoT Core: Cloud IoT Core is a managed solution to connect, manage, and consume data from numerous connected devices. It offers a complete solution for developers, allowing them to collect, process, analyze, and visualize IoT data in real-time for supporting better operational efficiency.
Google Cloud TPU: Cloud TPU is designed to run cutting-edge machine learning models with AI services on Google Cloud. Cloud TPU is the custom-designed machine learning ASIC that powers Google products like Translate, Photos, Search, Assistant, and Gmail.
Conclusion
While all the three major cloud service providers offer IoT services, there are also other players in the market like Cisco, IBM, SAP, Oracle, Siemens, etc., These players are mainly focused on building new IoT capabilities for their existing customers. AWS, Azure, and GCP are more focused on leveraging their existing global infrastructure to add IoT services as a value-add. This objective and the range of software, hardware, firmware capabilities that these three major cloud providers bring to the customer influences the choice of the customer. When choosing between the three major providers, companies should evaluate a range of features including protocols supported, pre-built templates, operational excellence, provider maturity in IoT, provider global infrastructure (ex., edge locations), pricing, developer productivity.
About The Author
Kumarasenthil Muthuvel is a leader in information technology with a proven track record of partnering with multi-national organizations to modernize their infrastructure for efficiency and ROI. He has a bachelor’s degree in electronics and communication engineering and has 15 years of experience in cloud services, programming, database management, distributed processing, middleware, infrastructure as code technologies and practices. For more information, email kumarasenthil@gmail.com.