Amazon Web Services, Microsoft Azure, and Google Cloud account for 80% of the global cloud market. Which one is right for your operations?
Within the IIoT field, cloud platforms are often talked about. In this article, we will discuss some of the popular ones. Let’s dig in.
What Is a Cloud Platform?
A cloud platform refers to the operating system and hardware of a server in an Internet-based data center. It allows software and hardware products to co-exist remotely and at scale. The service offerings of each cloud provider in this analysis focus on three categories relevant to industrial companies:
- Application Management/Enablement: Services aimed at enabling software developers to make and manage Internet of Things (IoT) applications. This may include rules engines, IoT development environments, or digital twins.
- Device Management: Services designed to guarantee that connected devices are working properly by providing patches and updates for software running on the devices or their associated edge gateways. For example, this may include device monitoring, firmware updates, or deployment configuration management.
- Data Management/Enablement: Services that provide the capability to store and analyze IoT-related data.
- Currently, three large platforms hold 80% of the global cloud market: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. However, not all cloud platforms are created equal. While they offer similar baseline functionality, the platforms have carved out strategic niches for themselves, which render them better suited to some industries and use cases than others. IoT Analytics, an Internet of Things market research firm, has broken down the features of each of the major cloud platforms and provided commentary on their strengths and weaknesses.
- Cloud-based technology offers end users in the manufacturing and processing industries a plethora of benefits. Perhaps most importantly, it enables a “single source of truth” for large datasets gathered from disparate systems and facilities. By synchronizing this data, cloud platforms can enable end-to-end planning and visibility that would be difficult or impossible if local, on-premises servers were used instead. Moreover, because cloud platforms ingest large quantities of data from many locations and companies, they can be used to train powerful machine learning applications that individual operations would not have the capacity to develop on their own.
Which Cloud Platform Is Right for Your Operations?
Amazon Web Services (AWS)
Amazon Web Services (AWS) was the first major platform to introduce public cloud service, having done so in 2006. However, it only began adding IoT-specific services in 2015, according to IoT Analytics.
It is known for its ease-of-use and flexibility compared to other platforms, as attention has been paid to making setup as intuitive as possible, and tutorials are openly offered by the company. That said, while AWS’ offerings are diverse, they are not as specialized as Microsoft Azure, particularly regarding applications for manufacturing, says IoT Analytics.
Most prominently, AWS is also known for the multitude of its offerings, with a total of 227 different cloud services being listed on its website in 2022. This is because AWS’ business model is most oriented toward application management/enablement, rather than device management or data management/enablement. Still, the platform has begun to move in this direction with the announcement of several new IoT services aimed at those in industry, including AWS IoT RoboRunner and AWS Private 5G.
Microsoft Azure
Although Microsoft Azure launched its public cloud four years after AWS, it introduced its IoT services only five months after AWS did. Since then, IoT Analytics says Microsoft has established an IoT-centric strategy catering specifically to enterprise clients and has managed to overtake AWS in this domain. The key differentiator featured by Microsoft Azure is its ability to integrate with business intelligence tools like Power BI. Microsoft Azure is focused on simplifying the way IoT is used by enterprises to achieve better interoperability, with a particular emphasis on Industrial IoT and edge computing.
For many customers, Microsoft Azure is easier to adopt because they are already using Microsoft Windows, Microsoft 365, and Microsoft Dynamics in their front-office operations. As a result, data pulled from OT (operations technology) into the Microsoft Azure cloud is easier to integrate with front-office IT systems. Moreover, Microsoft Azure offers industry-specific services that AWS lacks, such as Microsoft Cloud for Manufacturing. Whereas AWS features strong application management/enablement offerings, Microsoft Azure is geared toward device management with special attention being paid to industrial hardware and devices.
Google Cloud
In the global public cloud computing market, Google Cloud is a distant third to both AWS and Microsoft Azure, according to IoT Analytics. However, it is still the key supplier of several commonly adopted cloud technologies. Most prominently, the open-source container orchestration platform Kubernetes was designed by Google and has become the de facto standard for managing software containers in the cloud.
In addition, because of Google’s extensive experience in organizing search and other data, IoT Analytics notes that Google Cloud excels in analytics, big data, artificial intelligence, and machine learning. Of the three major cloud platforms explored in this article, compared to both AWS and Microsoft Azure, IoT Analytics says Google Cloud offers substantially fewer IoT-specific services overall. While there are several major IoT clients who use Google Cloud, the platform is less focused on industrial companies and moreso on IT companies such as Spotify and Snapchat.
Google Cloud is most oriented toward data management/enablement services as opposed to application management/enablement or device management services. Google Cloud’s IoT service is called Cloud IoT Core and is similar to Microsoft Azure’s IoT Hub. However, it integrates Google’s general analytics tools to enable further data processing and management functionality.
There are several types of cloud platforms. Not a single one works for everyone. There are several models, types, and services available to help meet the varying needs of users. When considering industrial cloud platforms, find the one that best fits your own needs.
