Smart, connected operations are helping manufacturers to optimize plant performance through remote monitoring and predictive maintenance apps. Sensors placed on connected assets send readings to the internet, where businesses can access the information to gain insights that inform their decisions. While the data generated from these assets is central to any IIoT deployment, the architecture that supports it can be confusing.
Cloud and edge computing provide different models for data storage that can impact an industrial organization’s ability to leverage IIoT data. At first glance, it may seem as though cloud and edge are competing technologies, but they also complement each other throughout the digital transformation journey. To understand how, it helps to realize the strengths of each approach, as well as what a hybrid solution of both technologies offers.
The biggest benefit to hosting IIoT data in the cloud is the scalability that it provides to global organizations. As a centralized location for data storage that excels at ingesting and processing big data, cloud solutions are best suited for supporting industrial IoT platforms like ThingWorx that value speed, security, and flexibility.
Manufacturers that need a solid foundation to deliver and iterate IIoT applications often choose cloud-based IT solutions for a quick, uncomplicated setup that enables them to see results faster. Cloud providers with domain expertise like Microsoft typically have a range of complementary offerings that help industrial businesses take a more holistic approach to their digital transformation and IIoT initiatives.
On the other hand, edge computing and the ability to process data locally at the point of operation has its own distinct advantages. For one, time-critical operations that require instant data analysis, like a self-driving car, cannot afford the latency associated with cloud-based solutions. They must be able to process and respond to data in real-time, without relying on proximity to a centralized server farm.
Businesses with industrial equipment in remote locations or harsh environments may favor an edge computing approach that can help to minimize transmissions costs and response times, but maintaining and upgrading the distributed hardware can be challenging.
Industrial businesses don’t necessarily have to choose between cloud and edge computing to drive their IIoT strategy. Many are using both to make time-sensitive decisions on-site, while sending cleaned and processed data to the cloud to inform larger-scale production and utilization choices. Edge computing delivers the real-time diagnostics that on-site managers need, while the cloud provides visibility into operations for those outside of the production environment.
If you’re interested in learning more about the intersection between IT and OT, download this complementary e-book.