With the proliferation of IoT, connectivity and computing technologies are becoming more diverse. It can seem there are so many ways to power an IoT ecosystem, and it can be hard to cut through the hype of buzzwords to understand what it means for your unique business case.
This term stems from hyperscale computing, which is an agile method of processing data. Depending on data traffic, scale can quickly go up or down. Hyperscalers have taken this computing method and applied it to data centers and the cloud to accommodate fluctuating demand.
Major hyperscalers in the business offer Infrastructure as a Service (IaaS) to help meet the need of enterprises seeking digital platforms. Essentially, hyperscalers manage the physical infrastructure while the end user customizes a virtualized computing infrastructure.
The infrastructure layer in a technology stack is where the computing power lies, and IoT is gaining traction amongst hyperscalers and telecoms, who are beginning to invest in building IoT platforms. An IoT platform helps bring IoT solutions to market faster and streamlines the process to deployment.
This is a significant nod toward the importance of IoT in the technology realm, but hyperscalers certainly aren’t the first to develop IoT platforms. It is important to research the benefits of using an IoT platform from a cloud services provider versus an IoT expert.
IoT sensors and devices are responsible for collecting data, and connectivity is responsible for communicating the data. The part of the infrastructure that computes the data can either be the cloud or the edge.
The cloud is a centralized approach to process data and works well when it comes to power and capacity. It allows scalability for enterprises, and the pay-as-you-go model makes it an affordable approach to smaller organizations that do not want to build out an entire computing infrastructure in-house.
Edge computing is rising in popularity due to the speed at which data can be computed. Instead of sending data from the edge to the cloud, the data is computed right at the edge. The edge can mean several things, though.
When it comes to choosing between the edge and the cloud, it boils down to speed and cost. Artificial intelligence and machine learning in robotics are use cases where edge computing makes the most sense. Processing close to the device level makes sense when there is less tolerance for latency. Also in use cases such as autonomous vehicles, a slower reaction time from a machine in automated processes can spell disaster.
But not all IoT use cases are mission critical and latency isn’t a primary factor. Smart agriculture, for instance, wouldn’t sink costs into edge devices or developing a network or telco edge, since the low power devices with slower processors are at the core of the data aggregation.
KORE can help you strategize and build your infrastructure from devices, connectivity, and platforms, with security throughout. KORE is an IoT expert with nearly two decades of experience helping organizations deploy, manage, and scale their IoT solutions.
Want to learn more about IoT connectivity and how KORE can help? Check out this ABI Research whitepaper to learn more.
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