lack of skills, tools, and budgets.
Edge Computing and the Internet of Things (IoT) are becoming prevalent technologies for many industries: government, consumers, utilities, security, agriculture, smart buildings, healthcare, data center operations – just to mention a few!
A consequence of the widespread IoT adoption is that developers and architects are seeing how very different the supporting infrastructures are from other cloud-based or virtual applications.
Challenges that enterprises, healthcare and government agencies, for example, face as they attempt to deploy Edge computing and IoT, are lack of skills, tools, and budgets.
For example, with new, large and volatile data streams being produced by these systems, performance and capacity planning must be more integral than ever as part of the design, deployment and operation of Edge/IoT applications.
Here’s a slice of the real world: In a recent project, we found that a sensor camera application had potential flaws that would prevent full functionality – largely due to data processing, performance and cloud instance availability.
These limitations would potentially compromise the security of the facility. Modelling the application early in the development process identified the performance problems so that the software could be improved before deployment.
So, the good news is there are established best practices and tools to ensure successful deployments while managing performance, capacity, operations, data and analytics.
Cloud technology is essential to these implementations; in fact, the cloud is a critical part of the Edge infrastructure.
All of the major cloud providers already offer tools to manage the cloud infrastructures required for the Edge and IoT, and these offerings will continue to evolve to meet new demands.