Edge and internet of things-based initiatives may not dominate current news cycles, but there has been a significant increase in computing at the edges. In fact, IoT and edge technologies may be creating more technology opportunities than artificial intelligence, which currently receives most of the attention.
A survey of 1,037 IT executives and professionals revealed that control logic, or embedded automation, has surpassed AI as the most common edge computing workload. The survey also found an increase in development across all IoT sectors, with Java being the top language for IoT gateways and edge nodes.
Skills in designing and building edge systems involve shifting focus from traditional centralized data center approaches to understanding and optimizing the edge of networks and infrastructure. Professionals need to be adept in IoT integration, network security, and data analytics to handle rapid, secure data processing at the point of collection.
AI and machine learning are also playing a role in edge and IoT initiatives, driven by the demand for intelligent and autonomous systems capable of making real-time decisions. Managing large data volumes and ensuring enhanced security measures are crucial for professionals working with edge and IoT technologies.
Leveraging the edge and IoT has proven critical for companies like MasterCard, which have shifted their edge footprint to use both private and public cloud resources. Sensors and automation in edge systems help enhance efficiency and sustainability, leading to energy savings and overall operational improvements.
With the exponential growth of data at the edge and in IoT environments, companies are increasingly focusing on edge compute capabilities as a decisive advantage. Professionals need to understand how to leverage edge computing to enhance operational efficiency and decision-making processes in various sectors.
The increasing amount of raw data requires a transition from centralized processing to edge processing in order to alleviate bandwidth limitations, decrease expenses, and tackle issues such as network latency and congestion.
