What is a suitable use case for edge computing within hybrid cloud environments?

Real-time analytics for IoT devices is a suitable use case for edge computing within hybrid cloud environments. Edge computing brings processing capabilities closer to the source of data generation—such as IoT devices—allowing for immediate data analysis and quick decision-making. This is crucial for applications where timely insights are necessary, such as in smart cities, autonomous vehicles, or industrial automation. By analyzing data locally at the edge, organizations can reduce latency and bandwidth usage, as they do not need to transmit large amounts of data to a centralized cloud for immediate analysis.

In contrast, the other scenarios mentioned do not leverage the strengths of edge computing as effectively. For instance, data backup solutions and long-term data archiving generally require large-scale storage and less frequent access, making centralized cloud storage more suitable. Batch processing of large datasets typically involves executing processes that can tolerate some latency, where data does not need to be acted upon in real-time, making centralized processing a better fit. Therefore, real-time analytics for IoT devices stands out as a compelling use case that optimally benefits from the agility and responsiveness of edge computing in a hybrid cloud environment.