Getting started with edge computing

Edge computing, as defined by Microsoft Azure, is a framework allowing devices in remote locations to process data at the network's edge, minimizing latency by transmitting only essential data to central datacenters. Experts such as Jerome Hardaway, Kate Goldenring, and Alex Ellis discuss how this concept differs from traditional cloud applications, emphasizing the need for human-centric definitions and acknowledging the diverse categories like geography-based, resource-based, and connectivity-based aspects of edge computing. They highlight the architectural differences between edge, private, and hybrid cloud computing, noting that edge computing focuses on responsiveness and resource placement. While edge computing's application suitability varies, its development requires consideration of resource constraints and portability issues, often influenced by the extent of platform-specific features used. Skills in Kubernetes, Python, networking technologies, and communication are recommended for developers venturing into edge computing, with learning tools such as Raspberry Pi suggested for hands-on experience.