Edge computing is a distributed computing model where data is stored and processed close to or at the location it is being generated. This can involve using regional data centers or storage and processing located at network endpoints. Designing networks in this manner can produce many benefits over more traditional approaches to enterprise infrastructure architecture.
Here are 5 benefits of edge computing:
- Reduced Latency: - By storing and processing data close to its origin, edge computing minimizes the time required for data to travel, resulting in faster application performance and improved speed.
- Improved Reliability: - Unlike centralized architectures, edge computing offers enhanced reliability as it doesn't rely on a single central data repository. This decentralization reduces the vulnerability to connectivity issues and security breaches. Additionally, the failure of one edge device typically doesn't impact other devices or the overall enterprise system, ensuring greater overall reliability and reduced impact from a single point failure.
- Enhanced Security: - Edge computing's distributed nature and absence of a central repository mitigate the potential impact of security breaches. If a breach occurs, it is typically limited to a single node, minimizing the extent and consequences of malicious attacks.
- Reduced Cost: - E Edge computing reduces the need for extensive data movement between nodes and data centers. Since data is processed at its point of origin, bandwidth costs can be minimized, resulting in cost savings.
- Real-time insights: - Because edge computing processes data at endpoints, insights can be drawn from data more quickly. These insights, as opposed to raw data, can then be transmitted to a central command center or acted upon locally through process automation or AI.