Gartner predicts that 75% of enterprise-generated data will be created and processed outside of a centralized data center or cloud environment, up from 10% in 2018. Let’s look at the top edge computing benefits driving this rapid adoption.
Reduced Latency and Improved Performance
The time it takes for data to travel to and from the processing systems is known as latency, and it’s a leading cause of performance issues like slow speeds and timeouts. Edge computing occurs very close to the source of data collection, so that data doesn’t have to travel very far. This reduced latency improves the speed and performance of the applications that rely on edge data, such as cloud native EDA tools.
Improved Security and Data Privacy
Centralized data centers are a high-value target for hackers and other cybercriminals because they store and transfer large quantities of sensitive data. Edge computing keeps data dispersed around the edge of your network, so no single device holds too much valuable information. This makes edge compute systems less tempting to hackers and limits the damage if an edge device is breached.
In a centralized network, all data must flow through data processing servers in a data center, which creates a single point of failure for all the systems and applications that rely on that processing power. If there’s an equipment failure or network outage at the data center, everything grinds to a halt. Edge computing relies on many different processing systems distributed geographically and logically, which means one can fail without affecting all the rest. This improves the reliability and resiliency of the entire enterprise network.
Scaling up a large data processing server in a centralized data center can be highly disruptive because these systems power so many business-critical workflows and applications. Servers may need to shut down or restart to install new hardware, and a mistake in the software upgrade process could extend the downtime even longer. Because each edge computing system is only responsible for a limited number of data sources and only affects a small corner of your network, scaling and upgrading this infrastructure isn’t as disruptive or risky.
Operational Cost Savings
In a centralized architecture, the large quantities of data generated by edge devices must be transferred to the data center over the internet, using a lot of bandwidth. Since most ISPs and data centers have a usage-based pricing model, and the amount of data created at the edge will only continue to grow over time, this can drive operational costs through the roof. In an edge computing architecture most edge data stays on the local network (LAN), reducing your bandwidth usage and keeping costs under control.