Edge computing best practices

Edge computing raises technical concerns, such as security and scalability, as well as cultural considerations, such as how to improve collaboration among IT and operations teams

Data processing, analytics, and storage increasingly are taking place at the network edge, close to where users and devices need access to the information. Not surprisingly, edge computing is becoming a key component of IT strategy at a growing number of organizations.

A recent report from Grand View Research predicted the global edge computing market will reach $3.24 billion by 2025, expanding at a “phenomenal” compound annual growth rate (CAGR) of 41% during the forecast period.

One of the biggest contributors to the rise of edge computing is the ongoing growth of the Internet of Things (IoT). The vast amounts of data created by IoT devices might cause delays and latency, Grand View says, and edge computing solutions can help enhance the data processing power, which further aids in avoiding delays. Data processing takes place closest to the source of the data, which makes it more feasible for business users to gain real-time insights from the IoT data devices are gathering.

Also helping to boost the edge market is the presence of high-connectivity networks in regions such as North America.

Edge computing is used in a variety of industries such as manufacturing, IT and telecommunications, and healthcare. The healthcare and life sciences sector is estimated to see the highest CAGR between 2017 and 2025, Grand View says, because of the storage capabilities and real-time computing offered by edge computing tools that enable the delivery of reliable healthcare services in lesser time. The decision-making process is enhanced as network failures and delays are avoided.

Supporting edge computing can be challenging for organizations because it involves a lot of moving parts and a change in thinking from the current IT environment dominated by data centers and cloud-based services. Here are some best practices to consider when building a strategy for the edge.

Create a long-term edge computing vision

Edge computing involves a lot of different components, and it requires building an infrastructure with the capacity and bandwidth to ingest, transform, analyze, and act on enormous volumes of data in real time, says Matt Kimball, senior analyst, data center, at global technology analyst and advisory firm Moor Insights & Strategy.

On the networking side alone, it means deploying connections from devices to the cloud and to data centers. While companies might have a desire to ramp up their edge infrastructure as soon as possible in order to support IoT and other remote computing efforts, all of this is not going to happen overnight.

“Think big, act small – meaning map out the long-term vision for edge deployments” but don’t be in a rush to implement edge technologies all over the place right away, Kimball says.

The speed at which edge technologies can be rolled out varies

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