5 Gaps You Need To Fill In Your Edge Computing Strategy

According to IDC predictions, businesses will spend $176 billion on edge computing in 2022, which is 15% higher than what they spent in 2021. It also indicates that we might see more use cases for edge computing pop up as architectural approaches and technical capabilities continue to improve.

Red Hat’s Tech Outlook report for 2022 shows that 61% of respondents have plans to run edge and IoT workloads. As the popularity of edge computing grows so do the security risks. Businesses will have to invest in DDoS protection services to secure the edge. If your business is also planning to ride the edge computing bandwagon, you will have to create an edge computing strategy in order to implement it successfully.

In this article, you will learn about five potential gaps you must not ignore when creating your edge computing strategy.

5 Gaps You Should Fill In Your Edge Computing Strategy

Here are five gaps you should immediately fill in your edge computing strategy.

Rigid Definition of Edge

When a technology becomes a buzzword and its use cases continue to grow, defining it becomes a challenge. The same holds true for edge computing. A rigid definition of edge computing does not account for specific use cases in daily routines. If your business goals do not fit in an edge computing strategy, you should not force it.

For instance, an edge server could be a specialized piece of hardware for a company while an edge server might mean a conventional dedicated server to another company. Same goes for use cases as well. There is no denying the fact that standardized use cases built around industry standards will continue to emerge but we will also see enterprises adopt enterprise specific strategies and tools. 

In addition to this, enterprise applications also vary from industry to industry. How can you give a rigid definition for a technology that varies based on a wide range of factors? Well, you can’t. If you are currently sticking to a rigid definition of edge, you are getting it all wrong. You need to be flexible when defining and understanding edge computing as it can be a diverse technology with dozens of different use cases and applications. 

Ignoring Change Management

Imagine implementing edge technology in an organziation who haven’t even heard about it before let alone know something about it. The change would be so drastic that it would force most employees in the opposition camp and you will have to face some criticism and resistance as well. 

It will have a similar impact as implementing online tutoring solutions in a traditional education institute. That is where you change management skills. Ignoring change management altogether can be a recipe for disaster. You don’t want your employees to suffer just because you are implementing a new technology in your organziation. 

To get over this issue, you need to take all the stakeholders on board and show them how edge can bring value to your organziation. Once they realize it is beneficial, the next step is to make them comfortable with the change. Implement change slowly so they don’t feel overwhelmed by it. The way you manage change will directly impact the chances of your success and failure of edge computing initiative.

Lack of Consistency

If you have some hands on experience with hybrid cloud, you might know how important repeatability, consistency and automation is. Its value increases manifolds when you are running hundreds of containers at once.  Shahid Mazumder, who is a Global Director of telecom solutions at Aerospike offers some valuable advice on this matter. According to him, “Follow a standardized architecture and avoid fragmentation – the nightmare of managing hundreds of different types of systems.” He further adds, “Consistency and predictability will be key in edge deployments, just like they are key in cloud-based deployments.”

This is where you start to see shades of hybrid cloud in edge computing as the same benefits carry forward. If you are well versed in reducing complexity in hybrid cloud environments, you will benefit from these experiences when implementing edge computing in your enterprise.

Since edge computing components are heterogeneous, you should prepare yourself to deal with this. You can minimize the complexity by leveraging containers and Kubernetes. Moreover, this can also simplify the process of migrating the workloads from the cloud to the edge especially if edge computing goes mainstream.

Management At Scale

Due to its heterogeneous nature, it is harder to manage edge at scale. You won’t get the right idea of the difficulty until you see all the workloads run in production. To keep the management complexity under control, you need a centralized platform that lets you manage everything from a single dashboard. 

Look for platforms that enable you to manage your entire edge infrastructure and workloads from a single screen. This takes the pain out of the migration process and simplifies the process of making changes to configurations and settings.

One Size Fits All Approach

There is no worse mistake you could ever make when implementing edge computing than adopting a one size fits all approach. Whether you are buying art online or a technology solution, you should never adopt a one size fits all approach. If you think that build once, run anywhere can work for all workloads, you are wrong. We have already seen examples of systems that worked great on premises but struggled when implemented on the edge.

Did this article help you in finding gaps in your edge computing strategy?