The Edge Computing Reality Check: Debunking Technical Misconceptions

Huge quantities of data are being produced and consumed by internet of things (IoT) sensors, consumer electronics and devices everywhere. Cutting-edge technologies require companies to use all this new, real-time data alongside existing static datasets where they reside today. As organizations explore new data-driven opportunities, the use cases for edge computing are growing across industries:

• Remote health monitoring
• Autonomous vehicles
• Live multiplayer gaming
• Predictive equipment management
• Personalized shopping experiences

For these latency-sensitive initiatives, data must be processed closer to the source, which means companies need infrastructure at the edge.

So, how do you deploy and manage that infrastructure? Using centralized data centers or relying exclusively on the cloud can create challenges around latency, resilience, performance, scalability and cost. But deploying infrastructure in multiple locations by yourself can feel intimidating, especially as the location of your edge evolves over time.

Enterprises often don’t know where to begin with edge computing and worry about the complexity and technical challenges of moving workloads to edge locations. But many of these fears are rooted in misconceptions. There are proven ways to simplify edge computing and use it as an innovation accelerator.

4 common edge computing misconceptions

Businesses are always thinking about IT security, scalability and costs, and now you can add data management, technology integration and skills shortages in emerging technologies to the list of worries. Balancing these needs isn’t easy, but it doesn’t have to be as hard as you might think.

Let’s look at four common misconceptions about the technical complexity of implementing edge computing and show how you can address them:

1. Edge computing makes data access difficult and expensive

Where data resides has a huge impact on the success of workloads, especially AI. It can affect application performance, scalability, costs, flexibility, security and compliance. Companies that have a lot of data already in the cloud want to stay where they’re familiar and may worry that moving data to edge locations will lead to significant egress costs as well as data replication and governance problems. They perceive edge computing to be more complicated to set up and manage, and more technically complex all around. Interconnecting edge infrastructure with existing infrastructure feels daunting.

Reality check

In truth, there are many ways to simplify data access and seamlessly integrate edge infrastructure with the cloud and distributed data centers. You can use software-defined interconnection between existing infrastructure and new edge sites for centralized control and policy automation. And validated architecture blueprints can help you design, deploy and even automate scaling to manage costs.

Meanwhile, the economics of edge computing are evolving, and total cost of ownership is often more favorable than anticipated. Rather than making upfront investments in new equipment, you can use repeatable on-demand infrastructure at the edge. Processing data locally can optimize bandwidth usage, thus reducing network costs. Consultative workshops on cloud or edge optimization can also help you evaluate the efficacy edge deployments for your business.

2. We don’t have the right edge infrastructure skills

Organizations also fear they don’t have the in-house talent needed to set up and manage infrastructure in edge locations. A lot of companies focus on cloud-based skills and developing AI ecosystems rather than on infrastructure skills to operate those ecosystems. This leaves them lacking the personnel to design, deploy and maintain additional infrastructure across non-cloud technologies.

Reality check

You don’t have to do edge alone. Specialized help is available. By working with trusted managed or co-managed services and experienced partners, you can leave infrastructure deployment and management to the experts and let your teams focus on innovation. If you’re working with the right partners, you no longer need to have highly skilled employees physically present everywhere your systems are deployed.

3. Edge computing inherently increases security risks

Some companies worry that decentralizing their data and increasing their attack surface automatically opens them to greater data security risk. Those that currently have their data in the cloud often use built-in cloud security controls and therefore consider the cloud responsible for risk. Putting data and capabilities on private infrastructure at the edge requires evolving that risk mitigation strategy, and this can be intimidating.

Reality check

Edge computing allows you to process data closer to where it’s generated and minimize the transfer of sensitive information. While public and private infrastructure both come with security risks, using private edge infrastructure gives you better visibility and granular control over your most valuable data. It also safeguards sensitive information more than public cloud. Finally, distributed environments can increase resilience more than public clouds.

4. Edge infrastructure is too technically complex and won’t integrate with our existing systems

Organizations may think edge infrastructure will be too difficult to integrate with their existing systems. It’s true that interconnecting different endpoints across an edge architecture can be challenging. Companies need their main hubs and edge sites to integrate, ideally with unified observability for simplified management.

Reality check

While the technical complexity is real, standardized, repeatable deployments greatly simplify edge computing implementation. With automated, private interconnection solutions, you can connect all the parts of your distributed infrastructure seamlessly.

How to simplify edge computing

While edge computing may seem overwhelming, there are many solutions and services to simplify it. Here are some recommendations:

Lean on localized expert resources

You don’t need people on-premises in every location. Instead, lean on local expert-managed services and work with partners who can physically set up and manage infrastructure for you at the edge. There are fully managed solutions that cover everything from infrastructure installation to application management, as well as partially managed solutions that handle only certain functions and leave the rest to you. Either way, you’ve got options.

Build a rich partner ecosystem

Edge computing isn’t just about localized processing; it’s also about being in the right places, connected to the right partners for your business. Choose data center partners that will enable expansion to new markets as your business grows. Identify the experts you need to work with, figure out where they are, and then put infrastructure in places where you can easily interconnect everything in your business ecosystem: clouds, networks, content providers, specialized AI services and more.

Position yourself for flexibility, scalability and neutrality

Decentralizing infrastructure using an edge model increases flexibility on where your data goes and how it travels. You can use one cloud or many, physical and virtual IT solutions. Given how unpredictable the future is, it’s important to have options to evolve your edge infrastructure when needs change. Make sure you design and deploy in a way that makes it easy to scale up and down and continuously evolve your partners to avoid vendor lock-in.

Explore your edge opportunity with Equinix

Equinix is uniquely positioned to help companies simplify their edge deployments. With 270+ data centers around the world, companies can find their edge with Equinix, wherever it may be.

Equinix experts are standing by to assist with cloud and edge optimization workshops tailored to your needs. We also offer a rich ecosystem boasting thousands of enterprises, clouds, SaaS companies and network service providers, so you can partner with your chosen vendors in a neutral environment.

Equinix Fabric® provides secure, private connectivity across distributed environments on demand, solving for interconnection complexity in edge environments. And if you want extra support on your edge journey, Equinix Managed Solutions and Enablement Services provide a highly skilled set of on-premises resources to stand up and manage infrastructure in edge locations.

Learn more about how to expand your possibilities and gain confidence with edge by downloading our white paper, Where edge meets AI opportunity.