In 2021, updating outdated IT infrastructure will continue to be the top factor driving IT budget increases — cited by 56% of organizations planning on growing IT spend — followed by an increased priority on IT projects (45%) and escalating security concerns (39%).

Even with the impacts of COVID on the economy, a significant amount of businesses plan to grow IT spend. Doubtless, the desire to update IT infrastructure comes in part from businesses’ mass movement to the edge. Additionally, COVID has pushed this movement to the edge even harder as whole organizations move from centralized offices to distributed workforces.

Edge computing provides businesses with on-demand application and network access that can’t be supplied by centralized computing. With companies being impacted even more by the distributed reality of computing, they need to provide this access anywhere. Edge colocations help solve this challenge by delivering dense computing, network, and edge infrastructure from a single location.

By storing data on the edge, companies avoid convoluted network paths that slow down traffic and hurt the customer experience. However, a significant factor in making a company’s colocation strategy a success is infrastructure.

Choosing Hardware That Supports Your Edge Colocation Needs

There are four principal components to consider when designing edge colocation hardware that meets your needs: CPUs, storage, networking tools, and the system bus. The key to efficiency and performance isn’t simply purchasing more costly hardware but instead ensuring that all the components are optimized to work together at their full potential.

All of these components affect the latency of your infrastructure. This is important because as applications grow, they often begin to transmit more data between the network and the user. These elevated data requirements can slow down performance if businesses don’t take measures to increase their latency capabilities.

Processors That Can Handle Increasing Workloads

The processing unit you use is dependent on your use case. For example, applications that have a light processing load are often fine with a typical CPU setup. One solution to a heavy load is using a multi-CPU system. In this case, it’s important to ensure that the software is written to accommodate additional CPUs. Otherwise, the cost will far outweigh the benefits.

Additionally, many multi-CPU systems split memory between all available processors. The access to this shared memory is significantly slower than memory that is attached directly. Therefore, it’s important to start by ensuring that processors are being used to their potential before scaling the hardware, as this may result in amplified inefficiencies.

In many compute-intensive workloads, it’s common to see GPUs being used. This is especially true of the complex calculations found in AI and machine learning since GPUs can handle parallel processing and provide much better performance for heavy workloads.

Storage Adapted to the Needs of Your Business

Storage is another important consideration that needs to be closely aligned with the application. For read-heavy applications and low latency I/O cases, SSD and flash memory storage will work great. But what about applications that deal with a high number of I/O requests?

This is where NVMe SSDs provide the most value. While they are more expensive than SSDs and flash memory, their improved queue depth offers better performance for simultaneous I/O. When speed isn’t the most important factor, hard disc drives are a great low-cost option, especially since their price-to-density ratio is by far the best.

Networking tools that open the way for faster performance

Different networking cables plugged into a server.

Networking tools are the roadway for the rest of your edge infrastructure. Just as you wouldn’t build a four-lane highway for a small town, it would be impractical to purchase the fastest network interface cards (NICs) when the rest of your hardware will never be able to utilize its potential. Additionally, depending on the use case, it is sometimes more efficient to use different network cards for different CPUs instead of a single shared high-performance NIC.

System bus components that facilitate communication

The system bus controls communication between CPUs, memory, storage, and the network, meaning the systems can only go as fast as this communication can take place. More than any other component, the system bus must be optimized to the other hardware as communication and performance will be hindered otherwise.

Additionally, hardware needs to be matched with the application. For example, AI applications require large amounts of storage and memory and differ in the type of processor used. These considerations will impact system bus size, speed, and compatibility requirements.

Edge Computing Has Allowed Organizations to Adapt to New Workflows

Organizations both large and small had to make a fundamental shift to remote work when COVID first struck. These transitions were in part successful due to the improvements already made to the distributed infrastructure. Many large organizations like Amazon and Dropbox plan to stick with remote work even after COVID because they see it as a necessary shift and not a momentary trend. In addition to overwhelming market pressures, these shifts have pushed most companies to prioritize edge infrastructure in the years to come.

Likely you’re part of this group of businesses looking to increase your edge infrastructure. Our team at Intequus can help you develop edge colocation infrastructure that optimizes the use of each component and is specific to your applications. Talk to a team member about your infrastructure needs today.

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