Leveraging AI with colocation and edge computing

Simultaneously, the ever-expanding demand for powerful data storage and processing solutions is pushing the limitations of data centers, and while we continue to witness organizations adopting evolving digital technologies such as artificial intelligence, IT infrastructures must keep up and adapt to ensure scalability, swift responses, & dependability.

Colocation offers a compelling solution by providing a dependable hosting environment for your essential servers, storage, and Internet infrastructure.

To fully take advantage of the capabilities AI has to offer, organizations are turning towards colocation and edge computing infrastructures to locally process and manage their massive amounts of data.

The relationship between edge computing and colocation

Colocation and edge computing are two interconnected components of modern IT infrastructures that when combined, amplify data processing capabilities. Colocation enables organizations to place their servers, network equipment, and storage in data centers provided by their solution providers allowing for easy connectivity to various telecommunications and network service providers.

Edge computing processes data in close proximity to the original data source  – rather than moving and processing data in a centralized data center. Doing so increases speed and reduces latency, all while bolstering the real-time application performance. Positioning colocation centers at the network’s edge provides the ideal environment for edge computing by offering the physical infrastructure needed to support the localized processing of data. Businesses aiming to improve IT operations can do so by leveraging the symbiotic relationship between colocation and edge computing, that combined provides the necessary infrastructure required to handle the demands of AI and machine learning applications.

Colocation and AI workloads

Because colocation provides the benefits of on-premises IT infrastructure without the operational demands that come from maintaining a physical data center, businesses are turning to these services to address AI workloads. By offering a solution that incorporates adaptability and responsiveness, colocation guarantees business continuity – a must-have to keep up in a fast-paced digital landscape. Combining compliance with industry standards and regulations along with offering 24/7 security surveillance and access control, colocation not only provides operational resiliency but peace-of-mind.

AI workloads demand high-performance computing, which is often beyond the traditional scope of cloud solutions. Because colocation allows companies the ability to leverage the cloud alongside the resiliency of on-premises solutions, the solution provides a balanced approach to managing IT infrastructure. Colocation supports AI workloads through cooling systems, customization, and power infrastructure.

High-power computing needed for AI generates significant heat, necessitating strong and reliable cooling solutions such as ambient and mechanical systems found within colocation facilities. These same facilities offer revolutionary power distribution systems that incorporate redundancy – ensuring minimal waste and sustainability through guaranteeing equipment used receives the exact amount of energy needed, no more no less.

Edge computing and AI workloads

Edge computing enhances AI applications by processing data close to the data source, reducing latency and securing the functionality of real-time AI applications. Proximity allows for faster processing while also conserving bandwidth, as less data will need to be transmitted to central data centers. Additionally, edge computing facilitates the rapid analysis and extraction of data insights which proves crucial for AI applications relying on quick decision-making. In addition to the speed that edge computing provides, it also ensures compliance with privacy and high security standards. According to Axios, 75 percent of data computing is moving to the edge. Edge computing providers also reported to Axios of the high demand for their services from organizations either operating in remote locations or requiring specific security needs.

As businesses navigate the complexities of digital transformation, colocation emerges as a strategic asset, offering the agility, security, and scalability necessary to support high-performance AI workloads. With the remarkable expansion of AI adoption across industries, the fusion of colocation services and edge computing infrastructures will continue to play a pivotal role in the evolution of IT strategies, enabling organizations to harness the full potential of AI while maintaining operational efficiency and sustainability.

About the author

Roger Brulotte is the CEO of Leaseweb Canada, formerly known as iWeb Technologies, Inc. With over 20 years of diverse leadership experience in the IT infrastructure and telecommunications industries, he has held several key executive positions in the field. Prior to joining Leaseweb, he was the principal and general manager of Zayo Group, a company that specializes in providing light-speed data transmission infrastructure, including fiber and bandwidth connectivity, in North America and Western Europe. He has also served as the vice president of Sales & Strategic Alliances for Root Data Center and as the general manager of Cologix Canada, a network-neutral interconnection and data center company.

Article Topics

AI  |  AI workloads  |  colocation  |  edge computing  |  Leaseweb