The increasing need to process data close to its source is driving the rapid adoption of edge computing models. Grand View Research has forecast that the global edge computing market will see a 37.4 percent growth rate through 2027 as organizations move more workloads from centralized data centers and cloud services to edge computing platforms.
Edge computing puts compute and storage resources near devices that collect and generate data to reduce the distance data must travel for processing and analysis. This approach increases performance and throughput, conserves network bandwidth, improves data quality and reliability, and overcomes weak or spotty Internet connections in remote locations.
Propeller Insights recently conducted a global survey of IT executives to determine why they are putting workloads at the edge. More than half (54 percent) said they need to control and analyze data locally, while 47 percent said that sending data to the cloud for processing created too much latency.
However, 67 percent said their teams had trouble installing the full compute, storage, network and security stack in the edge environment. Managing IT infrastructure across numerous edge sites also poses serious challenges, with 37 percent saying they lacked the resources or time to keep applications and infrastructure up-to-date.
Why Edge Computing
Edge computing represents a significant shift in the deployment of IT infrastructure. In traditional IT architectures, organizations consolidate resources in a centralized data center or the cloud to ensure the reliable delivery of applications and services. As the IT environment becomes increasingly distributed, however, physics comes into play. Transferring data from endpoint devices to a distant data center creates latency that hampers application performance.
In a landmark study, computer scientists at the University of California-San Diego and Google found that applications ran up to 20 percent more efficiently when the data they need to access is located nearby. Apps requesting data from remote cloud servers did not perform as well because they had to wait longer for the data they requested to arrive.
The performance gains enabled by edge computing have a real business impact. It enables organizations to leverage data collected and generated by Internet of Things (IoT) devices for real-time decision-making. It also supports latency-sensitive applications such as artificial intelligence (AI) and virtual and augmented reality.
How SirviS Can Help
Most organizations have well-defined processes for deploying applications in a corporate data center or the cloud. Those processes can easily be applied to one edge node.
However, edge computing models typically involve many nodes, which are often spread across broad geographies. How are IT teams going to implement workloads throughout your edge environment and maintain it over the long term? An edge deployment that is not operationally sustainable and scalable will incur high resource costs.
SirviS has extensive experience in the configuration, integration and rollout of IT solutions across geographically dispersed edge data centers. Our proven methodologies, disciplined project management practices and extensive field services organization enable us to deliver highly customized edge computing solutions anywhere in the world.
We also leverage our Global Integration Center to receive, stage and test equipment and custom configure hardware components to meet the most demanding requirements. We can even deliver fully populated cabinets to edge sites — ideal for retail, hospitality, warehouse, education and other use cases where onsite space is limited.
Edge computing is a key trend that is transforming how IT infrastructure is designed, implemented and managed. If your edge initiatives are hindered by lack of time or resources, SirviS can help. Let us deliver the edge computing stack across your extended enterprise.
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