WWT's Derek Pounds is featured in this article from Insight.Tech, discussing the Advanced Technology Center and our work with partner Intel.

by Pedro Pereira

Hybrid cloud environments are the new normal. Currently, 82 percent of organizations have hybrid strategies combining public and private clouds with on-premises infrastructure. But now those environments increasingly include edge computing as well.

Edge computing places hardware as close to data sources as possible. Why? "The main motivations are data latency and data sovereignty," explains Derek Pounds, cloud consultant at solutions provider World Wide Technology (WWT).

In an edge-to-cloud context, this means bringing the capabilities of the public cloud into local environments. Specifically, companies can leverage platforms like Microsoft Azure Stack, AWS Outposts, and Google Anthos to deploy these cloud providers' services on-site.

While this arrangement can provide powerful benefits, putting together an edge-to-cloud architecture can be a monumental undertaking. But with the right mix of business case assessments, careful testing, and the latest in pre-validated solutions, companies can smooth the path to success.

Why the Edge Matters

The growth of enterprise Internet of Things (IoT) applications is a primary driver behind the emergence of edge-to-cloud architectures. These IoT applications often require real-time or near-real-time processing.

Examples can be seen in telemedicine, smart cities, oil and gas, and other critical functions that demand reliable connections and the ability to respond immediately to a problem. If data must travel hundreds of miles to a cloud, latency is inevitable; hence the need to keep data close to sources and users.

And because it keeps data at local sites, the edge also enables compliance with data sovereignty requirements. "Where data can't leave a particular site, data sovereignty becomes very important, especially with EU-based data that can't move outside of country locations," says Pounds.

Sovereignty also matters at a more granular level: Companies want to protect their data. Thus, the most sensitive data--such as proprietary designs--is typically kept on-premises with access granted to the narrowest set of employees. Other types of data can stay on-premises or move to the cloud.

Taking the time to understand the business is key to deciding "what portions of the business we can move to the cloud or how we can move them to the cloud in stages or phases" to ease the transition, Pounds explains.

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