Open in new tab

Two Industry Analysts Discuss Managing Multi-Cloud Complexity Across the Globe

As multi-cloud adoption expands across the world, international companies need to consider how globalization affects business ecosystems and hybrid IT complexity.

Digital transformation has heightened the focus on data as value, so businesses need to reevaluate the legal and logistical obstacles that come with the global distribution of data and determine what infrastructure will be required to make it work. Dana Gardner, Principal Analyst at Interarbor Solutions, sits down with leading IT industry analysts for his BriefingsDirect Voice of the Analyst podcast series to wrestle with the mounting complexities businesses face as they transform their IT strategy.

To tackle the implications of globalization, Gardner spoke with Peter Burris, Head of Research at Wikibon in Palo Alto, CA. To begin, Burris breaks down three main concerns that companies should be weary of when adjusting their IT strategy for globalization: latency, privacy, and control. Latency and bandwidth.

In a digital world, it's easy for businesses to forget that the complex physics of cloud computing on a global scale -- moving data of any size across different regions -- can be extremely expensive due to bandwidth costs and latency issues. Factoring costs and where they wanted to run particular applications into a global strategy becomes complicated when a service is being consumed thousands of miles away from where the data resides.

Gardner suggests that if it requires substantial heavy lifting to make bandwidth capable, international businesses might consider sticking to a private cloud or on-premises approach with a small, local data center. Burris identifies two architectural means of achieving this approach: edge centers, where data processing can be closer to the source for lower storage and processing cost, or a true private cloud.

Läs hela artikeln →

Läs nästa artikel

Top AI, Machine Learning and Analytics Trends for 2019 and beyond

Läs nästa: Top AI, Machine Learning and Analytics Trends for 2019 and beyond