Managing Latency-Sensitive Applications in Hybrid, Multi-Cloud Environments

The strategic trends -- on both the infrastructure and workforce front -- are being compounded by the different categories of data that applications are working with across different industry segments.
A growing number of organizations are exploring the the state of latency sensitive applications as workforces becomes more distributed and infrastructures become more fragmented.
Mining facilities that are in remote locations must still carefully monitor the structural integrity of their sites to maintain safe working environments, even when local infrastructure and connectivity can be best described as "iffy."

A growing number of organizations are exploring the the state of latency sensitive applications as workforces becomes more distributed (since the sudden WFH move made by many in 2020 is likely to stick around for the long-term) and infrastructures become more fragmented (as data centers, old mainframes, private clouds and multiple public clouds emerge as enterprise infrastructure coexist for the foreseeable future). These were among the conclusions from a recent CIO.com Chatham House Rule virtual roundtable that featured experts from Lumen and technology leaders from around the country.

I co-hosted the event with Jonathan Barton and Mateen Fikree from Lumen, who offered excellent direction and strategic perspectives on the fate of latency-sensitive applications in today’s complex, dynamic environment. Below are the issues that stuck with me over the course of our conversation:

The strategic trends -- on both the infrastructure and workforce front -- are being compounded by the different categories of data that applications are working with across different industry segments. We had a broad array of verticals represented around the room, including healthcare, financial services, mining, manufacturing as well as the public sector. It was interesting to see how each of these environments was dealing with time-sensitive applications that involve the integration of structured data, unstructured data...and information generated by operational systems (OT)...or IoT data...to manage and monitor time sensitive activities.
We discussed many operational scenarios that bring the importance of latency-sensitive applications into sharp relief. Monitoring patient data from remote locations and providing timely diagnostic analysis that drive immediate corresponding actions can be hampered by latency that results in tragic human consequences. This is especially true as the industry moves to take care of people from home (using telemedicine) and take pressure off of stressed medical facilities. In manufacturing, sensors that measure the performance of equipment must be integrated into life-cycle management applications that identify problems before lines of production are interrupted by breakdowns that can be avoided by continuous and automated data analysis. In financial services, brokers cannot afford to trade behind the market, even if they are working from home. Mining facilities that are in remote locations (the outer edges of the world) must still carefully monitor the structural integrity of their sites to maintain safe working environments, even when local infrastructure and connectivity can be best described as "iffy."
As a growing number of key enterprise elements expand away from each other, we discussed how "edge computing" is emerging to push processing capacity closer to where it is needed. We discussed how edge computing allows the digital laws of "data gravity" to coalesce around situations and circumstances in which they are needed. Jonathan and Mateen both described the explosion of use cases over the past few years, as wide area networks (WANs) play a growing role in connecting hybrid, multi-cloud environments by pushing compute capacity to where it is needed in an automated and intelligent manner.

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