Advanced Computing in the Age of AI | Tuesday, May 17, 2022

Multi-Cloud Begets Confusion, Calls for Automation 


The embrace of multiple public cloud providers as a way of avoiding vendor lock-in and manage costs has added another layer of complexity to the management of IT infrastructure already calibrated to a fine edge. That has created an opening for automation tools in general and artificial intelligence technologies in particular to help weary administrators manage multiple cloud and hybrid infrastructure.

In response, more than three-quarters of executives responding to a new vendor survey said they want to integrate AI into their multi-cloud strategies.

The survey of more than 1,000 executives by cloud management software vendor BMC concludes that the rise of multi-cloud strategies means "the traditional way of looking at IT infrastructure simply does not work anymore."

One reason is confusion over how enterprises define multi-cloud: Just over half of those polled defined it as including a combination of either public or private clouds along with on-premise infrastructure. (That is also a widely accepted definition of "hybrid clouds".) Meanwhile, 23 percent of respondents said multi-cloud includes all three: public and private clouds along with their own datacenters.

The confusion may explain why 40 percent of executives polled said they are not sure how much their company is spending on cloud services.

The company argues that the added administrative complexity of multiple clouds amplifies existing challenges ranging from data security and access along with cost and performance. "IT leaders must consider new ways to manage multi-cloud environments to ensure they are getting the expected benefits from public cloud in terms of cost savings, automated performance optimization, and increased security and governance," Bill Berutti, president of BMC's Enterprise Solutions unit, noted in releasing the survey results on Tuesday (Nov. 14).

Hence, BMC and other infrastructure vendors are advocating software-defined automation tools such as machine learning to manage multi-cloud infrastructure. Along with automating multi-cloud management, the company argues that AI and machine learning can help cut costly redundancies while increasing visibility into cloud assets.

While automation is seen as the leading multi-cloud challenge, resource utilization and reducing cloud consumption costs also were cited along with finding skilled IT administrators.

Given the survey's consensus that greater automation and other approaches are needed to manage multiple clouds, respondents also said they expect to spend invest in heavily in data security over the next two to three years. Other priorities include capacity optimization, performance analytics and cost containment.

Cost optimization was most often cited reason for using more than one public cloud vendor followed closely by the maintaining IT agility and mitigating the risks of dependence on a single cloud vendor.

The full BMC report is here.

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

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