EMA Blog: Business Intelligence and IT Management

“Machine learning (ML) today is frustrating. There is so much potential and the algorithms are all there, but I just do not know how I can leverage it for my organization,” says the CTO of a major professional services firm. “My CEO wants me to ‘leverage ML to lower OPEX and differentiate our service offerings, but there is nothing out there in the market that would allow me to get this done in a manner that has a high probability of success.” Then of course he asks me what I would do and where I would start, because the guy with “Machine Learning and AI” in his job title must know for sure…

What should machine and artificial intelligence (ML/AI) do for IT operations, DevOps and container management? The following table represents my quick outline of the key challenges and specific problem ML/AI needs to address. The table is based on the believe that ML/AI needs to look over the shoulder of IT ops, DevOps, and business management teams to learn from their decision making. In other words, every virtualization administrator fulfills infrastructure provisioning or upgrade requests a little bit differently. Please regard the below table as a preliminary outline and basis for discussion. At this point, and probably at no future point either, I won't claim to know the 'ultimate truth.'

What should machine and artificial intelligence (ML/AI) do for IT operations, DevOps and container management? The following table represents my quick outline of the key challenges and specific problem ML/AI needs to address. The table is based on the believe that ML/AI needs to look over the shoulder of IT ops, DevOps, and business management teams to learn from their decision making. In other words, every virtualization administrator fulfills infrastructure provisioning or upgrade requests a little bit differently. Please regard the below table as a preliminary outline and basis for discussion. At this point, and probably at no future point either, I won't claim to know the 'ultimate truth.'

Why are there still so many repetitive tasks in data center and cloud management today? Why does application management still contain so many manual steps? Why do most organization still suffer from automation and monitoring silos that prevent them from avoiding preventable application outages and service degradations?

“Oh, I’m not coming to VMworld this year, we are at Jenkins instead.” This is a sentence I’ve heard quite a few times now from vendors that I’m used to seeing at VMworld and it makes me wonder what’s going on.

(You can read more about the content of the EMA Top 3 - Enterprise Decision Guide in my first Post)

(Click here to jump to the next part and read about how EMA selected its Top 3 products)

“It feels like magic but it is technology,” and “we will help transform every company into a software company,” were the two quotes by Michael Dell that best summed up the spirit of  Dell EMC World 2017. These statements show the genuine excitement of a seasoned tech executive to attack the next challenge of his career: merging the Dell EMC brands -Pivotal, VMware, RSA, SecureWorks, and Virtustream- into one highly differentiated IT powerhouse.

Traditional IT infrastructure monitoring focuses on hypervisor hosts, storage and VMs. Application impact is tracked through vSphere resource tagging. This simple and mostly static drilldown approach to full-stack monitoring no longer works for modern microservices based computing.

"Today, a dev team leveraging Kubernetes containers can get a cloud app up in minutes." This statement by Arvind Krishna, IBM’s GM for Hybrid Cloud, at the beginning of his InterConnect 2017 keynote should have received a lot more recognition than it did. This one sentence shows the fundamental shift in IBM’s strategy, away from the old Tivoli-centric IT ops company and toward a modern DevOps-focused organization that is looking for differentiation up the stack. Today’s IBM encourages developers to deploy entire application environments without IT administrators even being aware.