EMA Blog: Business Intelligence and IT Management

OpenManage Enterprise is a big deal, but underrated: OpenManage Enterprise is the new infrastructure automation platform that could unlock the private and hybrid cloud for Dell. Deploying Dell infrastructure through a simple YAML file is within reach.

The EMA Top 3 report for Container Management and DevOps in Production and at Scale is a curated collection of a large number of data points that reflect individual priorities, pain points, technology adoption patterns, requirements, opinions, and so on, of 300 enterprises. It then dives deeper into these individual data points to provide readers with enough context to inform their technology selection process to some degree. However, each reader needs to pick out the nuggets that are the most relevant to him or her and then draw her own conclusions. Look at it this way: the EMA Top 3 polls 300 of your peers on 58 container and DevOps related questions and you can learn from the answers without having 300 separate conversations.

Why Machine Learning Diagnoses Cancer but Can’t Run our Hybrid Cloud

Digital attackers in 2018 need to focus on one key challenge: “how do I deliver the best possible value to my clients, without significantly increasing cost.“

For readers who would like to see what happened to our 2017 predictions, please take a look. Jens Soeldner and the EMA Team sat down again this month to look into the crystal ball for 2018.

“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.'