Stephane Zantain, Head of Customer Engagement, Europe, at Capgemini Invent, explains why customer engagement depends on being able to recreate one-to-one relationships despite complex touchpoints.
Cerner has applied DevOps principles to their capacity management practice – and call it BizOps. This new BizOps model allows them to better service their internal clients – faster, more accurate recommendations that have built the trusted relationships needed for fast, efficient service.
Justin Martin, lead of capacity management team at Cerner, talks about his goals for the capacity management team – staying ahead of the business needs.
Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise. By moving down the road of machine learning, LinkedIn can now do anomaly detection using machine learning models.
CA Technologies’ Chris Kline shares how to adopt an AIOps strategy in a DevOps world. Chris shares how AIOps enables a move away from siloed operations management and provides intelligent insights that drives automation and collaboration for continuous improvement. Since AIOps leverages big data, data analytics and machine learning to provide insight and enable a higher level of automation, no longer does IT Ops need to depend extensively on human operators for the management tasks that modern infrastructure and software require.
William Hill shares how AI and machine learning play a massive role in self-healing and the transformation that is taking place. Five years ago, companies would not be willing to even trust machines to start to make that decisional data. Today, it’s absolutely key to get visibility of all the piece of the jigsaw before making decisions on what can affect critical business services. AI helps analyze that metric explosion and make sense of it, because humans are limited by that. Not just understanding what the root cause of the problem is, but actually processing all this data coming through. https://www.williamhill.com/
