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Phil Alsop, Editor of Digitalisation World asks Aad Dekkers, Scale Computing how hyperconverges are addressing the developing edge market? Scalability is the prime mover when it comes to hyperconverged technology bringing benefits to edge computing applications.
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Enterprise customers are not looking to buy artificial intelligence or machine learning technology, but are seeking management tools to simplify IT Operations and DevOps. Hence, we can measure the success of AI/ML-driven management technologies based on their ability to free up the 25% of development- and 50% of IT operations resources that are typically absorbed by the release process and by ongoing application and infrastructure operations.
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VSA by Kaseya enables Community West Credit Union to manage and monitor systems remotely. The Credit Union has been using VSA for three years and it has helped in saving the time of the employees with remote monitoring. VSA by Kaseya also helps the Credit Union with scheduling the policies to ensure compliance standards are met.
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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/
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Learn how AIOps will help US Bank increase automation across the tool chain by analyzing large, monitoring-driven data sets. US Bank shares how they have so much data to get through that the root cause correlation is a large part of the bank’s triage process today. With the help of automation, US Bank envisions that the resolution side will be more effective, delivering better up time and improving customer experience.
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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.
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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.
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Justin Martin, lead of capacity management team at Cerner, talks about his goals for the capacity management team – staying ahead of the business needs.
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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.
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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.
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