Thursday, 5th August 2021
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Tackling cloud complexity with the right tools

  • Published on 03 Aug, 2021 in

Securing the right observability tools will help enterprises get control over their software and spot problems before they become a more widespread issue. By Stela Udovivic, Director of Product Marketing, VMware Tanzu

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Lift-and-Shift Cloud Migrations

  • Published on 03 Aug, 2021 in

The good, the bad, and how to avoid the ugly By Ricardo Negrete, Sr. Director Services and Technology, Virtana.

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Observability vs. monitoring: what’s the difference?

  • Published on 03 Aug, 2021 in

One of the more delicate debates in the DevOps world is what observability has to do with monitoring. By Chris Tozzi,, Sumo Logic.

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The importance of AIOps within Value Stream Management

  • Published on 03 Aug, 2021 in

IT organisations today are charged with both running the business as well as reinventing it. By Gaurav Rewari, CTO and GM of AI and VSM at Digital.ai

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AIOps: Moving beyond the trigger-driven alerts model with deep learning

  • Published on 03 Aug, 2021 in

The standard application of AI to IT operations is to mitigate the “overload of red alerts”: too much noise, not enough signal. This is a valid concern as IT estates grow larger, but the emphasis on individual overload does nothing to address the underlying process issue. By Shaun McGirr, AI Evangelist, Dataiku

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Telecom: Enabling Automaton Everywhere through AI and Analytics

  • Published on 03 Aug, 2021 in

As operators drive to increase the velocity and scale of Service Assurance processes across their complex, converging enterprise IT and network domains, automation has become a critical priority. By Ian Russ, EMEA Chief Architect within BMC Software’s Office of the CTO.

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Latest Video

How to Adopt an AIOps Strategy: CA Interview with Chris Kline

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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