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Observability vs. monitoring: what’s the difference?

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

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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The importance of AIOps within Value Stream Management

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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Telecom: Enabling Automaton Everywhere through AI and Analytics

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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How AIOps is driving digital transformation

In the current digital age, any successful organisation will understand that business growth requires managing dynamic infrastructures and embracing digital transformation. By Ali Siddiqui, Chief Product Officer, BMC Software

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Understanding legacy infrastructure by looking at the pyramids

When you look at the Saqqara Necropolis, the oldest of Egypt’s pyramids, do you immediately discard it as an irrelevant relic? Not at all. You admire it for the architectural skill involved in its construction, and the story behind its eternal beauty. By Marc Zottner, Field CTO, VMware Tanzu

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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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