Watch replay here: https://info.dynatrace.com/apm_wc_ai_webinar_na_registration.html Monitoring with Artificial Intelligence [Webinar] The modern technologies that accelerate speed of innovation, enable hyper-scale deployments, and promote business agility also make monitoring applications the same old way too difficult and labor-intensive. While some APM tools have gotten pretty good at correlating metrics, they still leave the heavy lifting to you. You’re left configuring thresholds, figuring out what went wrong and why — it’s more than a human can handle manually. Only automated AI-powered monitoring can keep pace with the speed at which your team is innovating. Daniel Kaar, Technology Strategist at Dynatrace, discusses how monitoring with AI can help you, including: • Why AI is necessary in today’s world of complex environments and deployments • Why current monitoring is not sufficient • How AI operates when doing root cause and business impact analysis AI does all of the discovery and analysis that takes teams of experts hours or days, in milliseconds — more accurately, and using fewer resources

1. Stephen Lamont
@stevelamont26
stephen.lamont@dynatrace.com
Monitoring with Artificial Intelligence
June 28, 2017
Daniel Kaar
@d_kaar
daniel.kaar@dynatrace.com

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broad
deep

8. Cloud
OS, Disks
Containers, Processes,
Logs
Application- & Webserver
Mobile*
Services
Network
Browser
3rd parties
FullStackDiscovery,Modeling&Analytics

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Expert Knowledge
Strong Relationship
Response time slow down impacted by CPU saturation
Potential Relationship
Response time slow down potentially impacted by code deployment
No Relationship
CPU saturation not impacted by load drop

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Levels of Impact
▪ Infrastructure – e.g. CPU, memory, IaaS service…
▪ Service – e.g. application code, database statements…
▪ Application – real users, outages…

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Problem Analysis

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What problem does our AI solve?

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Correlation Causation

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dynatrace.com/trial

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dynatrace.com/demos
‘Monitoring Redefined‘

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26. www.dynatrace.com
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