What is AI Ops?

AlOps Enables Continuous Insights

Why AI Ops?

What pain are we trying to solve?

Data sources are deployed on a diverse and ever-growing set of platforms/apps.

Meeting regulatory standards can’t be done quickly and easily executed.

Can’t meet reliability, performance, and experience quality expectations.

Problems hop from team to team; lack of collaboration.

Teams struggle to isolate cause & chase false alarms.

Inefficient war rooms, delayed Mean Time To Identify (MTTI) / Resolve (MTTR).

The benefits it provides:

Early detection for increased awareness and opportunities for pro-active automated corrective action.

Reduce MTTI/MTTR incorporating service context and operations data into probable cause analysis.

Combine data from ITSM, ITOM and 3rd parties for metrics, events, and topology.

Improve real-time topology visibility for increasingly dynamic environments including multi-cloud and container resources.

Minimizing Toil on Critical Staff by removing unnecessary tasks.

How do we measure Success?

Key metrics for AIOps

  • Improved User Experience: Quickly respond to operational issues and reduce event noise by up to 90%.
  • Reduced downtime: Using automation and predictive capabilities to take action before
    a service impact occurs.
  • Increase speed of resolution: Leading-edge AlOps and machine learning proactively detects and analyses
    events to determine root cause.
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Data/People/ Culture

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The right use cases

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Engaging with the business/customers

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The right technology

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Gain trust in the Al

KTSL’s AI Ops Report

Our AI Ops reports is now available, based on a survey of 400 senior IT leaders from large financial service companies across the UK and US, uncovers how companies like yours are leveraging the power of AIOps.

Click below to receive a copy of the report.

Request the report
KTSL
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