# Avoid the Machine Learning Hype – Casey Kindiger – Ep151

Page: https://stenobird.com/podcast/tech-interviews/avoid-the-machine-learning-hype-casey-kindiger-ep151
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Podcast: [Tech Interviews](https://stenobird.com/podcast/tech-interviews)
Published: 2021-02-17T00:00:00+00:00
Episode link: https://soundcloud.com/techstringy-580399274/avoid-the-machine-learning-hype-casey-kindiger-ep151
Audio file: http://www.podtrac.com/pts/redirect.mp3/feeds.soundcloud.com/stream/986188267-techstringy-580399274-avoid-the-machine-learning-hype-casey-kindiger-ep151.mp3
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Duration seconds: 1981

## Resource

Moving beyond rules-based IT operations requires a strategic shift from simple threshold alerts to intelligent, data-driven AIOps. This discussion explores how to leverage machine learning without falling into the trap of hype or excessive manual data munging.

## Highlights
- Main idea: AIOps is a cultural transformation, not just a technology upgrade, requiring buy-in across the entire organization
- Failure mode: Relying on fixed, rules-based thresholds fails to scale with the increasing complexity of modern enterprise data
- Practical takeaway: Focus on existing business KPIs and priorities rather than trying to invent overly complex new metrics
- Failure mode: Avoid architectures that require manual data munging or constant manual updates to models at every learning step
- Practical takeaway: Empower 'citizen data scientists' within IT teams to interact with and influence machine learning models without needing PhDs

## Topics

AIOps, Machine Learning, IT Operations, Data Science, Enterprise Technology, Digital Transformation, Automation, Data Analytics

## Chapters
- 1:00 — Introduction to Casey Kindiger: An introduction to the CEO of Grokstream and his background in IT process automation.
- 3:20 — Defining AIOps: A breakdown of what AIOps actually means and how it differs from traditional operations.
- 5:50 — The Limits of Rules-Based Systems: Why fixed thresholds and encoded responses are insufficient for modern telemetry data.
- 8:10 — The Failure of Manual Signatures: Discussing why manual updates and signature-based approaches cannot keep pace with rapid change.
- 10:40 — Complexity as a Driver for Change: How the massive volume of underlying data is forcing a shift toward intelligent analytics.
- 13:20 — Strategies for Implementation: Practical tips for aligning AIOps initiatives with existing business priorities and KPIs.
- 15:40 — The Cultural Shift: Addressing the human element of AIOps and managing the transition of IT workloads.

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## Transcript

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