World Model · podcast knowledge graph

An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708

2024-11-04 · 75 min · episode 708 · 13 entities

episode page audio

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    An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708
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  • → hosted by TWIML company
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    Feed author/publisher: TWIML

Entities found in this episode

concepts 5

  • mentioned Science concept
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    Feed category: Science
  • mentioned Tech News concept
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    Feed category: Tech News
  • discusses Science concept
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    evidence rules-v4
    Feed category: Science
  • discusses News concept
    0.40
    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
    0.40
    evidence rules-v4
    Feed category: Tech News

companys 4

  • mentioned TWIML company
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    Feed author/publisher: TWIML
  • mentioned Technology company
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    Feed category: Technology
  • discusses Technology company
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  • hosted by TWIML company
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    Feed author/publisher: TWIML

persons 3

  • mentioned Sunil Mallya person
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    An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708
  • mentioned Sam Charrington person
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    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
Today we're joined by Sunil Mallya, CTO and co-founder of Flip AI. We discuss Flip’s incident debugging system for DevOps, which was built using a custom mixture of experts (MoE) large language model (LLM) trained on a novel "CoMELT" observability dataset which combines traditional MELT data—metrics, events, logs, and traces—with code to efficiently identify root failure causes in complex software systems. We discuss the challenges of integrating time-series data with LLMs and their multi-decoder architecture designed for this purpose. Sunil describes their system's agent-based design, focusing on clear roles and boundaries to ensure reliability. We examine their "chaos gym," a reinforcement learning environment used for testing and improving the system's robustness. Finally, we discuss the practical considerations of deploying such a system at scale in diverse environments and much more. The complete show notes for this episode can be found at https://twimlai.com/go/708.