Metrics & Mayhem

Al Mann
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Metrics & Mayhem is a straight-talking podcast on leadership under pressure for leaders and teams in banking, finance, and software. Weekly Signal Drops deliver quick insight, with longer episodes when a topic needs room. Built from years of operations (keeping services running) and observability (understanding what systems are doing), the rule is simple: clarity beats noise. No jargon. No fluff. Just signals that matter, even when the dashboards look smug.

  1. ١١ أغسطس

    Wide Events: Observability 2.0, Without the Hype

    Everyone is talking about observability 2.0 and wide events. This is the plain-English version, and the honest part: they are powerful, and they are not new. I cover what a wide event actually is, why it answers the questions logs and metrics cannot, t...

    Wide Events: Observability 2.0, Without the Hype

  2. ٧ أغسطس

    You Don't See the Foundation: Why AI Ops Fails Before It Starts

    The demo shows you the tower, the agent that fixes the incident on its own. It never shows you the year underground that made it possible: the clean telemetry, the tags, the traceability. This Signal Drop is about why AI ops is only ever as good as the...

    You Don't See the Foundation: Why AI Ops Fails Before It Starts

  3. ٢٨ يوليو

    OpenTelemetry Profiles: The Fourth Signal, Explained

    Metrics, logs and traces tell you the box is hot. They cannot tell you which function is burning the CPU. OpenTelemetry Profiles, the fourth signal, finally can. In this Tech Tuesday, Allan Mann explains continuous profiling: what an OpenTelemetry prof...

    OpenTelemetry Profiles: The Fourth Signal, Explained

  4. ٢٤ يوليو

    The Gate Stays Human: Who's Accountable When AI-Ops Acts

    When can you let an AI agent act on its own in production, and when does a human have to stay on the gate? This Signal Drop gives you the whole AI-ops governance model in one line: you decide what to automate by blast radius, not by how confident the t...

    The Gate Stays Human: Who's Accountable When AI-Ops Acts

  5. ١٧ يوليو

    Quiet Isn't Good: How to Justify Observability Spend

    Your observability is working, nothing is on fire, and that is exactly when someone asks why you are still paying for all of it. This Signal Drop is about the prevention paradox: the better your monitoring works, the harder it becomes to fund, because ...

    Quiet Isn't Good: How to Justify Observability Spend

  6. ١٤ يوليو

    How Do You Observe an AI Agent? | Tech Tuesday 02

    AI agent observability is the missing camera on the agents now acting in your production systems. AI agents are moving beyond answering questions. They investigate incidents, call tools, analyse production data and, in some cases, apply changes. But wh...

    How Do You Observe an AI Agent? | Tech Tuesday 02

  7. ١٠ يوليو

    Signal Drop 23: The Curiosity You Stop Needing

    Good tools answer the question so fast you forget you were the one who asked it. Dashboards, runbooks and AI incident summaries are all useful, and all quietly retire the questions you used to ask yourself. Curiosity is a muscle: when your systems stop...

    Signal Drop 23: The Curiosity You Stop Needing

  8. ٧ يوليو

    What Is MCP? The Model Context Protocol, Explained | Tech Tuesday 01

    MCP, the Model Context Protocol, is the open standard for connecting AI models to your tools and data. In the first Tech Tuesday, we explain what MCP is, the problem it solves, and where it fits in 2026, in plain terms. Introduced by Anthropic in late ...

    What Is MCP? The Model Context Protocol, Explained | Tech Tuesday 01
مشاهدة الكل (٣١)

حول

Metrics & Mayhem is a straight-talking podcast on leadership under pressure for leaders and teams in banking, finance, and software. Weekly Signal Drops deliver quick insight, with longer episodes when a topic needs room. Built from years of operations (keeping services running) and observability (understanding what systems are doing), the rule is simple: clarity beats noise. No jargon. No fluff. Just signals that matter, even when the dashboards look smug.

المعلومات

  • صناع العمل
    Al Mann
  • سنوات النشاط
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  • الحلقات
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  • التقييم
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  • حقوق النشر
    © 2026 Al Mann
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    Metrics & Mayhem