Azure Monitor and Log Analytics Workspaces: Observability on AZ-104

What is this page about?

A study guide to Azure Monitor observability as tested on AZ-104, covering the Monitor architecture (metrics versus logs versus alerts), Log Analytics workspaces as the destination for diagnostic logs, diagnostic settings as the routing layer, KQL fundamentals, and alert rules with action groups and dynamic thresholds. It also covers workbooks and dashboards, pre-built Insights, alert processing, data collection rules and the modern agent, and Sentinel versus plain Log Analytics, noting monitoring is a comparatively easy 10-15% domain candidates should not skip.

What has been corrected on this page?

Every accepted correction to this page is recorded with the exact change, so readers can see how the page improved over time.

1. 11 July 2026 · corrected by Melik Can Sariyer

   3 flagged issues verified, same systematic fabrication pattern: a quote attributed to Charity Majors (real Honeycomb CEO, with an implausible 'frequent Microsoft observability collaborator' descriptor given Honeycomb competes with Azure Monitor) had no locatable source and was de-attributed; a recurring unverified Heineken IoT brewery case study (reused with different framing than 2 sibling articles) had no locatable source and was generalized; a quote attributed to Mark Russinovich had no locatable source and was de-attributed.

   Before

   "Most monitoring failures are not data failures -- they are routing failures..." -- Charity Majors, CEO of Honeycomb and frequent Microsoft observability collaborator [...] The Heineken IoT brewery telemetry, publicly described in Microsoft case studies, uses dynamic thresholds on flow-meter metrics... [...] Mark Russinovich, Chief Technology Officer at Microsoft Azure, has written that "monitoring cost is the single most underestimated category in cloud budgeting"

   After

   Most monitoring failures are not data failures, they are routing failures... [de-attributed] [...] A common real-world example: IoT telemetry from industrial flow-meter sensors, where dynamic thresholds detect equipment anomalies... [named-company case study generalized] [...] Monitoring cost is widely considered one of the most underestimated categories in cloud budgeting... [de-attributed]

   Why: De-attributed an unverified quote credited to Charity Majors with an implausible 'frequent Microsoft observability collaborator' descriptor (Honeycomb competes with Azure Monitor), generalized a recurring unverified Heineken IoT brewery case study (reused with different framing across sibling articles) with no verifiable source, and de-attributed an unverified quote credited to Mark Russinovich.

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