Microsoft Sentinel Investigation Agent
Inside the architecture of an autonomous AI agent that investigates Microsoft Sentinel incidents end to end — how it plans, queries, validates, and reports.
Inside the architecture of an autonomous AI agent that investigates Microsoft Sentinel incidents end to end — how it plans, queries, validates, and reports.
What actually happens between a syslog daemon and the Syslog table in Log Analytics – DCR facility and severity filtering, the rsyslog and syslog-ng configs AMA installs, the localhost:28330 hop, TLS, forwarder sizing, and the commands to prove data is flowing.
Six advanced KQL operators every Sentinel analyst should know beyond basic filtering and joins – mv-expand, parse, bag_unpack, arg_max, materialize, and time-series anomaly detection.
A clear comparison of Microsoft Defender for Cloud and Microsoft Sentinel — what each product does, where they overlap, and how they work together in a mature security architecture.
A beginner’s guide to KQL covering filtering, aggregation, joins, and string operations — with practical examples using real Sentinel tables.
A structured, repeatable incident response workflow for Microsoft Sentinel — from triage and investigation through containment, documentation, and closure.
How to create and use Sentinel watchlists for dynamic allow-listing, IOC matching, and alert enrichment — with practical KQL examples and automation patterns.
How ASIM works in Microsoft Sentinel, the key schemas, how to use parsers in KQL queries, and how to write custom parsers for your own data sources.
How UEBA works in Microsoft Sentinel, what data it requires, and how to integrate it into detection and investigation workflows for measurably better outcomes.
A structured step-by-step career roadmap for becoming a proficient SOC analyst with deep Microsoft Sentinel expertise — built from real-world experience.
Free download — Microsoft Sentinel
Production-tested queries for detection, threat hunting & cost optimisation. Ready to copy-paste into Sentinel.
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