Jason Edwards
Reliable detection and response begin with visibility that teams can trust under pressure. This chapter explains why telemetry is the foundation of evidence-based security operations, emphasizing attribution, correlation, and reconstruction as the practical outcomes that separate usable logging from raw data volume. It defines what “good telemetry” looks like in operational terms, including consistency, timeliness, completeness, integrity, and usability, and ties those characteristics directly to faster triage and more defensible incident narratives. The chapter then walks through the core log source domains—endpoint, network, identity, and cloud control plane—showing how each answers a different investigative question and why single-source visibility is fragile. It details the engineering considerations that make telemetry usable at scale: resilient collection pipelines, normalization that preserves meaning and provenance, and retention strategies aligned to investigative reality rather than convenience. Throughout, it highlights common failure modes such as latency creep, partial drops, and parsing regressions, and explains how to detect and manage gaps before they become incident-critical blind spots. Finally, the chapter covers operational ownership, access control, and integrity protections needed to keep telemetry trustworthy in adversarial conditions. It explains how to structure source and pipeline responsibilities, define measurable service expectations, and govern changes so detections do not silently fail. It also shows where AI can responsibly improve telemetry operations through enrichment, entity resolution, and quality monitoring, while requiring human-in-the-loop approval boundaries, explainability, and auditability to avoid false confidence and drift.