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02/08/2026 11:40 am
TL;DR: Centralized logging consolidates identity, cloud, endpoint, and application telemetry into one searchable store, reducing console-hopping and enabling cross-source correlation, normalization, and faster investigations, according to Panther. The governance question is no longer whether to centralize logs, but whether teams can scope, normalize, and retain them well enough to avoid building an expensive archive that still misses attacks.
NHIMG editorial — based on content published by Panther: What Is Centralized Logging? Benefits, Architecture, and Best Practices
By the numbers:
- 85% of organisations lack full visibility into third-party vendors connected via OAuth apps.
- Only 5.7% of organisations have full visibility into their service accounts.
- 71% of NHIs are not rotated within recommended time frames, increasing the risk of compromise over time.
Questions worth separating out
Q: How should security teams centralize logs across identity, cloud, and endpoint systems?
A: Start with the investigations you need to support, then map each log source to a detection or forensic purpose.
Q: Why do fragmented access logs weaken identity governance?
A: Fragmented logs weaken identity governance because they prevent teams from reconstructing access events into a reliable narrative.
Q: What do teams get wrong about centralized logging storage tiers?
A: They often treat storage as a cost exercise instead of an investigative design decision.
Practitioner guidance
- Define logging scope by investigation use case Map each log source to a detection, forensics, or audit need before ingestion.
- Normalize identity and cloud telemetry to one schema Adopt a common event schema for identity, workload, and endpoint logs so rules can be written once and reused across sources.
- Tier storage by investigative value Keep recent, high-value logs in hot storage, move rarely queried material to warm or cold tiers, and send compliance-only data directly to lower-cost retention.
What's in the full article
Panther's full article covers the operational detail this post intentionally leaves for the source:
- Step-by-step breakdown of collection patterns across DaemonSet, sidecar, and agentless logging architectures.
- Implementation details for OCSF-based normalization and rule portability across multiple telemetry sources.
- Tiered storage guidance for hot, warm, cold, and archive retention with cost and query tradeoffs.
- Platform-specific examples of detection-as-code, rule testing, and SIEM-style alert tuning.
👉 Read Panther’s article on centralized logging architecture and best practices →
Centralized logging: what it means for IAM, SIEM, and audit teams?
Explore further
02/08/2026 12:52 pm
Centralized logging is now an identity governance problem, not only a SOC architecture problem. When identity providers, workloads, and endpoint tools generate events in separate silos, the security team loses the ability to prove who did what, when, and from where. That makes logging foundational to IAM, PAM, and NHI accountability, not just detection. Practitioners should treat the log plane as part of access governance.
A question worth separating out:
Q: How do organisations know if centralized logging is actually working?
A: Look for faster cross-source investigations, fewer manual timeline reconstructions, and detection rules that still work when a source changes format. If analysts still switch between consoles to confirm basic facts, the logging architecture is not yet delivering operational value. A working log plane reduces friction across both response and audit workflows.
👉 Read our full editorial: Centralized logging is becoming the control plane for incident response
