Forensic investigations rely on facts, not assumptions. Yet one of the biggest pain points is incomplete or inconsistent data. By the time anomalies trigger an alert, key traces may already be gone. Systems roll logs too soon. Audit data is scattered across services. Cloud storage policies purge history before anyone thinks to check. Each gap erodes the ability to prove what happened and when.
Another common pain point is data integrity. In many systems, logs can be altered—sometimes by accident, sometimes by intent. Without tamper-proof retention, forensic evidence is open to challenge. Investigators lose time verifying whether records are trustworthy instead of analyzing what the records show.
There is also the problem of correlation. Modern applications span dozens of APIs, containers, and functions. Events from different subsystems need to line up on a precise timeline. If one service logs in local time, another in UTC, and a third batches updates out of order, reconstruction becomes guesswork. Forensic investigations stall.