Below is the list of blog posts with the “Log noise” tag.

Pre-SIEM log filtering and log reduction means dropping, trimming, deduplicating, or rerouting log events before they cross your SIEM’s ingest boundary. The work happens on the collecting agent or on a relay, not inside the SIEM. Most commercial SIEMs bill on the volume they ingest, in gigabytes per day or events per second, so every byte you remove upstream is a byte you never pay to index, store, or search.

Microsoft Sentinel charges by the gigabyte for most data you ingest into the analytics tier. To reduce Microsoft Sentinel ingest cost, drop events you never query, remove fields you don’t use, and route high-volume, low-value logs to the cheaper data lake tier. This article walks through how to do each of these with NXLog Agent configurations and KQL you can adapt for your environment. Lever Where it runs What it saves Trade-off Drop noisy events

Short answer: Splunk meters the raw bytes that reach its indexing pipeline, so you reduce Splunk ingest cost by stopping low-value data before that point. Fix noisy audit policies at the source, filter events by ID and pattern at the endpoint, remove fields you don’t search, collapse repeats, and route archive-only telemetry data to cheaper storage. Compression alone does not lower the meter. Splunk bills climb because every event arrives at full size, including the ones nobody searches.

Most security leaders can tell you their SIEM bill to the dollar. Far fewer can tell you, line by line, what they’re paying for. That’s a problem because in financial services, that bill grows faster than the security coverage it’s supposed to buy. Let’s break it down. The bill is a function of volume, and volume is not your friend Ingestion-priced SIEMs charge by how much data you send. That makes your security budget a direct function of log volume.

How a federal agency’s monitoring gaps turned a containable incident into a three-week nightmare In September 2025, CISA responded to a federal agency breach that security teams could have stopped in hours. Instead, threat actors roamed the network undetected for three weeks. The damage? Multiple compromised servers, web shells planted across the infrastructure, and a persistent foothold that took significant resources to remediate. The root cause wasn’t a zero-day exploit or sophisticated malware.

Do you ever feel like you’re drowning in data? From endpoint logs and firewall events to database auditing and cloud metrics, the sheer amount of data is overwhelming. While telemetry data is crucial for threat detection, incident response, and compliance, it also brings a major challenge: log noise. Log noise obscures meaningful security signals. If left unchecked, you risk increased false positives, overloading security tools, higher SIEM licensing costs, and, most importantly, SOC alert fatigue.