Topic starter
11/11/2026 6:05 pm
TL;DR: Kubernetes telemetry is mostly low-value noise, Apica reports, with repetitive health checks, scrapes and duplicate errors overwhelming the signals practitioners actually need. That forces platform teams to treat log filtering and redaction as governance controls, not just cost optimisation.
Editorial analysis by NHI Mgmt Group, based on content published by Apica: “Cut Kubernetes Log Volume 85% with Zero Data Loss”.
By the numbers:
- Up to 85% of typical Kubernetes log volume is droppable or duplicate noise.
Key questions
Q: Why do repetitive Kubernetes probes create observability noise?
A: Repetitive Kubernetes probes create observability noise because liveness, readiness and startup checks run on a fixed cadence and can generate the same success, failure or timeout messages over and over.
Q: What is log deduplication in Kubernetes telemetry?
A: Log deduplication in Kubernetes telemetry is the process of collapsing many identical events into one representative record with a count or sample set.
Q: How do Kubernetes logs leak credentials into observability pipelines?
A: Kubernetes logs leak credentials when applications, sidecars or admission webhooks write secrets, tokens or headers into stdout, stderr or structured events that are then shipped to collectors and observability platforms.
Practitioner guidance
- Implement upstream log filtering Drop repetitive probe and scrape events before they reach premium ingestion tiers, and keep the rule set centrally managed so it can be changed without touching applications.
- Redact secrets at the boundary Scan log streams for API keys, passwords, tokens and other identity-bearing values before forwarding data to analytics, storage or SIEM destinations.
- Collapse duplicate events into counters Replace repeated identical errors with a counted record so investigators retain the occurrence pattern without paying to store thousands of duplicates.
Bottom line: Kubernetes telemetry can overwhelm observability platforms with noise, and the cost of retaining every line often exceeds the investigative value of most events.
Glossary terms: Log Deduplication, Telemetry pipeline, Workload Identity, Service Account
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11/11/2026 6:06 pm
Observability cost is now a governance problem, not just an engineering nuisance: when Kubernetes produces repetitive probes, scrapes and duplicate errors, the organisation pays to retain low-value data at the same rate as critical security signals. That distorts priority, because the most expensive parts of the pipeline are often the least useful for detection or forensics. Platform teams should view telemetry economics as part of control design, not as a separate FinOps concern.
A few things that frame the scale:
- Red Hat’s Kubernetes Security Report found that nearly 9 in 10 organizations had at least 1 container or Kubernetes security incident in the last 12 months.
A question worth separating out:
Q: What should teams prioritise first in Kubernetes log management?
A: Teams should prioritise where log volume is created, starting with workloads, sidecars, ingress layers and control-plane components that emit the most repeated or low-value events. That is where log level, sampling, filtering, redaction and deduplication have the biggest effect before data reaches the pipeline or SIEM.
👉 Read our full editorial: Kubernetes telemetry noise drives up cost and compliance risk