Breaking: Grafana Cloud Introduces Adaptive Logs Drop Rules in Public Preview
Grafana Cloud has released a public preview of Adaptive Logs drop rules, a new feature that lets platform and observability teams define custom rules to drop low-value logs before they are ingested into Grafana Cloud Logs. This eliminates noisy log lines that inflate storage costs and clutter dashboards.
“For years, teams have struggled with throwaway health checks, forgotten DEBUG logs, or verbose INFO logs from seldom-used services,” said John Lam, Senior Product Manager at Grafana Labs. “Now they can set a single rule to drop those logs entirely, without touching infrastructure change management or asking every service to reconfigure their logging.”
Background: The Problem of Noisy Logs
Most observability teams acknowledge that a significant portion of their logs are useless noise—health pings, repetitive debug output, or overly verbose messages from minor services. These logs do nothing but inflate monthly bills and distract engineers from real issues.
Yet removing them has traditionally required either complex configuration changes at the application level or laborious infrastructure change management. Until now, Grafana Cloud offered no simple way for centralized teams to drop unwanted logs before ingestion.
What This Means: Immediate Cost Savings and Cleaner Observability
With drop rules, teams take control of log volume directly at the ingestion pipeline. Instead of storing every log line and later filtering it out, they can prevent low-value data from ever being written to storage, reducing both noise and cost in real time.
“This is a game-changer for platform teams who want to enforce log hygiene across dozens or hundreds of services,” Lam added. “A single rule can eliminate 100% of health-check logs globally, no need to chase each team.”
How Drop Rules Work
Each drop rule can use any combination of log labels, detected log levels, or line content to decide whether to drop a log line before it reaches Cloud Logs. Users can specify a drop percentage to effectively sample noisy logs they don’t want to discard entirely.
Key capabilities include:
- Drop by log level: Eliminate all DEBUG logs that eat up your logging budget.
- Sample repetitive logs: Set a drop percentage to retain only a representative sample of chatty, repetitive messages.
- Target specific services: Combine label selectors with level or text matching to isolate a single noisy producer.
How Drop Rules Fit into the Adaptive Logs System
Adaptive Logs uses three mechanisms in a fixed order to manage log volume. When a log line arrives in Grafana Cloud:
- Exemptions protect critical logs from any modification.
- Drop rules are evaluated in priority order; the first match applies its drop rate.
- Patterns apply optimization recommendations to remaining logs that weren’t exempted or dropped.
The system ensures that drop rules, recommendations, and exemptions work together as a complete log cost management solution.
A Complete System: Drop Rules, Recommendations, and Exemptions
Each mechanism serves a distinct purpose. Drop rules eliminate known noise—for example, health-check logs that no service truly needs. A single rule with 100% drop rate enforces that standard across every service without requiring individual teams to change their logging configuration.
Drop rules can also apply sampling to specific workloads. A batch processing job generating repetitive log output can be targeted with a stream selector and a 90% drop rate, keeping only a representative sample for troubleshooting while cutting costs.
Urgency for Platform Teams
This public preview is available now for all Grafana Cloud users. Given rising log volumes and budget pressures, the ability to drop noise immediately can deliver significant monthly savings.
“We built this because our customers told us they were spending too much on logs they never looked at,” said Lam. “Now they can take action in minutes, not weeks.”