60–80%
Ingest reduction
only signal-worthy events reach the hot path
Fleak joins the Databricks startup accelerator. See the announcement
Observability bills scale with volume. Make yours scale with value.
Fleak trims, samples, and converts high-volume logs, metrics, and traces before they reach your observability platform, and routes the full-fidelity copy to cheap storage. Engineers keep the signal. Finance keeps the budget.
- Logs
- Metrics
- Traces
- OpenTelemetry
- Logs to metrics
- Cost per team
Up to 50%
Storage cost reduction
from deduplication at ingestion
Millions
Events per second
real time, zero storage required
Every service logs everything,
and you pay premium rates for all of it.
Debug logs, health checks, and high-cardinality metrics flow straight into platforms priced per GB, per host, and per custom metric.
Debug logs at premium prices
Verbose application logs land in the observability platform at full price, and nobody queries most of them after a day.
Cardinality explodes
One new label on a metric multiplies the series count, and the bill follows a week later.
Every team, its own agent
Teams ship telemetry with different agents and formats, so nobody can see which service drives the spend.
Keep the signal,
drop the bill.
Fleak shapes telemetry in flight, so the observability platform receives what engineers use and everything else waits in cheap storage.
Logs to metrics
Turn high-volume logs into counters and rate, error, and duration metrics, and keep the raw logs in object storage.
Sample traces and spans
Keep every error and slow trace and sample the healthy ones, with counts tagged so dashboards stay accurate.
Drop debug noise
Filter debug levels, health checks, and duplicate lines before they are indexed, by service, environment, or team.
Tame cardinality
Drop or aggregate high-cardinality labels before they become billable custom metrics.
OpenTelemetry in and out
Receive OTLP from collectors and SDKs, and send to any OpenTelemetry-compatible backend without changing instrumentation.
Cost by service and team
See volume and spend per service, team, and destination, so cost conversations start with data.
Pay for the telemetry engineers use.
Everything else stays in cheap storage, a replay away when an incident needs it.
The Brain finds the waste.
The Muscle trims it.
The Brain profiles telemetry by service and shows which logs, metrics, and labels nobody reads. The Muscle applies the approved rules deterministically, in flight, before the observability platform meters a byte.
Works in front of
- Datadog
- Splunk Observability
- Elastic
- New Relic
- Grafana
- Prometheus
A payments service logs every health check at INFO.
What should the observability platform receive?
Before
EverythingMillions of identical health-check lines a day, indexed at full price, never queried.
After
Metrics + errorsHealth checks become a counter. Errors and slow requests arrive in full. Raw logs go to object storage.
Trust model
ApprovedEvery rule is reviewed by the owning team before it ships, and can be rolled back in one click.
Visibility stays the same. The bill doesn't. Everything trimmed from the hot path is still a replay away.
"Observability spend should follow the questions engineers ask, not the volume services emit."
Observability optimization · Fleak Platform
Bring your last observability invoice.
30-minute working session. We'll show which telemetry earns its cost and what the rest should do.
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