Before founding Costory, we experienced firsthand how cloud cost alerting doesn’t work the way you think it should.
At first, we set simple rules:
Copied!Alert if daily spend > $1,000
Alert if S3 storage > 10 TB
It seemed sensible. But before long, those alerts were triggering almost every week.
A data backfill, a large training job, a traffic spike after a media campaign — all perfectly normal events — looked like “critical incidents” in our alerting system.
It became background noise. Nobody was acting on it anymore.

The Threshold Problem
Most FinOps alerting still works like this: pick a number, alert if you go over.
It’s the same mindset as early infrastructure monitoring:
Copied!if cpu_usage > 90% for 5m => alert
This is fine for catching massive spikes, but cloud costs today are far too dynamic for static rules:
- Elastic workloads — Auto-scaling clusters, event-driven compute, and batch jobs create large but expected fluctuations.
- Shifting business context — A launch, a marketing push, or a new model training job can legitimately increase spend.
- Threshold drift — The “right” threshold changes over time… but rarely gets updated.
The result: alerts fire constantly, engineers learn to ignore them, and real cost anomalies slip through.
Common False Positives We’ve Seen
- Data reprocessing — AWS Glue jobs backfilling historical data for compliance.
- Load testing — Kubernetes clusters scaling up for performance testing.
- Content migrations — S3 usage doubling during an asset migration.
All of these are normal.
A static threshold system can’t tell the difference between these and a genuine runaway cost.
What “Next-Gen” Cost Alerting Should Do
If you want alerts your SRE and FinOps teams actually value, they need:
- Historical baselines — Compare against your past usage patterns.
- Seasonality awareness — Understand predictable peaks, like holiday traffic or month-end batch jobs.
- Event correlation — Factor in releases, data jobs, and known business events.
- Noise suppression — Avoid firing on the same known condition repeatedly.
- Relevance scoring — Escalate only when the anomaly really matters.
Our Take at Costory
Because we’d been burned by noisy, context-free cost alerts in our previous companies, we started building context-aware anomaly detection.
Instead of asking:
“Did we exceed $X?”
We ask:
“Is this change unexpected given our history, workload patterns, and business context?”
The goal: surface only the anomalies worth your attention, while ignoring the noise that burns out engineers.
We’ll be opening a beta for this approach in mid-August for teams that want to try it.
The takeaway:
Static thresholds can catch catastrophic spikes, but they’re too blunt for modern cloud environments.
Smarter alerting requires context, history, and noise reduction — whether you build it yourself or use a tool like Costory.