Nobody reads
your logs.
Your app generated Enter a valid number log lines today.
Your traces created Enter a valid number spans.
Nobody looked at them.
Good luck finding that one error in 16.2M events.
The inconvenient truth
You're paying for data
that sits there.
The average team spends $50,000–$200,000/year on observability. Datadog. New Relic. Splunk. Sentry.
That money buys you petabytes of logs, millions of traces, thousands of metrics. It does not buy you understanding.
When production breaks at 3am, you still grep through logs manually. You still ask "what changed?" You still page the one engineer who knows how this service works.
Based on your log and span volumes above at $2.50/million events ingested
But wait, there's more
Tracing will fix it.
No, it won't.
Distributed tracing was supposed to be the answer. Correlate requests across services. See the full picture.
Here's what actually happened:
More data ≠ more understanding. You don't need more observability. You need someone—something—to actually look at it.
Calculate your waste
Observability waste calculator
How much are you spending on data nobody reads?
Be honest. We won't tell your CFO.
Your annual cost of not understanding production
$127,500
Observability spend + engineering time at $150/hr
Benchmark your stack
See how your observability
waste compares.
We're compiling data across hundreds of teams to expose the real cost of observability theater. Add your stack to the dataset.
In return, you'll get:
- Your cost-per-GB compared to devs on the same stack
- Which observability tools developers actually use (and regret)
- The hidden costs you're probably not tracking
Reports go out weekly as we hit data thresholds. The more teams, the better the benchmarks.