Logistics
Harbourline
Cut observability spend by 63% while tripling the volume they keep.
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63%
lower monthly bill
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3.1×
more data retained
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11 min
median time to detect
“We were paying per host on a fleet that autoscaled to four hundred nodes at peak. The bill was effectively a random number generator.”
The constraint
Harbourline runs freight routing across sixteen regions. Their previous vendor charged per monitored host, and their fleet autoscaled by a factor of eight between the overnight trough and the Monday morning peak. Nobody could forecast the bill, so the platform team had been quietly reducing what they monitored.
What we changed
We moved them to ingest-based pricing and rewrote the collection config to drop three high-cardinality debug labels that accounted for 40% of their volume and had never been queried. Tail sampling replaced a flat 5% head sample.
Where it landed
The bill dropped 63% and stopped fluctuating with the fleet size. Because retention was no longer being rationed, incident reviews now have the full window, and median time to detect fell from 34 minutes to 11.