The use case: how Homeaglow deploys Honeycomb
Homeaglow, a home cleaning services marketplace, uses Honeycomb for observability, distributed tracing, SLOs and performance optimization across its Django and GraphQL platform. The engineering team also uses trace and telemetry data to inform product decisions and queries system behavior through Honeycomb's MCP integration.
More reported results
Figures published in Honeycomb’s case study. They are not independently measured by usedby.
10x savings through caching
After initial cleanup, Homeaglow went more than twelve months without a single internally caused outage.
In the customer’s words
Honeycomb is like a Homeaglow for software engineers. The mental load is lighter. If something goes wrong, we will know, and we can fix it fast.Other companies using Honeycomb
Customers across industries, with public evidence.
AmperityConfirmed
Booking.comConfirmed
DepotConfirmed
DuolingoConfirmed
FenderConfirmed
FreshpaintConfirmedGo straight to the source
Based on Honeycomb’s published case study. We check the public evidence; the results are reported by the vendor.
honeycomb.io- Source published
- Feb 12, 2026
- Last checked
- Nov 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 40xChecked
Printed word for word on the page, near the name of Homeaglow.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Homeaglow.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Homeaglow uses HoneycombChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Honeycomb uncovered a memory allocation issue that resulted in a 40x improvement in the core booking API.