How Spotify migrated about 1,800 data pipelines with its Honk background coding agent
Spotify used Honk, its internal background coding agent built on Claude Code capabilities, to move downstream consumers off two deprecated datasets. The agent opened 240 migration pull requests, and the owning teams reviewed and merged them.
The problem
Two heavily used datasets were being deprecated. About 1,800 downstream pipelines depended on them, spread across BigQuery Runner, dbt and Scio, and they had to move within six months. Doing it by hand would have taken a lot of engineering time.
How they did it
- Found affected repositories with Backstage's lineage and Codesearch plugins.
- Queued the target repositories for change through Fleetshift, Backstage's plugin for large-scale code changes.
- Wrote detailed context files with field-mapping tables, since Honk could only see the context written for it.
- Left out the highly variable Scio pipelines and focused on the more standard dbt and BigQuery Runner code.
- For cases that needed judgment, told the agent to leave fields unchanged and add comments linking to human migration guides.
- Owning teams tested and merged the PRs themselves, because these repos rarely had build-time unit tests.
Results
- As reported by Spotify, the team 'successfully rolled out 240 automated migration PRs using Fleetshift'.
- Spotify estimated the work would have taken 'around 10 engineering weeks of effort' to complete by hand.
As reported by the source (Spotify Engineering blog); AgentGid did not measure these figures.
This suits a platform team with a large fleet of similar repos, a lineage tool, and engineers willing to write detailed mapping context. Honk is Spotify's internal tool, so you'd have to rebuild that layer yourself. Also note the 10-week saving is Spotify's own estimate, and owning teams still reviewed every PR. For a cheaper start, Pi is free (OSS), though you pay your model provider.
The agent used here
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