Streamlining Large-Scale Dataset Migrations with Automated Agents

At Spotify Engineering, we faced the daunting challenge of migrating thousands of datasets downstream for consumer applications. To make this process efficient and less painful, we combined three powerful internal tools: Honk (our automation framework), Backstage (the developer portal), and Fleet Management (infrastructure orchestration). The key innovation was deploying background coding agents—autonomous scripts that handle repetitive migration tasks. This Q&A explores how these components worked together to supercharge migrations, reduce manual effort, and minimize errors.

What are background coding agents, and how do they aid dataset migrations?

Background coding agents are automated programs that run in the background, executing predefined migration steps without human intervention. In our context, they handle tasks like schema transformations, data consistency checks, and updating downstream references. Each agent is configured via Honk, our in-house automation tool, which defines the migration logic and triggers. The agents operate as continuously running services, monitoring for migration requests and applying changes incrementally. This approach dramatically reduces the manual workload: instead of engineers writing ad hoc scripts for every dataset, they simply define the migration rules once, and the agents carry out the work across thousands of datasets, with retries and error logging built in. By running asynchronously, they avoid blocking critical developer workflows and allow migrations to proceed around the clock.

Streamlining Large-Scale Dataset Migrations with Automated Agents — Source: engineering.atspotify.com

How does Honk simplify the automation of dataset migrations?

Honk is Spotify’s framework for defining and executing automated workflows. In dataset migrations, Honk provides a declarative way to specify each step—from extracting source data to validating the new consumer schema. Engineers write migration agents as small, composable units that Honk orchestrates. Honk handles scheduling, error handling, and retry logic automatically. For example, a migration agent might check if a downstream dataset’s schema has changed, then apply the necessary transformation. Honk also integrates with Backstage to surface migration status and logs, giving developers visibility into progress. By abstracting away boilerplate infrastructure code, Honk allows teams to focus on the migration logic itself, speeding up development and reducing bugs. The result is a scalable automation pipeline that can handle thousands of datasets concurrently.

What role does Backstage play in the migration workflow?

Backstage, Spotify’s open source developer portal, serves as the central interface for managing and monitoring migrations. During a dataset migration, Backstage provides a dashboard where engineers can view all ongoing and completed migrations, see error logs, and drill into individual dataset status. It also acts as a service catalog: each dataset is registered with metadata about its owners, consumer applications, and schema details. When a migration is triggered, Backstage sends notifications to the relevant teams and updates the catalog automatically. This transparency reduces coordination overhead—teams know exactly what’s changing and when. Additionally, Backstage links to Honk workflows and Fleet Management dashboards, enabling smooth navigation between automation steps and infrastructure changes. Essentially, Backstage gives everyone a single pane of glass for the entire migration lifecycle.

How does Fleet Management orchestrate infrastructure during migrations?

Fleet Management is Spotify’s tool for managing server and service fleets. During dataset migrations, it ensures that the underlying compute resources are properly allocated, scaled, and updated. For example, if a migration requires spinning up temporary databases or running batch jobs, Fleet Management provisions the necessary containers or cloud instances. It also handles rolling updates: when a downstream dataset needs a new version of a consumer service, Fleet Management coordinates the rollout across the fleet without downtime. The coordination with Honk and Backstage is key: Honk triggers a migration step, Fleet Management executes any infrastructure changes, and Backstage tracks the progress. This orchestration prevents resource contention and ensures that migrations don’t overwhelm production systems. By automating infrastructure management, Fleet Management removes a major source of friction in large-scale migrations.

What were the main challenges of migrating thousands of datasets, and how were they overcome?

Manually migrating thousands of datasets would be error‑prone and time‑consuming. The biggest challenges included: (1) scale—each dataset had unique schema versioning, consumers, and dependencies; (2) coordination—dozens of teams needed to be aligned on timing and ownership; and (3) risk—any mistake could break downstream applications. We overcame these by introducing background coding agents that ran migration steps automatically, using Honk to define standard migration templates that adapt to each dataset’s specifics. Backstage provided visibility and ownership tracking, so every dataset had a clear owner and migration status. Fleet Management handled the infrastructure scaling and safe rollouts. Together, these tools turned a traditionally manual, high‑risk process into a reliable, automated pipeline. The agents also included validation steps—schema checks and dry runs—before final execution, significantly reducing the chance of failures.

What benefits did background coding agents bring to Spotify Engineering?

The adoption of background coding agents transformed our dataset migration workflow. First, speed—migrations that previously took weeks of manual scripting and coordination could now be completed in days, as agents ran in parallel across hundreds of datasets. Second, reliability—automated validation and retries meant far fewer human errors and outages. Third, developer satisfaction—engineers were freed from repetitive toil and could focus on higher‑value work. Backstage dashboards gave teams confidence that migrations were on track. Finally, scalability—the agent framework easily handled spikes, such as when a major schema change required migrating several thousand datasets simultaneously. The combination of Honk, Backstage, and Fleet Management with background coding agents proved to be a scalable, reusable pattern that has since been applied to other infrastructure automation tasks beyond migrations.