Mastering Dataset Migrations: A Step-by-Step Guide Using Background Coding Agents

Introduction

Migrating thousands of datasets across a complex infrastructure is a daunting task. At Spotify, we faced this challenge and developed an approach using Background Coding Agents combined with Honk, Backstage, and Fleet Management to streamline the process. This guide provides a proven methodology for supercharging downstream dataset migrations, reducing manual effort, and minimizing migration pain.

Mastering Dataset Migrations: A Step-by-Step Guide Using Background Coding Agents — Source: engineering.atspotify.com

What You Need

Honk – an orchestration service for managing background tasks.
Backstage – a developer portal for service catalog and visibility.
Fleet Management – tools for deploying and monitoring background agents.
Source and target dataset environments (e.g., databases, data lakes).
A migration plan – inventory of datasets, dependencies, and transformation rules.
Background Coding Agents – scripts or microservices that perform migration tasks asynchronously.
CI/CD pipeline for deploying agents and configuration updates.

Step-by-Step Guide

Step 1: Assess and Inventory Your Datasets

Begin by cataloging all datasets that need migration. Use Backstage’s service catalog to register each dataset as an entity, noting its owner, dependencies, and current location. This step creates a single source of truth for tracking migration status.

Create a Backstage plugin or custom entity type for datasets.
Tag each dataset with priority, migration window, and transformation requirements.
Identify downstream consumers (teams, services) that rely on the datasets.

Step 2: Design Background Coding Agents

Develop background agents that perform the actual migration. Each agent should handle a specific task, such as data copy, schema transformation, or validation. Agents run asynchronously, enabling parallel execution and fault tolerance.

Write agents in a language of your choice (e.g., Python, Go) that interact with both source and target systems.
Implement idempotency – agents should safely re-run if failures occur.
Include logging and metrics for monitoring via Backstage or a dashboard.

Step 3: Set Up Honk for Orchestration

Honk is the core orchestrator that schedules, executes, and monitors background agents. Configure Honk workflows that define the order of operations, timeout policies, and retry logic.

Define workflow steps: ‘Extract’, ‘Transform’, ‘Load’, and ‘Validate’.
Map each step to a specific background agent or lambda function.
Set up triggers – schedule-based (cron) or event-driven (e.g., upon dataset registration).

Step 4: Integrate Fleet Management for Agent Deployment

Use Fleet Management to deploy, update, and scale background agents across your infrastructure. This ensures agents run reliably and can be patched without downtime.

Package agents as container images and push to a registry.
Define fleet configurations – e.g., number of replicas, resource limits, and health checks.
Deploy using a rolling update strategy to maintain availability.

Step 5: Execute and Monitor Migrations

Trigger Honk workflows for each dataset migration. Monitor progress via Backstage dashboards that show real-time status, error rates, and completion percentages.

Use Honk’s built-in logging to track each agent’s output.
Set up alerts for failures or slow progress.
Validate migrated datasets by comparing checksums or running test queries.

Step 6: Automate Rollback and Cleanup

Include rollback agents that restore data if migration fails partially. After successful migration, clean up old dataset locations and update Backstage entity metadata.

Design rollback agents that revert steps in reverse order.
Archive or delete source datasets automatically after a cooldown period.
Update the dataset entity in Backstage to reflect the new location and status.

Tips

Start small: Pilot the system with a few low-impact datasets before scaling.
Maintain version control: Store agent code and Honk workflow definitions in your CI/CD pipeline.
Communicate with stakeholders: Use Backstage’s service ownership to notify dataset owners of migration schedules.
Monitor thoroughly: Implement custom dashboards in Backstage for real-time migration visibility.
Test rollbacks: Regularly test your rollback procedures to ensure reliability.
Document your process: Keep a runbook that covers common failures and resolutions.

By leveraging Background Coding Agents, Honk, Backstage, and Fleet Management, you can turn a painful migration into a smooth, automated operation. This method has proven successful for migrating thousands of datasets at Spotify, and with these steps, you can achieve similar results.