High-Performance
Data Migration Architecture
Fault-tolerant ETL solution migrating 10,000+ assets from Monday.com to Google Drive with zero downtime.
The Challenge
MRO Supply needed to migrate a massive volume of project data, including images, documents, and metadata, from Monday.com to a Google Drive archive. The sheer scale (10,000+ records) made manual migration impossible, while standard export tools failed to handle the complexity of linked assets and "living" documents.
Key Requirements
- Resumable execution: Network failures shouldn't restart the process.
- Data integrity: Every file must be verified and logged.
- Smart processing: Large images need compression; documents need conversion.
Engineering The Solution
We didn't just write a script; we built a robust data pipeline.
Resumable Migration
Implemented a state-aware system using migration_state.txt. The pipeline
tracks every processed ID, allowing it to resume exactly where it left off after any
interruption, ensuring zero duplicated effort.
Concurrency & Threading
Leveraged Python's concurrent.futures.ThreadPoolExecutor to process up to 5
assets in parallel. This multi-threaded approach reduced total migration time by 70%
compared to sequential processing.
Smart Image Optimization
Integrated Pillow (PIL) to detect and compress images >1MB on the fly. This optimization maximized storage efficiency without compromising visual quality for archival purposes.
Browser Automation
Standard APIs couldn't export Monday.com's internal "Docs". We deployed Playwright to simulate user sessions, rendering and capturing these documents as Markdown files automatically.
Technology Stack
Core Logic
APIs & Data
Automation
Pipeline Architecture
Init & State Check
Load local state
& Verify API keys
Fetch Data
GraphQL Cursor based
Pagination
Process
Compress Images
& Render Docs
Upload & Log
Drive Upload
& Sheet Entry
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