How Datadog Used Claude and Cursor for Test-Driven Production Migration
Datadog didn't just use Claude and Cursor for prototypes. They shipped a full production migration on AI.
Why it matters
Real-world case study of how enterprise teams are deploying AI coding tools (Claude, Cursor) to solve hard infrastructure problems at scale—moving beyond pilots to critical system overhauls. Shows practical adoption patterns and lessons learned that other engineering leaders need to understand.
The key facts
11 to knowDatadog used Claude + Cursor for test-driven production migration
Project involved overcoming storage backend hard limits
Significant performance improvements achieved
Production system (not pilot) involved in migration
Engineer-authored lessons learned shared publicly
Focus on what worked vs. what didn't
Datadog production migration case study
Tools: Claude + Cursor for test-driven development
Use case: Storage backend optimization and performance improvement
Focus: Practical lessons learned, not theoretical
Source: Datadog engineer Arnold Wakim via InfoQ
Go to the source
InfoQ AI/MLinfoq.com
Publisher excerpt: In a recent article, Datadog engineer Arnold Wakim shared what worked, what didn't, and the lessons they learned while evolving a critical production system using AI to overcome hard limits in its storage backend and significantly improve performance. By Sergio De Simone