Discover how Olivier and Alexey founded Datadog after meeting at IBM. Learn their journey from the dot-com bust to building a $8,000-person company that moni...
How Two French Engineers Built Datadog in NYC
Key Insights
- Rejection as motivation: Datadog was rejected by Y Combinator twice, which became a driving force to prove doubters wrong and build a successful company.
- DevOps unification: The core idea was bringing developers and operations teams together on one platform to solve cloud monitoring challenges.
- Cloud underestimation: The founders initially underestimated the cloud's explosion, thinking AWS was just a toy companies would never use.
- Culture over documentation: Rather than writing down company values, Datadog's culture flows from the top through hiring, promotion, and leadership example.
- AI-driven transformation: With AI accelerating product development, experienced developers now accomplish in days what once took teams of six months.
From IBM to a Cloud Monitoring Vision
Olivier and Alexey met at IBM Research in upstate New York during the late 1990s. Olivier arrived for an internship on internet protocols and planned to stay six months, but remained in New York for over 26 years. Both worked through the dot-com boom and bust—experiences that taught critical lessons about startup execution. Later, they built tech teams at an educational software startup that grew to 800 people, exposing them to significant DevOps and operational challenges. This experience revealed a gap: developers were essentially blind to production issues, while operations teams used separate, specialized tools.
The Bet: Unifying Dev and Ops
Datadog was founded in 2010 with a bold premise—bringing developers and operations into one unified platform. At the time, "monitoring" was job-specific and reactive, with ops-only tools that developers never touched. The founders targeted this fragmented market from the bottom up. While they didn't fully grasp it then, their platform bet aligned perfectly with the cloud explosion. However, they massively underestimated cloud adoption, viewing AWS as an interesting experiment. Companies they talked to said cloud was a toy they'd never use—and then everyone adopted it.
Building Culture Without a Manifesto
Rather than posting company values on walls, Datadog's leadership deliberately avoided written culture statements, believing that if people need "don't be evil" written down, they shouldn't work there. Instead, the culture flows from leadership through hiring, promotion, and firing decisions. After 26 years with co-founder Alexey, Olivier remains deeply involved in product decisions—reading customer support requests, sales transcripts, and employee survey comments. This hands-on approach prevents sanitized information from hiding real problems. When he spots issues in raw feedback, he replies with simple questions that push the entire management chain to understand actual conditions rather than upward-facing summaries.
Scaling Product Strategy with 20+ Offerings
Datadog now operates approximately 20–25 products. Product expansion decisions come primarily from observing how customers use the platform—they build workflows and extensions that signal unmet needs. Beyond customer-driven features, leadership also makes strategic bets on emerging trends without waiting for explicit demand. AI presents a new challenge: the market moves too fast to wait for customer requests, so Datadog must get ahead of shifts and accept being wrong more often.
Public Company Reality and AI's Impact
Since going public in 2019, Datadog weathered a 65% stock crash when lockup expired during COVID, followed by multiple market cycles. Being public changes the rhythm of investor engagement—a few quarterly calls and a week of preparation replace the constant fundraising demands of private companies. The main concern shifts from survival to employee compensation through RSUs tied to stock performance.
AI has fundamentally altered the company's approach. In December, Olivier stood before the engineering team and declared that within two quarters, they wouldn't write code by hand anymore. Experienced developers accomplished in days what previously took teams of six months. This inversion—from mostly writing to mostly automating—signals a structural reorganization. Smaller teams can now tackle problems that once required larger groups, though the exact future state remains unclear.
European Founders and the US Market
Olivier emphasizes that while Europe now offers adequate funding, founders must pursue the US market as soon as product-market fit emerges. He doesn't believe the entire company needs to relocate—if there are two founders, typically one moves to the US. Datadog created its Paris office later for talent acquisition, hiring people unable to renew US visas or seeking to return to France.
Conclusion
Two French engineers rejected by Y Combinator transformed that setback into fuel for building Datadog, the cloud monitoring platform that unified fractured developer and operations teams. Their journey reveals that culture, deep product involvement, and willingness to move fast on hiring and firing matter more than perfect planning. As AI reshapes how code is written, Datadog's strategy of leading rather than following demand shows the company is positioned to evolve with its customers.
Original source: How Two French Engineers In New York Built The Company That Monitors The Entire Cloud
powered by osmu.app