Cloud Monitoring Leader 'Datadog' CTO Sells Billion-Dollar Stake... Family Trust Also Sells

In an early-May 2026 SEC filing, Datadog, Inc. (NASDAQ: DDOG) disclosed that co-founder and Chief Technology Officer Alexis Le-Quoc, together with a family trust affiliated with insider Amit Agarwal, converted Class B common shares into Class A shares and then sold those Class A shares under a pre-established Rule 10b5-1 trading plan. The Agarwal family trust converted 20,000 shares on May 4 and another 20,000 on May 11, subsequently selling the Class A shares in two block trades worth hundreds of millions of Korean won—retaining only a small direct stake. Nonetheless, the filing noted that through other family trusts and spousal holdings, the trust group still maintains significant Class A and B positions. CTO Le-Quoc exercised stock options and converted Class B to Class A shares on May 4–5, then sold approximately $7 million (roughly KRW 10 billion) of Class A stock in tranches. Despite these disposals, he continues to hold multi-billion-dollar exposure in Datadog via his remaining direct Class A shares and trust-held indirect holdings.

On May 7, Datadog reported first-quarter 2026 revenue of $1.006 billion, up 32% year-over-year, and raised both its second-quarter and full-year 2026 revenue guidance, exceeding market expectations. Following the strong results and upgraded outlook, Datadog’s share price jumped about 30% in a short span, reaffirming its standing as a leading growth stock in the software and cloud sector.

Headquartered in New York, Datadog is a cloud-application observability and security platform provider offering a SaaS solution that delivers real-time monitoring of complex cloud infrastructures—servers, databases, microservices and more—to enterprise customers worldwide. Co-founder Alexis Le-Quoc, as CTO, steers the company’s product and technology strategy. Since its IPO on Nasdaq under the ticker DDOG, Datadog has been consistently cited as a key beneficiary of enterprise cloud migration and the expanding demand for AI-driven workloads.