Olivier Pomel – Co-Founder & CEO of Datadog

Olivier Pomel – Co-Founder & CEO of Datadog

Olivier Pomel is the co-founder and Chief Executive Officer of Datadog, the New York-based technology company that has grown from a small cloud-monitoring startup into one of the world's leading observability and security platforms.

Pomel co-founded Datadog with Alexis Lê-Quôc in 2010 after the two engineers experienced firsthand the growing divide between software development and IT operations. Their original insight was straightforward but timely: as companies moved toward cloud infrastructure, agile development, and increasingly complex software environments, engineers needed a better way to understand what was happening across their systems.

More than a decade later, that original idea has expanded considerably. Datadog now combines infrastructure monitoring, application performance monitoring, log management, user experience monitoring, security, software delivery, service management, product analytics, and AI-powered capabilities on a unified platform.

As of 2026, Pomel remains Datadog's CEO and co-founder. The company's latest public filings identify him as its Chief Executive Officer and principal executive officer, while Datadog's own leadership materials continue to list him as CEO & Co-Founder.

Who Is Olivier Pomel?

Olivier Pomel is a French-born software engineer and technology entrepreneur whose career has largely centered on building complex software systems and engineering organizations.

Before founding Datadog, Pomel worked at IBM Research and several internet startups before joining Wireless Generation, an education technology company in New York. At Wireless Generation, he served as Vice President of Technology and helped grow the engineering organization from a small group into a team of nearly 100 engineers.

Wireless Generation was eventually acquired by News Corp. in 2010. That same year, Pomel and his colleague Alexis Lê-Quôc began working on the idea that became Datadog.

Pomel's technical background is somewhat unusual among high-profile enterprise software CEOs. He was also an original author of the VLC media player, the open-source multimedia software project that later became one of the best-known open-source media players in the world.

He holds a master's degree in computer science from École Centrale Paris.

Education and Early Engineering Career

Pomel studied computer science at École Centrale Paris, one of France's leading engineering schools. His education gave him a strong foundation in software engineering, but his career quickly moved beyond traditional engineering roles.

He worked as a software engineer at IBM Research and at several internet companies before moving into technology leadership.

One of the early projects associated with Pomel's career was VLC, the open-source multimedia player. His involvement in the project's early development illustrates a recurring theme in his career: working on technically ambitious software and building practical tools around complex engineering problems.

Rather than following a conventional corporate technology path, Pomel repeatedly moved toward environments where software teams were dealing with new technical challenges.

That experience became particularly important at Wireless Generation.

Building Engineering Teams at Wireless Generation

At Wireless Generation, Pomel became Vice President of Technology.

The company was developing software and data systems for K-12 education, requiring the organization to handle large amounts of information and build reliable technology for schools and teachers.

Pomel grew the company's development team from a handful of engineers to close to 100. Datadog's official biography describes this as one of the major parts of his experience before founding the company.

More importantly, Wireless Generation is where Pomel and future Datadog co-founder Alexis Lê-Quôc worked closely together.

Pomel led development while Lê-Quôc was responsible for operations. Their experience working on opposite sides of the development-and-operations divide would eventually provide the foundation for Datadog.

Wireless Generation was acquired by News Corp. in 2010, giving Pomel and Lê-Quôc the opportunity to pursue a new company together.

The Founding of Datadog

Pomel and Lê-Quôc began working on Datadog in late 2010.

At the time, cloud computing was changing how software companies built and operated their infrastructure. Instead of relying primarily on physical servers, companies were increasingly adopting cloud services, virtual machines, distributed systems, and eventually containers and microservices.

This created a new operational problem.

Development teams were releasing software faster, while infrastructure was becoming more distributed and dynamic. Traditional monitoring tools were often designed around older IT environments and did not provide the unified visibility modern engineering teams needed.

Pomel later explained that the founders had experienced this problem themselves. At their previous company, he was running development while Lê-Quôc was running operations. They understood the communication and organizational problems that could occur when the two groups operated separately.

Datadog was designed around bringing these worlds together.

The founders' original thesis was that cloud infrastructure and agile software development would fundamentally change the monitoring problem. In a 2016 Datadog article, Pomel explained that they had started working on the company because infrastructure was going to look dramatically different in the coming decade and would require a new type of monitoring and analytics platform.

Why the Name Datadog?

The company's unusual name has its own connection to Pomel's previous experience.

At Wireless Generation, production servers were apparently given "dog" names. Database servers became "data dogs," and one particularly problematic database was known internally as "Data Dog 17."

When Pomel and Lê-Quôc started their new company, "Datadog" was initially used as a codename.

The name was memorable enough that they eventually kept it, dropping the "17." Pomel later explained the story during an interview about the company's early years.

What began as an internal nickname eventually became the name of a publicly traded technology company.

From Monitoring Tool to Observability Platform

Datadog's early product focused heavily on infrastructure monitoring, but Pomel and his team gradually expanded the company's ambitions.

The underlying idea was that modern engineering organizations did not need another isolated monitoring tool. They needed a unified view of their increasingly complicated technology environments.

Datadog therefore expanded across multiple layers of the technology stack.

The platform grew to include infrastructure monitoring, application performance monitoring, logs, network monitoring, real-user monitoring, security, cloud cost visibility, software delivery, service management, and product analytics.

This expansion allowed Datadog to become more than an infrastructure-monitoring product. It became a broader observability platform connecting data from applications, infrastructure, users, networks, and security systems.

That strategy also helped Datadog benefit from a major structural shift in enterprise technology: the migration from traditional on-premises infrastructure toward cloud computing.

Datadog's IPO

After years of building the company as a private startup, Datadog went public in September 2019.

The company priced its initial public offering at $27 per share and began trading on the Nasdaq under the ticker symbol DDOG on September 19, 2019. The IPO ultimately raised approximately $709 million in net proceeds after the underwriters exercised their additional share option.

The public listing was an important milestone for Pomel because Datadog had taken a somewhat unconventional path.

The company was headquartered in New York rather than Silicon Valley, and Pomel has spoken openly about the difficulty the founders initially faced raising money from investors who were accustomed to seeing infrastructure startups emerge from the West Coast.

In a 2019 interview, he explained that Datadog initially relied on smaller checks and angel investors. That forced the company to operate efficiently and stay close to customers.

The strategy eventually paid off.

Building a Large Public Technology Company

Datadog's growth since its IPO has been substantial.

For fiscal year 2025, the company reported $3.43 billion in revenue, representing 28% year-over-year growth. It generated $915 million in free cash flow and ended the year with approximately $4.47 billion in cash, cash equivalents, and marketable securities.

By the end of 2025, Datadog had approximately 4,310 customers generating at least $100,000 in annual recurring revenue and 603 customers generating at least $1 million in ARR.

The company also had approximately 8,100 employees across 35 countries at the end of 2025, demonstrating how far it had expanded from the small engineering organization Pomel and Lê-Quôc started in 2010.

Datadog joined the S&P 500 in July 2025, another indication of its evolution from startup to major public technology company. At the time, Pomel highlighted the company's more than 30,000 global customers and said the company was still in the early stages of cloud adoption and AI transformation.

Olivier Pomel's Leadership Philosophy

Pomel's leadership style is closely connected to his engineering background.

Rather than positioning Datadog simply as a software company selling monitoring tools, he has consistently emphasized the underlying changes taking place in software development and infrastructure.

One of his most important early observations was that development and operations could no longer remain separate disciplines.

Cloud computing made software environments more distributed. Agile development made release cycles faster. Open-source software increased the number of components engineers could use. Microservices and containers multiplied the number of systems that organizations needed to understand.

The monitoring problem therefore became a systems problem.

Datadog's strategy has been to solve that problem by bringing more data and functionality into one platform.

This approach has allowed Pomel to retain a technical focus while scaling the company into a large enterprise software organization.

The AI Opportunity

Artificial intelligence has become one of the most important strategic areas for Pomel and Datadog.

Rather than treating AI simply as another feature category, Datadog is positioning itself around two related opportunities.

First, companies need to monitor the AI systems they are building.

AI applications introduce new operational challenges involving model performance, latency, cost, reliability, security, prompts, agents, GPUs, and continuously changing behavior.

Second, AI can be used inside the Datadog platform itself to help engineers investigate and resolve problems.

Datadog has therefore developed AI capabilities including its Bits AI agents, AI-powered security capabilities, GPU monitoring, MCP integrations, and tools for observing AI applications.

The company's 2025 AI strategy described a broader ambition: move observability from passive visibility toward systems that can investigate problems, recommend actions, and eventually perform remediation more autonomously.

This represents an important evolution of Pomel's original vision.

The original Datadog product helped engineers understand what was happening inside their systems.

The next generation aims to help systems understand what is happening themselves.

Datadog's 2026 Growth

The company's financial performance in 2026 shows that the AI transition has not replaced Datadog's existing observability business; instead, it is expanding the company's opportunity.

In the first quarter of 2026, Datadog generated $1.006 billion in revenue, up 32% year over year. The company had approximately 4,550 customers with at least $100,000 in annual recurring revenue.

In the second quarter, revenue reached $1.12 billion, representing 36% year-over-year growth. Datadog reported approximately 4,720 customers with at least $100,000 in ARR.

Pomel described the company's strategy as helping customers observe, secure, and increasingly automate operations around AI-enabled systems.

The company's product development during 2026 has included AI-powered capabilities such as Bits Code, Bits Chat, Bits Agent Builder, security agents, GPU monitoring, and the Datadog MCP Server.

Datadog also acquired Adaptive ML in 2026 to accelerate its work around reinforcement learning, world models, and agentic AI.

A Technical CEO in an AI-Driven Market

One of the defining characteristics of Pomel's career is the continuity between his early engineering work and his current leadership role.

He did not begin by identifying a large market and then looking for a technology to enter it.

Instead, he and Lê-Quôc encountered a technical and organizational problem themselves.

They saw that developers and operations teams were becoming increasingly dependent on each other, while the tools available to them remained fragmented.

They built Datadog around that observation.

More than 15 years later, Pomel is applying a similar approach to AI.

AI systems are creating new operational complexity, and the company is attempting to build the infrastructure required to understand, secure, and operate those systems at scale.

That gives Datadog a natural position in the AI infrastructure ecosystem.

Challenges Ahead

Despite Datadog's scale, Pomel's company operates in an intensely competitive market.

Datadog competes across several overlapping categories, including observability, application performance monitoring, cloud security, log management, infrastructure monitoring, and developer tooling.

The competitive landscape includes both established technology companies and specialized software startups.

At the same time, AI is changing the market itself.

Datadog must continue investing heavily in research and development while ensuring that its platform remains useful to traditional cloud customers and relevant to companies building AI-native applications.

The company also needs to balance breadth with simplicity. A unified platform can become increasingly valuable as more functionality is added, but it can also become harder for customers to understand and deploy.

Pomel's challenge is therefore not simply to keep Datadog growing. It is to maintain the product's original value proposition—making complex technology environments easier to understand—even as those environments become dramatically more complicated.

The Future of Datadog Under Olivier Pomel

Pomel's current strategy suggests that Datadog is moving toward a future in which observability becomes increasingly autonomous.

The traditional model of monitoring is reactive:

Something breaks, an alert appears, and an engineer investigates.

The AI-powered model is more ambitious:

The system detects an anomaly, gathers context, identifies the likely cause, proposes a solution, and potentially takes action.

Datadog is already moving in this direction through its Bits AI agents and other AI-powered capabilities.

Pomel has described the broader goal as helping organizations manage complexity and build more autonomy into their operations. In the company's second-quarter 2026 results, he emphasized the need to help customers observe, secure, and act on AI-enabled systems.

If that vision succeeds, Datadog could evolve from being primarily an observability platform into an operational intelligence and automation layer for modern software organizations.

Why Olivier Pomel Matters

Olivier Pomel's significance extends beyond Datadog's financial success.

His career illustrates how technical founders can identify major changes in computing before those changes become obvious to the broader market.

In 2010, cloud infrastructure and DevOps were still developing concepts. Pomel and Lê-Quôc recognized that the transition would create a fundamentally different monitoring problem.

They built a company around solving it.

Datadog subsequently became a major public technology company, expanded into security and other software categories, and is now applying its platform to one of the biggest technological shifts of the current era: artificial intelligence.

Pomel has remained CEO throughout that journey.

The result is a rare example of a founder maintaining strategic and operational leadership while taking a technical infrastructure startup through rapid growth, an IPO, global expansion, and another major technological transition.

His story is ultimately one of staying close to the engineering problems created by technological change—and building a company around solving them.

Key Facts About Olivier Pomel

Category	Details
Full Name	Olivier Pomel
Current Role	CEO & Co-Founder, Datadog
Company	Datadog, Inc.
Founded Datadog	2010
Co-Founder	Alexis Lê-Quôc
Education	M.S. in Computer Science, École Centrale Paris
Previous Executive Role	VP of Technology, Wireless Generation
Previous Employer	IBM Research
Technical Background	Software engineering, infrastructure, data systems
Notable Early Work	Original author of VLC media player
Datadog IPO	September 2019
Stock Ticker	NASDAQ: DDOG
FY2025 Revenue	$3.43 billion
FY2025 Free Cash Flow	$915 million
Employees at End of 2025	Approximately 8,100
2026 Focus	Observability, cybersecurity, AI, agentic AI and autonomous operations

The current role, educational background, previous positions, and VLC connection are documented by Datadog's leadership materials and SEC filings. Financial and employee figures are based on Datadog's 2025 annual results and annual filing.

Summary

Olivier Pomel is the co-founder and CEO of Datadog, a company he built with Alexis Lê-Quôc after identifying a fundamental problem in modern software development: developers and operations teams needed a unified way to understand increasingly complex cloud environments.

With a background in computer science, software engineering, open-source development, and technology leadership, Pomel brought an unusually technical perspective to the role of CEO.

Under his leadership, Datadog evolved from a monitoring startup founded in 2010 into a global public technology company with billions of dollars in annual revenue.

The company's next chapter is increasingly focused on artificial intelligence. Datadog is building tools to monitor AI applications while also using AI to investigate incidents, improve security, assist developers, and automate operational work.

For Pomel, the underlying mission remains remarkably consistent: make complex technology easier to understand and operate.

The difference is that the complexity Datadog must address today is far greater than it was when the company began.