AI at Datadog: Monitoring machines in the age of LLMs | Olivier Pomel, CEO of Datadog
Sep 27, 2024
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Olivier Pomel, co-founder and CEO of Datadog, shares the remarkable journey of transforming Datadog into a tech giant from early rejections. He emphasizes their open product development philosophy that prioritizes customer insights. The conversation dives into the launch of new products like DASH for LLM observability and innovative tools like Toto for time series forecasting. Olivier also discusses integrating AI in operations and the challenges faced in anomaly detection, providing a fascinating look at the nexus of technology, customer collaboration, and AI.
Datadog's evolution from a single product to a multi-billion dollar platform illustrates their commitment to iterative development and customer collaboration.
The company's strategic adoption of AI, particularly through products like Watchdog and Beats AI, enhances user experience by automating anomaly detection.
Datadog's all-in-one observability approach unifies various monitoring categories, fostering collaboration and improving operational efficiency across different organizational teams.
Deep dives
The Founding Story of Datadog
Datadog was founded in 2010 in New York City by two French immigrants during a time when the city's tech ecosystem was not as vibrant as it is today. Initially considered a risky venture, Datadog has now become a significant player in the tech landscape, boasting nearly 29,000 customers and a market cap of $39 billion. The founders' humble beginnings are highlighted by their journey through the challenges of starting a software company in a competitive market. Their persistence and innovative approach to product development have propelled Datadog to become a leader in the observability space.
Innovative Product Development Strategy
Datadog's product development strategy emphasizes collaboration with customers and design partners from the outset. Instead of following a traditional model of creating a fully formed product to release after years of development, the company opts to ship initial versions quickly and iterate based on real user feedback. This approach allows for rapid adaptation and the ability to keep pace with customer needs, enhancing the overall effectiveness of their products. As a result, Datadog has successfully expanded its platform over the years by adding various products that cater to a wide range of observability needs.
Navigating the AI and Machine Learning Landscape
Initially cautious about integrating AI and machine learning into their offerings due to concerns about false positives and negatives, Datadog has since adopted a more confident approach. Their AI strategy includes the launch of products like Watchdog and Beats AI, designed to enhance user experience through automated anomaly detection and predictive insights. The company recognizes the critical role of AI in improving observability, and they are committed to refining their technology to ensure reliability and accuracy. This evolution demonstrates Datadog's readiness to embrace AI in a way that adds significant value to their customers.
The Transformation of Observability Solutions
Datadog has seen significant transformations in the field of observability, migrating from simple monitoring tools to a comprehensive, integrated platform. The journey included recognizing the need to unify various monitoring categories, leading to the development of an all-in-one solution that caters to infrastructure, application, and user experience monitoring. This shift not only improved operational efficiency but also fostered collaboration between previously siloed teams within organizations. The expansion into security solutions and AI-driven products further solidifies Datadog's position as a holistic provider within the observability space.
Future Trends and Opportunities in AI
Looking ahead, Datadog identifies numerous opportunities within the AI landscape as it relates to their core business. The rise of generative AI and other advanced models presents new challenges and options for observability, as these technologies bring increased complexity and data management needs. Datadog aims to enhance its foundation model, Toto, to capitalize on these advancements and improve predictive analytics. As the interplay between observability and AI unfolds, Datadog remains committed to delivering innovative solutions that meet the evolving requirements of their customers.
In this episode, we dive deep into the story of how Datadog evolved from a single product to a multi-billion dollar observability platform with its co-founder, Olivier Pomel. Olivier shares exclusive insights on Datadog's unique approach to product development—why they avoid the "Apple approach" of building in secret and instead work closely with customers from day one.
You’ll hear about the early days when Paul Graham of Y Combinator turned down Datadog, questioning their lack of a first product. Olivier also reveals the strategies behind their iterative product launches and why they insist on charging early to ensure they’re delivering real value.
The second half of the conversation is focused on all things AI and data at Datadog - the company's initial reluctance to use AI in its products, how Generative AI changed everything, and Datadog's current AI efforts including Watchdog, Bits AI and Toto, their new time series foundational model.
We close the episode by asking Olivier about his thoughts on the topic du jour: founder mode!
▶️ Listen to 2020 Data Driven NYC episode with Oliver Pomel: https://www.youtube.com/watch?v=oXKEFHeEvMs
DATADOG
Website - https://www.datadoghq.com
Twitter - https://x.com/datadoghq
Olivier Pomel
LinkedIn - https://www.linkedin.com/in/olivierpomel
Twitter - https://x.com/oliveur
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
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