Datadog: Cloud Monitoring as a Service
An analysis of one of the defining enterprise software from the past decade
The $30 Billion Market Cap Enterprise SaaS Behemoth
There have been several requests for an analysis of Datadog, a company providing foundational applications for DevOps and security. I believe their request comes from the curiosity to understand Data Dog's solutions, which may seem complex and technical as they run on top of on-premise, cloud, and applications infrastructure.
As we explore the business model and product, I want to demonstrate the opposite. That, in fact, Datadog solutions are enablers of simplicity to the explosion of complexity in the modern technology stack. To uncover how, I will first cover the basics of the problem that Olivier Pomel and Alexis Lê-Quôc set out to solve in their founding in 2010 - DevOps.
An Introduction to DevOps
When developing and deploying software, responsibilities are segmented across two areas: development and operations. The first, development, consists of those responsible for writing, testing, and reviewing code for software. They are the builders, conceptualizing and architecting the software end-to-end. The second, operations, involves the deployment of the software and its delivery after the code has been created. They are responsible for the front-line monitoring of production and live environments for issues.
Until recently, these two operations worked separately in a development process known as a waterfall methodology. Essentially, it means that each part of development was handled by a different team or department. Information was in silos, and context was lost, leading to many delays and miscommunications with projects.
The methodology of choice underwent a cultural change in the mid-2000s. A new methodology, DevOps, emerged and is being adopted by companies as Amazon, Netflix and Facebook. In practice, DevOps was a new combination of philosophies, practices and tools that increased the speed in which companies deliver applications. Most importantly, in DevOps, development and operations teams were no longer “siloed.” In DevOs they merged into a single team where the engineers work across the entire application lifecycle.
For DevOps to operate within an organization, a wave of applications emerged to run on top of new technological practices such as microservices, logging, continuous delivery, and continuous integration.
One of these applications was Datadog.
Company Overview
Datadog was founded in 2010, to build a real-time data integration platform to connect the silos between Dev and Ops. At the time, legacy applications for monitoring static on-premise architecture were not built to function in the modern cloud or hybrid environments and Datadog set out to build observability tools to provide infrastructure-wide visibility.
Their first use case, Infrastructure Monitoring, was launched in 2012 and functioned by connecting the data from disparate sources into digestible and actionable insights. The tool was used to collect health and performance data from servers, virtual machines, containers, databases, and other backend components in a tech stack, and was released at the perfect timing as both DevOps and on-demand cloud computation adoption was on the rise.
Benefiting from the secular tailwinds of cloud migration and DevOps, Infrastructure Monitoring became an instant success. From there, Datadog expanded their platform rapidly, innovating and adding new solutions to its product portfolio, which increased from 1 to 19 products from 2012 to 2023. The expansion was set in three distinct phases. First, Datadog released a suite of solutions in a monitoring and analytics platform for developers, IT operations teams, and business users in a set of observability use cases. Second, in 2020, they released security use cases by developing products for cloud security as a new expansion. Lastly, in 2021, they released developer-focused products to increase the depth for technical teams.
With its continuous product expansion and innovative use cases, Datadog has established itself as a market leader in observability and security for cloud applications. The company went public in FY2019, reporting revenues of $363M for that year. Since then, Datadog's success has been consistent, forecasting a close to FY23 with revenues of $2.05Bn and a Non-GAAP operating income of $400M. Thirteen years after its inception, the company boasts a 48% score on the rule of 40 and stands as one of the few SaaS companies in the $1Bn+ ARR club.
Company History
Datadog was founded by two natives from France, CEO Olivier Pomel and CTO Alexis Lê-Quô. The duo were alumni of Ecole Centrale (Paris) and worked together as senior management in Wireless Generation, another SaaS company, where they began their friendship and relationship.
They set out to build a Datadog solution leveraging the cloud and DevOps tailwinds in 2010, but had difficulties finding investors who understood the product. It was technical, new, and hard to understand at that time. As a result, fundraising was hard. Olivier and Alexis could only raise their $1.1M seed round from lesser-known investors. As Olivier put in a presentation in Data Driven NYC “"we were in a "not funded, oh my god, how are we going to survive mode" for about a year." Starting cash-strapped, it forced them to be a cash-efficient business and connect to their customers very often to build their first solution.
Times were challenging until 2012, when Datadog introduced their first solution, infrastructure monitoring, to the broader market. The product achieved an instant product-market fit, propelling the company into significant success. Shortly after the product's release, in November 2012, Datadog announced their initial institutional funding round, partnering with Index Ventures and RTP Global. After a series of priced rounds reaching Series D, the company priced their IPO in September 2019, raising $648M in their public offering.
Product
Datadog provides a SaaS platform that integrates and automates infrastructure monitoring, application performance monitoring, log management, real-user monitoring, and many other capabilities to provide unified, real-time observability and security for their customers’ entire technology stack. In other words, they unify separate tools into an integrated monitoring and analytics platform, readily available to everyone who cares about applications and their impact on business.
Datadog’s proprietary platform is designed to provide metrics, traces, logs, and other data from over 600 integrations to provide a unified view of infrastructure, application performance, and the real-time events impacting performance. From inception, it was designed to be cloud-agnostic and easy to deploy, with hundreds of out-of-the-box integrations, a built-in understanding of modern technology stacks, and extensive customizations. Customers can deploy their platform across their entire infrastructure using their out-of-the-box functionality and simple, self-service installation within minutes. After integration, Datadog’s time to value is instant, becoming a core part of the infrastructure used by developers, operations engineers, and business leaders.
The key use cases of Datadog’s products are to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior, and track key business metrics. This can be applied to businesses across all industries and sizes that have on-premise, hybrid, or on-cloud technology stacks.
The product design decision that contributes to the product’s success:
Built for dynamic cloud and hybrid infrastructures: The Platform was born in the cloud and was built to work with cloud technologies such as microservices, containers, and serverless computing.
Simple but not simplistic: The platform is easy-to-use with out-of-the-box integrations, customizable drag-and-drop dashboards, real-time visualization, and prioritized alerting. The platform is deployed in a self-service installation process within minutes, allowing new users to quickly derive value without any specialized training, heavy implementation, or customization.
Integrated data platform: Datadog combines the “three pillars of observability” - metrics, traces, and logs in one single pane of glass.
Built for collaboration. The platform was built to break down the silos between developers and operations teams by providing development and operations teams with a standard set of tools to develop a joint understanding of application performance and shared insights into the infrastructure supporting the applications.
Scalable: Datadog´s SaaS platform is highly scalable and is delivered through the cloud. Datadogs platform is massively scalable, monitoring more than tens of trillion events a day and millions of servers and containers at any time.
Go-to-Market
Datadog is built for development and operations (IT) teams across organizations of all sizes and industries. As the product is built-on top of the easy-to-use, out-of-the-box functionalities with cross-platform, cloud and technology adaptability, it can be deployed in any customer that requires observability and security features in their cloud.
The product design enables a go-to-market motion has the flexibility to target different industries, geographies, and customer types. At the same time, the fast time to value allows them to provide free trials to promote awareness, usage, and adoption of their products. Their principal strategy is to land and expand, selling a specific use case at first and using their footprint within their customer base to increase usage or offer new products.
To distribute the platform globally, Datadog has a team of approximately 2,300 professionals in the sales and marketing departments. Each of these teams is segmented by geography to ensure coverage across the Americas, Asia-Pacific (APAC), and Europe, the Middle East, and Africa (EMEA). In tandem with the marketing department, the sales units actively chase leads from marketing campaigns, guiding potential clients through the evaluation and purchasing journey.
They organized their go-to-market- across four revenue-generating organizations:
Enterprise Sales Team: Dedicated to catering to large businesses.
High-Velocity Inside Sales Team: Primarily engaged in acquiring new clientele.
Customer Success Team: Responsible for onboarding new clients and expanding relationships with current ones.
Partner Team: Collaborates with resellers, system integrators, referral partners, and managed service providers.
The team's revenue generation organization has been widely successful. Datadog had approximately 23,200 customers in December 2022, spanning organizations of a broad range of sizes and industries, compared to approximately 18,800 in the prior year. Of those, 2,780 had an ARR of $100,000 or more, representing 85% of their revenues.
Market Size
There is a seismic shift from static on-premise IT architectures to distributed, dynamic multi-cloud and hybrid cloud architectures with ephemeral technologies such as containers, microservices and serverless architectures becoming increasingly common.
As companies transition to the cloud and their underlying infrastructure evolves, the monitoring requirements for this infrastructure also change. According to Gartner, only 5% of applications were monitored by 2018.
Gartner's most recent forecast estimates the Total Addressable Market for Datadog's observability products at $62Bn, calculated by multiplying the potential ARR of existing customers. Datadog's business capitalizes on several secular growth drivers:
The momentum of digital transformation and cloud migration.
Rising penetration among cloud and next-generation DevOps customers.
An expanding range of products and use cases for clients.
Business Model
Datadog business model is centered around offering a land-and-expand model of offering products that are easy to adopt with a very short time of value. Their customers expand their footprint with their products on a self-service basis, increasing consumption and usage of their first product and enabling the expansion into other products in the platform. Currently, the company offers 19 products on their integrated Data Platform. As of Q2 FY23, 82% of their customers used 2 or more products, and 45% used 4 or more products.
The company generates revenues from subscriptions of customers using their cloud-based platforms. These agreements are monthly, annual, or multi-year with the majority of their revenue coming from annual subscriptions. Each agreement has a contractual amount of usage that is proportioned over the subscription period. If the customers exceed that limit, an incremental payment is charged to the customers. The usage is measured by the number of hosts or volume of data indexed. The contracted usage is provided as utilized. Unlike many other enterprise-grade software companies, Datadog doesn't charge for implementation due to the ease of integrating their software. This ease is attributed to the pre-built integrations they offer, especially beneficial for large enterprise customers.
Combining an easy-to-adopt and multi-product business model with a land-and-expand software motion has proved very effective. As of Q2 FY23, Datadog has 120%+ Net Revenue Retention on a business with $1.9bn in TTM revenues.
Financials & Summary Metrics
Datadog’s financial performance has been spectacular since its founding as a capital-efficient, high-growth technology stock.
Datadog reported $2Bn in Annualized Recurring Revenue (ARR) as of Q2 FY23, which reflects a 25% YoY growth.
The company increased its number of customers with an ARR of $100,000 from 1,800 in Q3 2021 to 2,990 by Q2 2023.
Datadog's "land and expand" strategy has been highly successful, with the company reporting a TTM Net Dollar Retention of 120% as of Q2 FY23.
Simultaneously, the company’s Gross Dollar Retention stands in the mid to high 90%.
International customers contribute to 28% of Datadog's revenues. The company boasts a Non-GAAP operating margin of 21% and a Free Cash Flow Margin of 28%.