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Datadog Acquires Eppo to Expand Its AI, Product Analytics, Experimentation and Feature Flag Capabilities

1. Datadog acquires Eppo for advanced feature flagging and experimentation. 2. Integration enhances Datadog’s Product Analytics suite for better insights. 3. Eppo helps scale AI workloads safely, improving user experience metrics. 4. The acquisition promotes faster, risk-mitigated product development cycles. 5. Collaboration between engineering, product, and business teams is emphasized.

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Why Bullish?

The acquisition strengthens Datadog’s product offerings, likely boosting customer interest and revenue, similar to past acquisitions like that of Sqreen, which enhanced security features and benefited stock performance.

How important is it?

The acquisition not only adds a new capability but also enhances Datadog’s competitive edge in cloud observability, attracting more enterprise clients.

Why Long Term?

The integration of Eppo's capabilities into Datadog's suite will create enduring value and growth potential, evidenced by past acquisitions that took time to mature, such as PagerDuty's acquisition of Peoplecast.

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EPODDOG
Combining observability with experimentation and feature flags will help companies build high-quality products faster and with less risk, especially when using AI May 05, 2025 08:55 ET  | Source: Datadog, Inc. NEW YORK, May 05, 2025 (GLOBE NEWSWIRE) --  Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced it has acquired Eppo, a feature flagging and experimentation platform, which will tightly integrate with Datadog’s existing Product Analytics suite. Today, application developers need to stitch together analytics from various tools across engineering, product and business teams to understand the impact of their new features and improvements. Changes are often rolled out without understanding their impact to KPIs, making it difficult to tie these changes back to business outcomes. With its acquisition of Eppo, Datadog creates a full end-to-end product analytics solution on one platform. This unified approach means that engineers can track code changes with feature flags, data science leaders together with product managers can design and measure impact with experiments, and business analysts can use Datadog’s Product Analytics suite to understand overall product usage and business outcomes. As AI workloads grow, Eppo’s experimentation capabilities help developers safely scale complex systems. These capabilities can measure the impact to the overall user experience in real time and accelerate the safe roll-out of changes, ultimately creating a more agile and trustworthy development workflow. “The use of multiple AI models increases the complexity of deploying applications in production. This complexity makes it difficult for developers to quantify the business impact of different models, agent behaviors, prompts or UI changes,” said Michael Whetten, VP of Product at Datadog. “Experimentation solves this correlation and measurement problem, enabling teams to compare multiple models side-by-side, determine user engagement against cost tradeoffs and ultimately build AI products that deliver measurable value." “Eppo wants to bring a high velocity, experiment-first culture to companies of every size, stage and industry,” said Chetan Sharma, founder and CEO of Eppo. “With Datadog, we are uniting product analytics, feature management, AI and experimentation capabilities for businesses to reduce risk, learn quickly and ship high-quality products.” Eppo will continue supporting existing customers and bringing on new customers as part of Eppo by Datadog. About DatadogDatadog is the observability and security platform for cloud applications. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries 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. Forward-Looking Statements This press release may include certain “forward-looking statements” within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended including statements on the benefits of new products and features. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control, including those risks detailed under the caption “Risk Factors” and elsewhere in our Securities and Exchange Commission filings and reports, including the Annual Report on Form 10-K filed with the Securities and Exchange Commission on February 20, 2025, as well as future filings and reports by us. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise. ContactDan Haggertypress@datadoghq.com

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