Datadog Email Format

Software Development
1,001-2,500 employees
New York, NY, USA

Datadog is a cloud monitoring and analytics platform that provides observability for servers, containers, databases, and third-party services to help DevOps teams optimize performance worldwide.

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first.last@datadoghq.com

Company Overview

Industry
Software Development
Founded
2010
Headquarters
New York, NY, USA
Revenue
$2.5B-$5B
FUNDING Stage
Public
Key Executives
Olivier Pomel (CEO & CO-FOUNDER), David Obstler (Chief Financial Officer), Adam Blitzer (Chief Operating Officer)

Tech Stack

Amazon EC2

Cloud Infrastructure

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Key Executives

Chief Executive Officer

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Chief Finance Officer

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Chief Operating Officer

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Chief Technology Officer

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Chief Marketing Officer

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Chairman

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4.9/5 on G2
40K+ GTM professionals
SOC 2 Type II certified

Frequently Asked Questions

What is the email format of Datadog?

Datadog uses the first.last format, so Jane Smith would be jane.smith@datadoghq.com.

What cloud observability products does Datadog offer?

Datadog offers a broad platform covering infrastructure monitoring, application performance monitoring (APM), log management, cloud security, digital experience monitoring, and LLM Observability for AI-powered applications, all accessible through a unified interface.

How can I find the right Datadog contact for outreach or verify a Datadog email address?

Since Datadog uses the first.last@datadoghq.com format, you can build email addresses directly from names. Tools like Clay can help you enrich a prospect list with verified Datadog contacts and confirm their current roles before reaching out.

Who leads Datadog as its CEO and co-founder?

Olivier Pomel co-founded Datadog and serves as its CEO. The executive team also includes David Obstler as Chief Financial Officer and Adam Blitzer as Chief Operating Officer.

Does Datadog's LLM Observability product support monitoring of AI agents and large language model applications?

Yes, Datadog's LLM Observability product lets engineering teams monitor, evaluate, and troubleshoot LLM-powered applications and AI agents in production, extending the same observability platform used for traditional infrastructure and APM workloads.

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