Datadog provides the observability and monitoring infrastructure necessary for tracking AI agents and large language model (LLM) applications in production. Operating within the monitoring and evaluation layer of the agent stack, the platform enables developers to capture telemetry on LLM latency, token consumption, and API costs. Through its LLM Observability features, Datadog provides visibility into the execution of complex agentic workflows, allowing users to trace individual steps in a reasoning chain and monitor how agents interact with external tools and data sources.
For the broader AI ecosystem, Datadog bridges the gap between traditional cloud infrastructure and non-deterministic AI outputs. This connection is essential for engineering teams that require a single view to monitor both the underlying server health and the performance of the agents running on them. By centralizing logs, traces, and metrics, the company provides the operational oversight needed to secure and scale agentic systems, helping users identify performance bottlenecks or unexpected model behaviors that could impact the reliability of autonomous software.
Datadog is architecting a comprehensive, SaaS-based observability, security, and analytics powerhouse engineered specifically for the complexities of cloud-scale applications. Its strategic objective is to serve as the definitive "single pane of glass" for contemporary engineering teams, effectively dissolving the silos between development, operations, and security by unifying metrics, traces, logs, and AI-driven insights across the entire global technology stack.
The essence of Datadog's innovation lies in its frictionless capability to ingest, correlate, and visualize massive telemetry streams in real-time. By leveraging the lightweight Datadog Agent, organizations eliminate the friction inherent in fragmented toolchains and disjointed datasets. This holistic visibility delivers a profound operational impact: drastically reducing Mean Time to Resolution (MTTR), optimizing infrastructure expenditure, fortifying dynamic cloud environments, and ultimately safeguarding enterprise revenue and the end-user experience.
Delivered as a robust cloud-based SaaS, Datadog enables users to deploy an open-source agent across hosts, containers, and serverless environments. This agent autonomously harvests metrics, logs, and traces, transmitting them to a central platform. Powered by Watchdog, Datadog’s sophisticated AI engine, the platform surfaces anomalies, triggers intelligent alerts, and populates customizable dashboards for rapid triage and automated orchestration.
Established in 2010 by Olivier Pomel (CEO) and Alexis Lê-Quôc (CTO)—visionaries who met at École Centrale Paris—Datadog is headquartered in New York City. The organization has evolved into a global titan with over 8,100 employees, maintaining a rigorous, engineering-led culture that champions the open-source community.
Datadog stands as the preeminent Category Leader in the modern observability landscape. Recognized by Gartner and Forrester as a benchmark in AIOps and Observability, the platform acts as the critical bridge between foundational cloud providers (AWS, Azure, GCP) and intricate application architectures, surpassing legacy monitoring with a developer-centric philosophy.
A SaaS-based observability and security platform for cloud-scale applications.
Datadog is hiring.