Datadog (DDOG) FY2025 results: revenue $3.4 billion, up 27.7% on the year

Datadog is an observability and security platform for cloud applications, sold as software as a service. It integrates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security, service management and other capabilities into one real-time view of a customer's technology stack. The company started in 2010 to build a real-time data integration platform, launched its first product, Infrastructure Monitoring, in 2012, and has since extended past observability into cloud security, software delivery and service management.

The platform is modular. Many products are fully capable stand-alone, so a customer can take them one at a time or several at once, and when deployed together they cross-correlate automatically. Data is collected client-side by a single agent covering metrics, traces, logs and other data, and more than 1,000 out-of-the-box integrations pull in data from public cloud, private cloud, on-premise hardware, databases and third-party software. Every piece of data ingested is tagged with metadata regardless of type, so a log event and an application trace can be queried together, correlated, alerted on and visualised in one interface. The filing states the platform currently monitors trillions of events per hour and millions of servers and containers.

Observability

Infrastructure Monitoring watches IT infrastructure across public, private and hybrid cloud, containers and serverless, with all infrastructure data in one repository. Application Performance Monitoring gives code-level distributed tracing across microservices, hosts, containers and serverless functions. Log Management ingests, indexes and queries logs; Logging Without Limits separates the cost of ingesting logs from processing them, and Flex Logs separates storage from query so retention and querying capacity move independently. Observability Pipelines collects, transforms and routes logs, metrics and traces from any source to any destination.

Synthetics monitors applications and API endpoints with simulated user requests, while Real User Monitoring analyses browser and mobile application performance as actual users experience it. Product Analytics gives engineering leaders, product owners and product managers a picture of product, user and performance data across applications. Continuous Profiler measures code-level performance with an always-on, low overhead approach. Database Monitoring shows query metrics and explain plans from all of a customer's databases in one place. Data Observability covers Data Streams Monitoring for event-driven applications and Data Jobs Monitoring for Spark and Databricks jobs. LLM Observability traces large language model chains end to end, with visibility into input and output, errors, token usage and latency at each step. Error Tracking groups errors into issues across frontend and backend applications with debug context down to lines of code. Cloud Network Monitoring visualises network traffic flow, and Network Device Monitoring covers routers, firewalls, switches and load balancers.

Service management and automation

Incident Response unifies monitoring, paging and incident management into one workflow. Workflow Automation automates and orchestrates processes across a customer's stack with out-of-the-box actions and customisable blueprints, and App Builder is the low-code way to build custom applications alongside it. Event Management aggregates and consolidates alerts into one view for centralised operations teams. Bits AI SRE is an always-on AI agent for troubleshooting, which the filing says was developed against thousands of real-world incidents. Cloud Cost Management gives granular visibility into cloud costs alongside metrics, traces and logs.

OnCall, Product Analytics and the Bits AI SRE agent were all launched in 2025, OnCall to build on-call schedules and feed real-time observability data into a customer's incident response plan.

Security

Cloud Security scans a customer's infrastructure agentlessly for vulnerabilities, misconfigurations, identity risks and compliance violations. Code Security prioritises vulnerabilities by runtime, covering first-party code and third-party open-source code in development and at runtime. Cloud SIEM detects and investigates threats across cloud-scale environments and stores and analyses operational and security logs in real time. Threat Management splits into Workload Protection, which does in-kernel analysis of workload activity across hosts and containers, and App & API Protection for API visibility, posture management and runtime protection. Sensitive Data Scanner discovers, classifies and redacts sensitive data on ingestion against built-in or user-defined rules, to support compliance with GDPR, HIPAA and CCPA. CI Visibility covers the continuous integration environment, with Pipeline Visibility for slow or failing pipelines, builds and jobs across providers, and Test Visibility for slow, failing and flaky tests.

A Marketplace sits alongside the products, where customers can access products built by partners on top of the Datadog platform.

From Datadog's annual report on Form 10-K for the year ended 31 December 2025. The filing

Written from the 10-K filed 18 February 2026: read the full 10-K.