Datadog provides a cloud‑based observability platform that consolidates logs, metrics, traces, and security data from cloud, container, serverless, and on‑premises environments. It offers real‑time correlation, AI‑driven anomaly detection, and customizable dashboards for developers, SREs, and IT ops to troubleshoot performance issues, monitor security threats, and optimize applications across hybrid and multi‑cloud infrastructures.
Funding
Funding not disclosed
Founders
Product
Problem
Modern cloud applications generate massive volumes of logs, metrics, traces, and events across distributed infrastructure, making it difficult for developers and IT teams to collect, correlate, and analyze this data in real time. Without unified visibility, performance issues, security threats, and cost inefficiencies remain hidden until they cause outages or breaches.
Solution
Datadog offers a cloud‑based observability platform that unifies log management, application performance monitoring, security monitoring, network analysis, synthetic testing, real‑user monitoring, and serverless observability. Data from any source—cloud services, containers, servers, or client browsers—is ingested via agents or APIs, normalized, and stored in a searchable index. Integrated analytics and AI‑driven alerts surface performance degradations, anomalies, and security incidents as they occur. Users access customizable dashboards, correlation across data types, and automated incident response workflows, enabling rapid troubleshooting and proactive optimization across hybrid and multi‑cloud environments.
Target Audience
Primary customers are developers, site reliability engineers, and IT operations teams managing cloud‑native, hybrid, or multi‑cloud applications, as well as security analysts needing unified visibility across the stack.
Features
- Unified ingestion of logs, metrics, traces, and events with support for on‑premises, cloud, container, and serverless workloads
- Real‑time correlation engine that links performance metrics with log entries and security alerts
- AI‑assisted anomaly detection and alerting for performance regressions and potential threats
- Interactive dashboards and customizable visualizations for end‑to‑end traceability
- Built‑in synthetic monitoring and real‑user monitoring to assess frontend and API health
- Integrated security monitoring, including Cloud SIEM, workload protection, and sensitive data scanning
- Extensible API and integrations with major cloud providers, CI/CD pipelines, and third‑party tools
- Scalable architecture with pay‑as‑you‑go pricing and optional on‑premises CloudPrem deployment for data residency