Datadog
Unified cloud monitoring, observability, security, and incident response platform
Score
60
User Rating
3.0
Free/Trial Support
Not Supported
Starting Price
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Last Updated
Sep 29, 2026
Overview
What is Datadog?
Datadog is a cloud-based observability, monitoring, security, and incident-response platform for infrastructure, applications, logs, networks, user experiences, software delivery, cloud costs, and AI systems. It unifies metrics, traces, logs, security signals, dashboards, alerts, integrations, and automated workflows so engineering, operations, security, and business teams can detect issues, investigate root causes, improve performance, and automate remediation across any stack.
What is Datadog used for?
Top Features
- Infrastructure, host, container, Kubernetes, serverless, and network monitoring
- Application Performance Monitoring with distributed tracing, service maps, error tracking, and continuous profiling
- Centralized log ingestion, indexing, retention, search, analytics, archiving, and rehydration
- Cloud security posture management, workload protection, Cloud SIEM, code security, and application protection
- Real User Monitoring, session replay, product analytics, synthetic testing, and mobile app testing
- Software delivery monitoring for CI pipelines, test optimization, code coverage, feature flags, and DORA metrics
- Incident response, on-call management, case management, event correlation, and status pages
- AI-powered investigation, chat, code assistance, agent building, and agent observability
- Cloud cost visibility, FinOps reporting, Kubernetes cost allocation, budgets, forecasts, and recommendations
- Dashboards, notebooks, alerts, SLOs, integrations, OpenTelemetry support, RBAC, and governance controls
- Workflow Automation and App Builder for low-code operational remediation
- Database monitoring and data observability for jobs, pipelines, data quality, and lineage
How to use Datadog?
Create a Datadog account or start a free trial, choose the relevant products, and connect cloud providers, hosts, containers, applications, databases, logs, CI systems, or user-facing applications through integrations and the Datadog Agent. Configure dashboards, monitors, alerts, service-level objectives, security rules, and workflows to analyze telemetry, investigate incidents, and automate remediation. Usage and costs can be reviewed through Datadog's plan and usage tools.
Alternative Tools
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Pros & Cons
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Use Cases
- Monitor cloud infrastructure, Kubernetes clusters, containers, and serverless workloads
- Trace application requests and correlate performance issues with infrastructure, logs, deployments, and database queries
- Centralize logs from multiple cloud providers and investigate production incidents
- Detect cloud misconfigurations, vulnerabilities, identity risks, and runtime threats
- Monitor customer-facing web and mobile experiences with RUM, session replay, and synthetic tests
- Optimize CI/CD pipelines, identify flaky tests, and enforce code coverage standards
- Coordinate incidents with on-call schedules, escalations, timelines, postmortems, and automated workflows
- Track and reduce cloud, SaaS, Kubernetes, and observability costs
- Observe AI agents, evaluate model outputs, monitor LLM costs and latency, and detect quality or security issues
- Monitor database performance, slow queries, data pipelines, and data quality checks
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