Overview

Datadog is a software-as-a-service (SaaS) platform that provides monitoring and analytics for cloud-scale applications. It aggregates data from servers, databases, tools, and services, offering a unified view of an organization's entire technology stack. The platform is designed to help development, operations, and security teams gain visibility into the performance and health of their systems, from infrastructure to individual application requests.

Datadog's core offerings include infrastructure monitoring, which tracks metrics from hosts, containers, and serverless functions; application performance monitoring (APM), providing detailed tracing for distributed applications; and log management, which centralizes and analyzes log data. The platform also extends to real user monitoring (RUM), synthetic monitoring, network performance monitoring (NPM), and security monitoring, providing a comprehensive suite of observability tools. This broad scope positions Datadog for organizations needing deep insights into complex, hybrid, and multi-cloud environments, as noted in analyses of modern monitoring strategies by industry publications like The New Stack.

The platform's architecture relies on agents deployed on hosts and integrations with various cloud providers and third-party services to collect data. This data is then processed, indexed, and made available through customizable dashboards, alerts, and machine learning-driven anomaly detection. Datadog is particularly suited for enterprises managing large-scale, dynamic infrastructures where rapid detection and resolution of performance issues are critical. Its module-based pricing allows organizations to select specific capabilities, scaling consumption based on factors like hosts, log volume, and trace counts.

Key features

  • Infrastructure Monitoring: Collects and visualizes metrics from servers, containers (Docker, Kubernetes), serverless functions (AWS Lambda, Azure Functions), and cloud providers like AWS, Azure, and Google Cloud.
  • Application Performance Monitoring (APM): Provides end-to-end tracing for requests across distributed services, identifying bottlenecks, errors, and latency issues within applications, with support for multiple programming languages (OpenTelemetry compatibility).
  • Log Management: Centralizes, processes, and analyzes logs from all sources, allowing for real-time log ingestion, search, filtering, and archiving.
  • Real User Monitoring (RUM): Monitors the performance and user experience of web and mobile applications from the end-user's perspective, capturing metrics like page load times and JavaScript errors.
  • Synthetic Monitoring: Proactively tests application availability and performance from various global locations using simulated user requests or API checks.
  • Network Performance Monitoring (NPM): Visualizes network traffic flows, identifies network bottlenecks, and monitors connectivity between services and hosts.
  • Security Monitoring: Detects threats, monitors compliance, and investigates security incidents across the cloud environment, leveraging log data and network telemetry.
  • Incident Management: Offers tools for incident response, including on-call scheduling, alert routing, and post-mortem analysis.
  • Continuous Profiler: Provides always-on code-level performance analysis in production, helping to optimize resource utilization and reduce latency (developer documentation).
  • Cloud Cost Management: Offers visibility into cloud spending across providers, helping teams optimize cloud resource usage and identify cost inefficiencies.

Pricing

Datadog employs a module-based pricing structure, allowing users to select and pay for specific monitoring capabilities. The primary pricing dimensions are typically per host for infrastructure, per GB for logs, per million traces for APM, and per million sessions for RUM.

Pricing as of 2026-05-07:

Product Starting Tier Pricing Basis
Infrastructure Monitoring $15/host/month Per host (billed hourly), custom metrics per 100 metrics/month
Log Management $0.10/GB ingested/month Per GB ingested (volume discounts available), per million log events (retention dependent)
APM & Continuous Profiler $35/host/month Per host, per million traces ingested, per million profiler samples
Real User Monitoring (RUM) $4.50/1K sessions/month Per 1,000 sessions (web or mobile)
Synthetic Monitoring $5/1K tests/month Per 1,000 API tests or browser tests
Network Performance Monitoring (NPM) $27/host/month Per host (billed hourly)
Cloud Cost Management $10/orchestrator/month Per cloud orchestrator (e.g., Kubernetes cluster)

Additional products like Security Monitoring, Incident Management, and Serverless Monitoring have separate pricing models. Detailed pricing information is available on the Datadog pricing page.

Common integrations

Alternatives

  • New Relic: Offers a comprehensive observability platform with APM, infrastructure monitoring, logs, and RUM, often compared for its developer experience and feature set.
  • Dynatrace: Provides AI-powered full-stack monitoring with a strong focus on automation, root cause analysis, and digital experience management.
  • Grafana Labs: Offers open-source and enterprise solutions built around Grafana for dashboards, Prometheus for metrics, and Loki for logs, providing flexibility for self-hosted or managed observability.
  • Prometheus: An open-source monitoring system with a time series database, widely used for collecting and querying metrics in cloud-native environments.
  • Splunk: Known for its robust log management and security information and event management (SIEM) capabilities, also offering infrastructure and APM solutions.

Getting started

To begin monitoring a Python application with Datadog APM, you typically install the Datadog Agent on your host and then instrument your application using the Datadog Python tracing library. This example demonstrates how to set up a basic Flask application with Datadog APM.

First, install the necessary packages:

pip install Flask ddtrace

Next, create a simple Flask application (app.py):

from flask import Flask

app = Flask(__name__)

@app.route("/")
def hello_world():
    return "<p>Hello, Datadog!</p>"

@app.route("/greet/<name>")
def greet(name):
    return f"<p>Hello, {name}!</p>"

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000)

To enable APM, run your application using the ddtrace-run command. Ensure your Datadog Agent is running and accessible (default is localhost:8126). You will also need to set your Datadog API key and application key as environment variables, or configure them in the Datadog Agent.

DD_AGENT_HOST=localhost \nDD_TRACE_AGENT_PORT=8126 \nDD_SERVICE=my-flask-app \nDD_ENV=development \nddtrace-run python app.py

After running the application and making a few requests (e.g., to http://localhost:5000/ and http://localhost:5000/greet/cloudpicker), traces and metrics for your Flask application will appear in your Datadog APM dashboard. For more detailed setup and configuration options, refer to the Datadog Python APM documentation.