How to Use Datadog

Datadog is a unified observability platform — metrics, logs, traces, and infrastructure monitoring all in one place, so debugging a production issue doesn't mean stitching together three separate tools.

Step 1: Install the Agent

Datadog's Agent runs on your hosts or containers and starts shipping infrastructure metrics — CPU, memory, disk — within minutes of installation.

Step 2: Instrument your app for APM

Add the relevant language library (Python, Node, Java, and others) to get distributed traces showing exactly where time is spent as a request moves across services.

Step 3: Ship logs

Point your log output at the Agent or use a log-forwarding integration. Datadog automatically correlates logs with the metric and trace data from the same host or service, instead of leaving you to cross-reference timestamps by hand.

Step 4: Build a dashboard

Combine widgets from any data source — metrics, logs, APM — onto one custom dashboard scoped to the service or team you actually care about.

Step 5: Set up a monitor

Define a threshold, like an error rate above a set percentage, and Datadog alerts your team through Slack, PagerDuty, or email the moment it's crossed.

Where it bites

Pricing is per-host and per-GB-ingested, so cost scales fast with fleet size and log volume. Teams that ship every log line at full verbosity in production are often surprised by the bill — log sampling and retention filters are worth setting up early, not after the first invoice.