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How to Fix Datadog Synthetics Browser Test

DodaTech Updated 2026-06-26 3 min read

In this tutorial, you'll learn about How to Fix Datadog Synthetics Browser Test. We cover key concepts, practical examples, and best practices.

The Problem

Your Datadog synthetics browser test configuration is not working. Data is not showing up, monitors do not trigger, or the feature behaves unexpectedly.

Datadog is a leading observability platform, but synthetics browser test misconfiguration leads to blind spots in your monitoring. The DodaTech SRE team uses Datadog to monitor all production systems. Here is the fix.

Error Symptoms

You see in Datadog:

synthetics-browser-test monitor: No data reported
5f036e64af70 Evaluation window empty

Wrong Configuration

This is the problematic synthetics browser test setup:

monitor:
  name: "My Monitor"
  type: metric alert
  query: avg(last_5m):avg:system.cpu.user{host} > 90
  # Missing proper synthetics-browser-test configuration

The monitor uses default settings that may not match your data source. Without correct synthetics browser test parameters, the monitor never evaluates properly.

Result:

Monitor created: My Monitor
Status: No Data

Right Configuration

Here is the correct synthetics browser test setup:

monitor:
  name: "Production Host CPU - datadog-syntheti"
  type: metric alert
  query: avg(last_5m):avg:system.cpu.user{host} > 90
  message: |
    CPU usage is above 90% on {host.name}
    @slack-dodatech-alerts
    @pagerduty-dodatech
tags:
    - env:production
    - team:sre
    - service:datadog-synt
  priority: 2
  options:
    notify_audit: false
    locked: false
    timeout_h: 0
    new_host_delay: 300
    require_full_window: true
    notify_no_data: true
    no_data_timeframe: 10
    evaluation_delay: 60

Expected output:

Monitor "Production Host CPU" created
Status: OK (or Alert when threshold exceeded)

Prevention

  • Use the Datadog API or Terraform provider to manage monitors as code
  • Tag all resources consistently (env, service, team) for granular filtering
  • Set proper evaluation windows to reduce noise and false positives
  • Use composite monitors for complex multi-condition alerting logic
  • Configure notification handles for Slack, PagerDuty, email, and webhooks
  • Review Incident Response runbooks for alert handling procedures
  • Monitor monitor health with the Datadog Monitor Overview dashboard
  • Set up metric metadata to define unit, description, and integration source

Common Mistakes with synthetics browser test

  1. Using return to exit a function early instead of wrapping a pure value in the monad
  2. Mixing let bindings with <- bindings in do notation, producing type errors
  3. Overlapping type class instances that cause GHC to reject the program with ambiguous dispatch errors

These mistakes appear frequently in real-world DATADOG code. DodaTech's contributors have identified these patterns through analysis of open-source projects and production systems.

Practice Exercise

Write a pure function that safely divides two integers using Maybe, then test it with edge cases like division by zero and negative numbers.

This exercise reinforces the concepts covered in this guide. Try implementing it before checking online solutions.

FAQ

Why is my Datadog synthetics-browser-test not showing any data?

Check the Agent status with <a href="/devops/monitoring-tools/">datadog</a>-agent status and verify the API key is valid. For integration metrics, check the integration tile in Datadog for setup instructions.

How do I test Datadog monitor queries before creating them?

Use the Datadog Monitor Evaluate API endpoint to test query results, or use the query preview in the monitor creation UI to verify data is available.

Does DodaTech use Datadog for observability?

Yes, DodaTech uses Datadog for infrastructure monitoring, APM tracing, log management, and synthetic testing across all environments. We ingest over 100GB of data daily.

What is the difference between Datadog metric and log monitors?

Metric monitors evaluate time-series data against thresholds, while log monitors count occurrences of log messages matching a search query. Choose based on your data type.

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