Datadog Synthetic Monitoring vs Checkly

Here’s a practical comparison of Datadog Synthetic Monitoring vs Checkly.

Quick take

• Choose Datadog Synthetic Monitoring if you already use Datadog for observability and want synthetics tightly integrated with logs, APM, metrics, dashboards, and alerting.
• Choose Checkly if you want a developer-first synthetic monitoring tool focused on API checks, browser checks, and Playwright-based workflows, with strong GitOps/CI/CD support.

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High-level differences

Area	Datadog Synthetic Monitoring	Checkly
Primary strength	Broad observability platform integration	Developer-friendly synthetic checks
Best for	Teams already on Datadog	Engineering teams wanting code-defined monitoring
Browser monitoring	Yes	Yes, very strong
API monitoring	Yes	Yes, very strong
DNS / SSL / network style checks	More limited vs dedicated uptime tools in some cases	Strong uptime-style checks
CI/CD + Git	Good, but not its main identity	Excellent, core workflow
Alerting	Very powerful via Datadog	Strong, simpler, focused
Dashboards/analytics	Best-in-class when using full Datadog stack	Good, but narrower than Datadog
Learning curve	Moderate to high	Lower for dev teams
Pricing style	Can become expensive with scale	Usually easier to predict for synthetic-only use

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Datadog Synthetic Monitoring

Pros

• Deep integration with Datadog observability stack
• Great if you need to correlate synthetic failures with:
  • APM traces
  • logs
  • infrastructure metrics
  • real user monitoring
• Good for enterprise-scale monitoring and centralized operations
• Mature alert routing and incident workflows

Cons

• Can feel heavy if you only want synthetics
• Pricing can add up, especially at scale
• Less “code-first” and GitOps-centric than Checkly
• Setup and maintenance may be more complex for smaller teams

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Checkly

Pros

• Very developer-centric
• Checks can be defined as code and managed in Git
• Strong support for Playwright and browser automation
• Great for:
  • API monitoring
  • login flows
  • critical user journeys
  • uptime checks
• Faster to adopt for engineering teams
• Often simpler and more transparent for synthetic-only monitoring

Cons

• Not a full observability platform
• If you need deep correlation with app logs/APM/infra metrics, you’ll still need another tool
• Less broad than Datadog for enterprise observability needs

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Which one should you pick?

Pick Datadog if:

• You already pay for Datadog
• You want one platform for observability + synthetics
• You need strong cross-linking between monitoring, logs, traces, and metrics
• You have a larger operations/SRE team

Pick Checkly if:

• Your team prefers monitoring-as-code
• You want synthetics tightly integrated with GitHub/GitLab/CI
• You mostly care about API and browser journey checks
• You want a simpler, more focused product

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Common real-world pattern

A lot of teams use:

• Datadog for infrastructure, app performance, logs, and alerting
• Checkly for synthetic tests around user journeys and API uptime

That combo works well if you want the best of both worlds.

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Bottom line

• Datadog Synthetic Monitoring = best if you want a single observability platform
• Checkly = best if you want developer-first synthetic monitoring with a strong code/Git workflow

If you want, I can also give you:

1. a feature-by-feature matrix,
2. a pricing comparison, or
3. a recommendation based on your team size and stack.