Top 1 Alternative to Datadog Synthetic Tests for Synthetics/E2E

Introduction and Context

Synthetic monitoring and end-to-end (E2E) testing have evolved dramatically over the past decade. Early reliability checks were simple: ping a host, run curl against a URL, and alert if the response didn’t match expectations. As web applications grew more interactive, teams adopted browser automation technologies—most notably Selenium—to simulate real user workflows across pages, forms, and services. Parallel to this, the rise of DevOps and cloud-native architectures pushed observability platforms to fold performance, logging, and monitoring into unified experiences.

Datadog Synthetic Tests emerged in this context as a natural extension of the Datadog observability platform. By combining API checks and browser-based flows with alerts, dashboards, and CI/CD hooks, it provided a cohesive way to validate user journeys and service-level availability from the outside in. Its model blends a visual recorder for complex flows with programmable steps, giving teams both speed and control. For organizations already invested in Datadog for metrics and logs, adopting Datadog Synthetic Tests helped centralize visibility and incident response.

What made Datadog Synthetic Tests popular:

• Integrated platform coverage: browser checks, API monitors, and alerting coexisting with APM, logs, and infrastructure metrics.

• Flexible test authoring: a recorder for quick capture of flows and code for fine-grained logic.

• CI/CD integrations: gating deployments with synthetic health checks and running monitors in pipelines.

• Broad applicability: Web/API coverage suits most modern digital experiences.

That said, no tool is one-size-fits-all. As teams scale usage, expand their technology stacks, or optimize costs, it’s natural to evaluate alternatives that might better suit specific constraints or preferences. Below we outline one strong alternative, especially relevant if your organization’s telemetry is centered on another observability platform.

Overview: The Top 1 Alternative

Here is the top 1 alternative for Datadog Synthetic Tests:

• New Relic Synthetics

Why Look for Datadog Synthetic Tests Alternatives?

Datadog Synthetic Tests covers a lot of ground, but teams commonly explore alternatives for practical reasons such as cost, ecosystem alignment, and feature fit. Common drivers include:

• Cost at scale: Heavy synthetic usage (many checks across multiple global locations and frequent schedules) can become expensive. If your organization runs thousands of test executions per day, pricing and budgeting become central considerations.

• Web/API-only scope: If you also need native mobile app testing (beyond mobile web), you may require additional tools. Consolidating E2E coverage across web, APIs, and native apps often calls for a broader stack.

• Test maintenance overhead and flakiness: Any synthetic/browser automation tool can become flaky if tests are not thoughtfully structured. Dynamic selectors, timing issues, and environment instability require disciplined patterns (e.g., resilient locators, test data isolation, robust waits).

• Ecosystem alignment: Teams already standardized on a different observability platform (e.g., New Relic) may prefer tighter native correlations, unified dashboards, and streamlined alerting in that ecosystem.

• Private networking and configuration complexity: Running synthetics against internal services (e.g., via private locations) introduces operational work—managing runners, credentials, and secure connectivity—regardless of vendor. Some organizations prefer alternatives that better match their existing infrastructure or operational processes.

• Custom scripting preferences: Some teams prefer a primarily code-driven approach from the outset (e.g., JavaScript for scripted monitors), favoring familiarity, versioning discipline, and reuse patterns that match their engineering workflows.

If any of these resonate, evaluating an alternative can clarify trade-offs and potentially lower total cost of ownership while improving developer experience.

Detailed Breakdown of Alternatives

New Relic Synthetics

What it is: New Relic Synthetics is New Relic’s synthetic monitoring and E2E testing solution designed for web and API use cases. It focuses on scripted checks—primarily JavaScript for browser and API monitors—to validate availability, performance, and critical user flows. As part of the broader New Relic observability platform, it ties synthetic signals to APM, logs, and infrastructure metrics for unified visibility.

Who built it: New Relic, a well-known observability company that provides application performance monitoring, logs, infrastructure, and analytics, built and maintains New Relic Synthetics as a native component of its platform.

What makes it different:

• Script-first model: The core experience emphasizes JavaScript-based scripted monitors, which appeals to teams that prefer code-centric authoring, version control, and modular reuse.

• Deep ecosystem integration: Synthetic results naturally correlate with New Relic APM traces, logs, and dashboards, streamlining triage and root cause analysis for teams already using New Relic.

• Consolidated telemetry: For organizations centralized on New Relic, governance and reporting are simplified by keeping synthetic and application telemetry in one place.

Core strengths and capabilities:

• Flexible scripted monitors (JavaScript):

• Native integration with New Relic observability:

• Global and private locations:

• CI/CD compatibility:

• Alerting and SLOs:

• Commercial support and reliability:

How it compares to Datadog Synthetic Tests:

• Authoring model:

• Ecosystem fit:

• Feature breadth:

• Test stability and maintenance:

• Operational considerations:

• Cost:

Best for:

• Teams automating end-to-end flows across browsers and platforms, especially those already operating within New Relic’s observability ecosystem and comfortable with JavaScript-based scripted monitors.

Things to Consider Before Choosing a Datadog Synthetic Tests Alternative

Before changing tools (or adding a second one), align the decision with your technical and organizational context. Consider the following:

• Project scope and coverage:

• Language and authoring approach:

• Ease of setup and onboarding:

• Execution speed and stability:

• CI/CD integration and policy controls:

• Debugging and observability:

• Data and environment management:

• Security and networking:

• Scalability and governance:

• Reporting, alerting, and SLOs:

• Community, support, and roadmap:

• Cost and purchasing model:

• Team skills and ownership:

Conclusion

Datadog Synthetic Tests remains a strong and widely adopted solution for synthetic monitoring and E2E validation across web and APIs. Its combination of recorder-driven flows, programmable steps, CI/CD integrations, and tight linkage with Datadog’s observability stack makes it a pragmatic default for many teams.

However, if you’re consolidating on a different observability platform or prefer a script-first approach, New Relic Synthetics stands out as a compelling alternative. It delivers flexible JavaScript-based monitors, integrates directly with New Relic’s APM/logs/metrics, and offers the global and private execution options needed for modern applications. Teams already invested in New Relic often benefit from simpler governance, unified dashboards, and streamlined incident response when synthetic and application telemetry live together.

When deciding:

• Stay with Datadog Synthetic Tests if your monitoring stack is already Datadog-centric, you want the speed of a recorder plus code workflow, and you value integrated dashboards and alerts alongside Datadog APM and logs.

• Consider New Relic Synthetics if your organization is standardized on New Relic, you prefer JavaScript script-first monitors with strong reuse patterns, and you want native correlation with New Relic’s telemetry to accelerate triage.

Practical next steps:

• Pilot side-by-side: Run a representative subset of your critical user journeys and API checks in both tools. Compare stability, execution time, reporting clarity, and triage speed.

• Set evaluation criteria: Use a scorecard covering ease of authoring, CI integration, failure diagnostics, global coverage, private networking, cost, and team satisfaction.

• Plan for reliability: Regardless of your choice, invest in test design discipline—stable selectors, robust waits, deterministic test data, and clear ownership—to reduce flakiness and operational toil.

Optionally, complement your synthetic strategy with supportive practices and services:

• Use feature flags and safe toggles to keep tests deterministic during rollouts.

• Employ environment-specific mocks or stubs to isolate dependencies where full integration introduces instability.

• Leverage a cloud-based browser grid or headless execution service to parallelize test runs and reduce pipeline time, especially for large suites.

Ultimately, the best tool is the one that aligns with your team’s workflows, skills, and platform investments while delivering stable, actionable insights. For many organizations, Datadog Synthetic Tests will remain the right fit; for others, New Relic Synthetics may offer a cleaner path to integrated, script-first synthetic monitoring within the New Relic ecosystem.