How Vio.com Uses Checkly to Catch Issues in Minutes and Cut Monitoring Overhead

Vio.com operates one of the world’s fastest-growing travel search and booking platforms, helping millions of users compare prices across hundreds of booking sites worldwide to find the perfect stay at the best price. 

With a mission to make travel effortless, inspiring, and fair, Vio.com integrates with major providers like Booking.com, Expedia, and other OTAs, operating in over 100 markets. With critical flows relying on real-time search results, hotel-level pricing, and third-party redirect logic, the team needs constant visibility into what’s working and what’s not.

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The Challenge

Vio.com started their synthetic monitoring journey with Datadog Synthetics, which gave them solid visibility into production health early on. But as their monitoring needs grew more complex, the team began to run into a few practical limitations.

As they looked to scale monitoring more efficiently, the team began exploring alternatives that could better match their preferred workflows, while still maintaining strong coverage and fast feedback loops.

Rising costs at scale

Datadog provided reliable coverage, but expanding their test suite quickly became expensive, especially as the team looked to add more tests across multiple environments.

Developer workflow friction

While the platform supported code-based test management via Terraform, this introduced a learning curve for front-end engineers who primarily worked in JavaScript and TypeScript.

Limited flexibility in custom setups

To tailor the monitoring experience further, the team built a custom Playwright test runner using GitHub Actions. It worked but came with trade-offs, like being tied to a single region and occasional instability.

Debugging overhead

Investigating test failures in the custom system often meant digging through logs and raw Playwright output, without the benefit of a dedicated UI or trace viewer.

The Solution

Checkly became the ideal middle ground. Several factors made it the long-term synthetic monitoring platform of choice for Vio.com.

It combined everything the team liked about Datadog (visual test feedback, scheduling, alerting) with everything they loved about their own Playwright-based system (code-based test logic, flexibility, ease of maintenance).

Migration was easy. The team already wrote Playwright tests in structured folders based on priority (/critical, /hourly, /daily). With minimal setup, they began running all tests through Checkly and phased out their GitHub Actions scheduler.

Even now, new engineers can get up to speed fast, thanks to a standardized test framework and simple folder structure. No onboarding bottlenecks, no extra tooling.

Built for developers

Checkly’s Playwright-native support meant front-end engineers could finally own and manage their monitoring setup—no need for YAML-heavy configurations.

True Monitoring as Code

Vio.com defines all checks in code and only uses the Checkly UI for debugging. Folder structure maps directly to scheduling behavior, and deployment is automated.

Reliable alerts and faster triage

Checkly alerts engineers in Slack when tests fail. From there, they can view traces, video replays, and logs—right from the notification—cutting debugging time down to seconds.

More coverage, less cost

The team reduced its monitoring bill by more than 50% while expanding test coverage. Their current Checkly plan still has headroom, allowing for further growth without additional spend.

With Playwright and Checkly, writing and maintaining tests is much easier. We get the benefits of synthetic monitoring using tools our engineers already know, and migrating was seamless since our suite was already written in Playwright.

Dale French

Engineering Manager, Vio.com

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What They Monitor With Checkly

Vio.com now successfully uses Checkly to monitor the crucial flows on their website.

Search result pages

Ensuring the correct hotels and dates show up in key destination searches

Hotel-level results

Confirming the right hotel IDs map to the correct detail pages

Booking redirection flows

Validating partner and direct booking options redirects to the right destinations

Support features

 Like "freeze a price" functionality—monitored daily

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# scaffold a project with example checks

npm create checkly@latest

# run them from our global locations

npx checkly test

# turn them into production monitors

npx checkly deploy