English for Checkly Monitoring Developers
Vocabulary for developers using Checkly — checks-as-code, uptime alerts, browser checks, assertions, and monitoring in CI — for teams discussing synthetic monitoring in English.
Checkly is a synthetic monitoring platform built around “checks-as-code” — you define API and browser checks in your own repository using TypeScript or JavaScript, version them alongside your application code, and run them both on a schedule and inside CI. Its vocabulary sits at the intersection of testing and monitoring, which trips up teams used to thinking of those as separate disciplines. Here’s the English to talk about it clearly.
Checks-as-Code
Checks-as-code — defining monitoring checks in source-controlled files rather than clicking through a dashboard UI, so checks get code review, versioning, and CI integration like any other code. “Every new API endpoint ships with a matching checks-as-code file in the same PR — reviewers can see the monitoring alongside the feature that needs it.”
Check — a single, scheduled test of a specific endpoint or user flow, run from geographically distributed locations to catch regional outages. “We added a check for the checkout API specifically, separate from the general health check, because checkout failing silently is a much bigger deal than a slow static page.”
Check group — a collection of related checks that share configuration (alert channels, locations, environment variables), used to avoid repeating the same settings across many checks. “All the payment-related checks live in one check group, so if we need to add a new alert channel, we set it once instead of updating a dozen checks.”
Types of Checks
API Check
An API check sends a request to a specific endpoint and validates the response, useful for verifying backend correctness without a full browser.
“The API check hits
/healthevery minute from six regions — if three of them start failing, we know it’s a regional network issue, not the app itself.”
Browser Check
A browser check runs a real, scripted user flow in a headless browser (login, add to cart, checkout) to catch issues that only show up in the rendered UI.
“The browser check caught a broken ‘add to cart’ button that the API checks completely missed, since the API itself was returning a healthy 200.”
Assertion
An assertion is a specific condition a check must satisfy to pass — a status code, a response time threshold, or the presence of certain text on a rendered page.
“We added an assertion on response time under 800ms, not just status code 200 — a technically successful but slow response should still trigger an alert.”
Alerting and Reliability
Uptime alert — a notification triggered when a check fails, typically after a configurable number of consecutive failures to avoid paging on a single flaky blip.
“We set the uptime alert to fire after two consecutive failures instead of one — that cut false-positive pages by more than half.”
Alert channel — the destination a failed check’s notification is routed to, like Slack, PagerDuty, or email, configurable per check or check group.
“Payment checks page on-call through the PagerDuty alert channel, while marketing page checks just post to a low-priority Slack channel.”
Monitoring as code in CI — running the same check definitions as part of the deployment pipeline, so a broken flow can block a release before it reaches real users.
“We run the critical browser checks as a CI gate before promoting to production — if checkout is broken, the deploy simply doesn’t go through.”
Explaining Checkly to a Team
| Situation | Phrase |
|---|---|
| Justifying checks-as-code | ”Keeping checks in the repo means they get reviewed and versioned like the feature they’re monitoring, instead of drifting silently in a separate dashboard.” |
| Explaining an alert threshold | ”We require two consecutive failures before paging — that filters out one-off network blips without hiding a real outage.” |
| Describing check coverage | ”API checks confirm the backend is healthy, but the browser check is what actually caught the broken button — we need both.” |
| Discussing CI integration | ”The critical-path browser check runs as a deploy gate now, so a broken checkout flow can’t reach production undetected.” |
Common Mistakes
- Relying only on API checks and assuming the UI is fine — a healthy backend response doesn’t guarantee the frontend renders or wires it up correctly.
- Setting alert thresholds too sensitive (one failure = page) and causing alert fatigue that leads to real outages being ignored.
- Treating checks-as-code files as write-once — like any test, they need updating when the flow they monitor changes, or they start giving false confidence.
Practice Exercise
- Explain, in two sentences, why a team might need both an API check and a browser check for the same feature.
- Write a short PR description for adding a new browser check to a check group, including an assertion on load time.
- Draft a message justifying adding a critical-path check as a CI gate before production deploys.
Related Resources
- English for Bugsnag Error Tracking Developers
- English for VictoriaMetrics Developers
- English for Better Auth Developers
Navigating the Nuances: Practical Phrases for Checkly Users
As a developer working with Checkly, you’ll inevitably find yourself communicating about synthetic monitoring, uptime alerts, and automated checks. While technical terms are important, mastering the language of these discussions – how you phrase your requests, feedback, and reports – can significantly improve collaboration within your team and ensure clarity when interacting with stakeholders. Often, developers from non-English speaking backgrounds may find themselves relying on direct translations which can introduce ambiguity or miss crucial context. This section focuses on developing a more natural and effective way to express yourself within the Checkly ecosystem.
One key area is refining how you describe issues. Instead of simply stating “Website down!”, consider “The synthetic transaction failed three times in a row, indicating a potential issue with [specific component]’s availability.” Notice the inclusion of detail – why it’s an issue, and what component might be involved. This proactive approach demonstrates understanding and helps prioritize investigations. Similarly, when requesting changes to checks or configurations, move beyond vague instructions like “Fix the check.” Instead, frame your request as a problem statement: “The current uptime check isn’t sensitive enough to detect intermittent issues with the API endpoint; can we increase the polling interval?” This clarifies the impact of the change and provides context for the developer. Furthermore, be mindful of using active voice – it generally leads to clearer communication than passive constructions (e.g., “The check was failing” vs. “We observed that the check was failing”).
Another common pitfall is over-reliance on literal translations. Technical jargon often has established English equivalents that are more efficient and universally understood within the DevOps community. Don’t be afraid to use terms like “synthetic transaction,” “uptime SLA,” or “assertion failure” – they’re frequently used and readily grasped by colleagues. Finally, when documenting checks or alerting rules, adopt a clear and concise style, avoiding overly complex sentences. Think about how you would explain the check to someone unfamiliar with your project; clarity is paramount.
Here’s an example of using Checkly to verify a specific scenario:
checkly --url https://www.example.com/api/v1/products --method GET --timeout 5000 --retries 3 --assert "status_code == 200" --assert "response_length > 10"This command demonstrates a simple check using Checkly’s CLI, verifying both the HTTP status code and the response length. This example illustrates how precise technical language is used to define expectations for monitoring and alert functionality. Understanding these nuances will not only improve your communication but also contribute to a more efficient and collaborative workflow within your team.