Use the simplest check that can detect the failure you care about: an HTTP probe for availability and response behavior, or a browser script for visible content and user journeys. A green HTTP check means only that a particular runner received the response its check accepts; it does not prove that a visitor can log in, complete checkout, or use the whole site. The examples below show how to define success, preserve the monitored URL as the result identity, capture useful failure details, and get failures to an operator.
Choose what the script must prove
Before choosing a tool or writing code, spell out the failure that matters. “The site is up” is too vague to be a reliable test: a server can return a response while serving an error page, and a landing page can load while a critical workflow is broken.
- Endpoint reachable: use an HTTP or TCP probe to detect connection, DNS, TLS, or protocol-level problems.
- Expected response: check the HTTP status and, when useful, a stable part of the response body.
- Acceptable speed: record duration and alert on a threshold chosen for the endpoint and use case.
- Page usable: use a browser check to verify rendered content or a user-visible state.
- Journey works: use a browser test for the smallest meaningful multi-step flow, such as reaching a confirmation state after submitting a test transaction.
A monitor also needs an explicit runner identity and location. A result tells you what that runner could reach from its network position; a single runner cannot establish availability from every region or network.
Example 1: probe a website with Prometheus Blackbox Exporter
Prometheus Blackbox Exporter performs probes on behalf of Prometheus. The official multi-target exporter guide demonstrates a direct probe request like this:
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curl 'localhost:9115/probe?target=prometheus.io&module=http_2xx'
This assumes an exporter is already listening on localhost port 9115 and has a module named http_2xx configured. The module determines what constitutes a successful HTTP probe. Output includes probe measurements such as DNS lookup timing, HTTP phase durations, status code, TLS details, and certificate expiry. This is useful for external availability and protocol signals; it does not render a page or exercise a visitor’s browser workflow. See the Prometheus multi-target exporter guide.
Preserve the website as the target identity
For recurring checks, Prometheus scrapes the exporter’s /probe endpoint and passes the monitored URL and module as parameters. The exporter address is the scrape destination, not the site being tested. If the configuration leaves the exporter address as the series’ instance label, dashboards and alerts can misleadingly identify the exporter instead of the probed website. Preserve the original target in a separate label and set instance to that target:
scrape_configs:
- job_name: blackbox-http
metrics_path: /probe
params:
module: [http_2xx]
static_configs:
- targets:
- https://example.com/
- https://status.example.com/
relabel_configs:
- source_labels: [__address__]
target_label: __param_target
- source_labels: [__param_target]
target_label: instance
- target_label: __address__
replacement: blackbox-exporter:9115
Here blackbox-exporter:9115 must resolve to the exporter from the Prometheus runner’s network, and the configured http_2xx module must exist on that exporter. The first relabel rule passes each listed website as the probe’s target; the second keeps that website visible as instance; the final rule directs Prometheus to scrape the exporter. Adapt the exporter hostname and targets to your deployment. Prometheus must be configured to scrape this job for checks to recur.
Set a scrape interval deliberately. The Prometheus guide uses five seconds in a tutorial example, not as a universal recommendation. A very short interval can generate needless traffic and operational noise; a long interval can delay detection. Choose a cadence appropriate to the endpoint, acceptable detection delay, probe capacity, and the load you are willing to create.
Read the result in context
Use the probe’s success metric together with status, duration, DNS, TLS, and other phase measurements to distinguish a failed check from a slow or partially degraded one. Decide which conditions page someone: for example, whether one failed probe is enough, or whether the alert should require repeated failures. That policy depends on the service’s risk and tolerance for transient network errors; a single successful probe should not be treated as proof of overall health.
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Prometheus collects measurements by scraping metrics endpoints; its first steps guide explains the general model. The Blackbox Exporter is a self-hosted option, so you operate the exporter, Prometheus, storage, dashboards, and notification path. Connect alert rules to an alerting destination your team monitors; collecting a metric alone does not notify anyone.
Example 2: check rendered content with Playwright
An HTTP response check cannot establish that the browser rendered the right content. A Playwright test can open a page and assert that an expected visible element exists. This standalone Node.js example uses Playwright’s test runner:
import { test, expect } from '@playwright/test';
test('homepage shows the expected page heading', async ({ page }) => {
await page.goto('https://example.com/', { waitUntil: 'domcontentloaded' });
await expect(page.getByRole('heading', { name: 'Example Domain' })).toBeVisible();
});
Save it as tests/homepage.spec.js in a project with @playwright/test installed, then run it with npx playwright test tests/homepage.spec.js. The example checks content on the example domain, so replace its URL and assertion with a stable, meaningful condition on your own site. The assertion is illustrative, not evidence about any other site’s health.
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Run checks periodically and expose results
A test that runs only when a developer starts it is a test, not ongoing monitoring. Schedule it in a CI runner, container, or other controlled environment, preserve the exit status and useful error output, and connect failed runs to a notification path. A Playwright synthetic monitoring example project runs tests periodically in a Docker image and exposes Prometheus metrics and a health-check endpoint; its README says its default interval is every five minutes and can be configured. Those are properties of that project, not defaults of Playwright. The project also says it does not deliver alerts itself, so a separate monitoring or notification system is needed. See the Playwright Synthetic Monitoring project README.
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Authentication changes, test data, cookie state, and external dependencies can cause synthetic failures that are not the same as a public outage. Make the test account and cleanup behavior explicit, and distinguish an application assertion failure from a runner or dependency failure in the information you retain.
Prometheus probe or browser journey?
| Approach | What it can establish | What it does not establish | Operational responsibility |
|---|---|---|---|
| HTTP/TCP probe | Reachability and configured protocol or response checks; useful timing and connection measurements depend on the probe. | That a browser rendered the intended interface or that a multi-step user workflow succeeds. | With a self-hosted exporter and Prometheus, you operate the probe runner, metrics collection, history, alert rules, and notification path. |
| Playwright synthetic check | That a browser can perform the scripted actions and satisfy the assertions from its runner’s environment. | That every user, region, account, or untested path sees the same result. | You maintain the script, runtime, schedule, test data, result storage, and alert delivery or integration. |
Choose based on the failure you need to detect, not on which tool has the longer feature list. A lightweight endpoint probe is generally the better fit for protocol availability and response timing. A browser test is warranted when rendering, client-side behavior, authentication, or a user journey is part of the service promise. Many teams use both because the checks answer different questions.
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Managed monitoring options
If operating runners and result storage is not the right fit, managed services are another execution model. Google Cloud documents HTTP, HTTPS, and TCP uptime checks, custom synthetic monitors, and broken-link checks. Grafana Cloud documents HTTP/HTTPS, scripted and browser, DNS, TCP, ICMP, and traceroute checks. New Relic documents API management for synthetic monitors, including scripted browser and API types. Their features, regional availability, limits, and prices can change; the cited documentation establishes these capabilities, not a current plan or price comparison.
- Google Cloud synthetic monitoring overview
- Grafana Cloud Synthetic Monitoring
- New Relic Synthetics REST API
Make alerts useful, not merely frequent
A monitor becomes operationally valuable when a failure reaches someone who can act on it. Keep the measurement and failure detail needed to diagnose the alert without leaking secrets.
- Record: target identity, check or test name, pass/fail state, timing, timestamp, and useful status or assertion error.
- Alert on an owned condition: define the failure threshold and who responds. A threshold that is too sensitive can produce noise; one that is too forgiving can hide an outage.
- Separate symptoms: distinguish connection/TLS/DNS failures, unexpected HTTP status, slow responses, assertion failures, and runner errors where possible.
- Keep credentials private: do not emit authorization headers, cookies, passwords, or tokens into metrics labels, logs, alerts, or committed test files.
- Document the vantage point: state where the runner executes and which network path it uses. If regional differences matter, checks from multiple locations may be needed.
Google Cloud describes synthetic monitors as simulated requests that periodically record success and additional request data such as latency in its synthetic monitoring overview. Its documentation also notes a geographic qualification worth checking before choosing a configuration: public uptime checks can use multiple global locations and checker regions can be specified, but request data is not guaranteed to remain in a particular geographic location. For synthetic monitors using Cloud Run functions, the function can be invoked from any region supported by uptime-check servers, and that behavior is not configurable. A function’s deployment region therefore should not be assumed to define the whole monitoring path.
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Troubleshooting common monitoring failures
The probe says the site is down, but it loads for you
Compare the probe target, DNS resolution, TLS measurements, and runner network path with your browser’s context. The runner may be in a different network location, may not have access to a private endpoint, or may encounter a region-specific problem. Confirm the exact URL and module before changing alert thresholds.
The probe is green, but users report a broken page
An HTTP check can pass while client-side scripts, authentication, page content, or checkout is broken. Add a browser assertion for the affected user-visible outcome, and keep the endpoint probe for the separate availability signal.
Metrics identify the exporter instead of the website
Check that relabeling passes the original target as __param_target, copies it to instance, and then sets __address__ to the exporter address. Without target preservation, a dashboard may obscure which URL was actually probed.
The browser test fails intermittently
Inspect whether the failure is in navigation, an assertion, authentication, test data, or a third-party dependency. Prefer stable visible assertions, isolate test accounts and data, and avoid relying on arbitrary fixed delays when the script can wait for a meaningful visible condition. Keep enough error output to diagnose the failing step while excluding secrets.
Checks run but nobody receives an alert
Verify the whole path: the scheduled job or Prometheus scrape is running, failures affect the expected metric or exit status, alert rules match that condition, and a notification destination is configured and reachable. A check endpoint or metrics export is not, by itself, alert delivery.
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Checks create load or too many notifications
Revisit cadence, number of targets, and browser workflow cost. A frequent browser journey can consume more runner resources and exercise more application paths than a simple request. Use a cadence that meets the detection goal without creating unnecessary traffic, and alert on a considered failure policy rather than every isolated transient error.
Or skip the browser setup
If the task is to capture a page image or PDF rather than build and operate a browser monitor, ScreenshotNeo is a website screenshot API and MCP server. One GET request can return a PNG, JPEG, WebP, or PDF; it is not a substitute for Prometheus metrics, scheduled alerting, or a Playwright assertion. A basic capture with cURL is:
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Frequently Asked Questions
Can a website return HTTP 200 and still be broken?
Yes. The response can be successful while important content or a browser-driven workflow is not; choose a browser assertion for that user-visible requirement.
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