Waiting for your users to report an outage means you are already losing revenue and trust. A proper synthetic monitoring setup solves this by running scripted, automated checks against your applications and APIs from external locations on a fixed cadence, so you detect failures and performance regressions before real customers hit them. In this guide I walk through how to implement synthetic monitoring for proactive uptime management: what to measure, how to script the checks, where to run them from, and how to route alerts so your team acts on signal instead of noise.
Why Synthetic Monitoring Beats Waiting for Real-User Data
Real-user monitoring (RUM) is valuable, but it has a fundamental limitation: it only tells you about problems after a real user experiences them. If your checkout API breaks at 2 a.m. when traffic is low, RUM may not surface the issue until morning volume returns and revenue is already gone.
Synthetic monitoring inverts that model. Instead of passively observing traffic, we generate deterministic, repeatable transactions on a schedule. This gives us three things RUM cannot:
- Coverage during low-traffic windows. Checks fire every minute regardless of whether users are online.
- Consistent baselines. Because the transaction is identical each run, latency and availability trends are directly comparable over time.
- Pre-production and pre-launch validation. You can point synthetic checks at staging or a new region before customers ever arrive.
Synthetic monitoring is the backbone of proactive uptime management. It pairs naturally with application performance monitoring and website availability testing to give SRE teams an early-warning system rather than a post-mortem tool.
The Four Types of Checks to Plan For
Before writing a single script, decide what you are protecting. Most teams need a mix of the following.
1. Uptime and Availability Checks
The simplest check: does the endpoint respond, with the expected status code, within a threshold? This is your baseline for website availability testing.
2. API Monitoring
APIs are where business logic lives, so api monitoring deserves first-class treatment. Validate status codes, response schema, payload contents, and latency. A 200 OK that returns an empty or malformed body is still a failure.
3. Multi-Step Transaction Checks
Critical user journeys (login, search, add-to-cart, checkout) span multiple requests and often a real browser. Script the whole flow, not just the landing page.
4. SSL and DNS Checks
Certificate expiry and DNS resolution failures cause hard outages that are trivially preventable. Monitor certificate expiration windows and alert well in advance.
Step-by-Step Synthetic Monitoring Setup
Here is the sequence I follow when standing up synthetic monitoring for a new service.
Step 1: Inventory Your Critical Paths
You cannot monitor everything with equal priority, and trying to will bury real alerts. Start by listing the transactions that directly affect revenue or safety. Rank them, then instrument the top handful first.
A useful exercise: for each candidate check, ask "if this fails silently for 15 minutes, what does it cost?" If the answer is "nothing measurable," it does not belong in your first tier.
Step 2: Define SLOs and Thresholds
Every check needs an explicit target. Vague goals like "the site should be fast" are unactionable. Set concrete objectives:
- Availability: 99.9% success rate measured over rolling 30 days.
- Latency: p95 response under 800 ms for the login API.
- Certificate expiry: alert at 21 days remaining.
These thresholds become the pass/fail criteria your alerting depends on.
Step 3: Write an API Check
Below is a minimal HTTP API check expressed as a config. Most synthetic platforms accept a similar declarative format, and the same logic works in a custom runner.
name: checkout-api-health
type: api
request:
method: POST
url: https://api.example.com/v1/cart/validate
headers:
Content-Type: application/json
Authorization: Bearer ${SYNTHETIC_TOKEN}
body: '{"cartId": "synthetic-canary-001"}'
assertions:
- type: status_code
operator: equals
value: 200
- type: response_time
operator: less_than
value: 800 # milliseconds
- type: json_body
path: $.status
operator: equals
value: "valid"
schedule:
every: 60s
locations:
- us-east
- eu-west
- ap-southeast
Notice three things: we assert on the body, not just the status code; we enforce a latency ceiling; and we run from multiple regions.
Step 4: Script a Browser Transaction
For multi-step journeys, use a headless browser. Here is a Playwright example that logs in and verifies the dashboard renders.
const { chromium } = require('playwright');
(async () => {
const browser = await chromium.launch();
const page = await browser.newPage();
const start = Date.now();
try {
await page.goto('https://app.example.com/login', { timeout: 15000 });
await page.fill('#email', process.env.CANARY_USER);
await page.fill('#password', process.env.CANARY_PASS);
await page.click('button[type="submit"]');
// Wait for a post-login element to confirm the journey succeeded
await page.waitForSelector('[data-testid="dashboard-widget"]', {
timeout: 10000,
});
const duration = Date.now() - start;
console.log(`PASS login flow in ${duration}ms`);
} catch (err) {
console.error(`FAIL login flow: ${err.message}`);
process.exitCode = 1;
} finally {
await browser.close();
}
})();
Use a dedicated canary account with a scoped, non-production identity so synthetic traffic never contaminates real business data or analytics.
Step 5: Run From Multiple Geographies
A check that only runs from one region tells you nothing about users elsewhere. Distribute checks across the regions where your customers actually are. Regional runs also help you distinguish a true application outage from a localized network or CDN problem: if us-east fails but eu-west passes, the fault is likely regional.
Step 6: Tune Alerting to Reduce Noise
The fastest way to get synthetic monitoring ignored is to alert on every single failed run. Transient blips happen. Apply these controls:
- Failure thresholds. Require N consecutive failures (for example, 3) before paging.
- Multi-location confirmation. Only page when the failure reproduces from more than one region.
- Severity routing. A certificate 21 days from expiry is a ticket. A checkout outage is a page.
- Deduplication windows. Suppress repeat alerts for the same open incident.
Wire alerts into your existing incident workflow so ownership is unambiguous. This discipline is central to reliable application performance monitoring at scale, and it is a core part of how our managed services and SRE capabilities approach on-call sustainability.
Step 7: Correlate With Internal Telemetry
Synthetic checks tell you that something is wrong. To learn why, correlate the failure timestamp with your logs, traces, and metrics. Include a trace-id header in synthetic requests so the failing transaction is directly findable in your distributed tracing system:
X-Synthetic-Trace: canary-checkout-2024-06-14T02:11:07Z
This closes the loop between detection and diagnosis, cutting mean time to resolution.
Common Pitfalls to Avoid
- Monitoring only the homepage. A green homepage says nothing about a broken payment path.
- Static test data that expires. Canary accounts, tokens, and fixtures rot. Rotate and validate them.
- Ignoring the third-party dependency problem. If your check fails because a payment provider is down, your alert should reflect that distinction, not blame your own service.
- No ownership. An alert with no clear owner is an alert that gets snoozed.
Requirements differ by sector. A fintech checkout flow and a healthcare portal have very different compliance and latency expectations, which is why we tailor synthetic coverage to specific industry contexts rather than applying one template everywhere.
Putting It Into Practice
Start small and expand. Instrument your single most important transaction, set an honest SLO, run it from two or three regions, and route a well-tuned alert to a named owner. Once that loop is trustworthy, add the next journey. Within a few iterations you will have a synthetic monitoring layer that catches regressions before your customers do, which is the entire point of proactive uptime management.
The measure of success is simple: your team learns about problems from a dashboard, not from a support ticket.
FAQ
How often should synthetic checks run?
For revenue-critical paths, a 1-minute interval is a common baseline. Lower-priority checks can run every 5 to 15 minutes. Balance detection speed against the cost and load of frequent runs, and never run so aggressively that your synthetic traffic distorts capacity planning.
What is the difference between synthetic monitoring and real-user monitoring?
Synthetic monitoring generates scripted transactions on a schedule from controlled locations, giving you coverage even without live traffic. Real-user monitoring passively observes actual user sessions. They are complementary: synthetic catches issues proactively, while RUM reflects genuine user experience and geographic distribution.
Can synthetic monitoring test authenticated flows safely?
Yes. Use a dedicated canary account with scoped, non-production permissions and clearly labeled test data. Exclude canary activity from analytics and billing, and rotate credentials on a schedule so expired tokens do not cause false alarms.
How do I keep synthetic alerts from becoming noise?
Require multiple consecutive failures and confirmation from more than one region before paging, route alerts by severity, and apply deduplication windows. Assign every check an explicit owner so no alert is orphaned.
Does synthetic monitoring replace application performance monitoring?
No. Synthetic monitoring is one input into a broader application performance monitoring strategy. It excels at detection and availability testing, but you still need logs, traces, and metrics to diagnose root cause once a check fails.
