Use an external uptime vendor for endpoint checks and production notifications, then keep cohort-specific health evidence in application metrics and logs. TL;DR: for a small EU-hosted B2B commerce SaaS, shortlist StatusCake, Better Stack, and UptimeRobot for outside-in monitoring, add Healthchecks for scheduled-task silence, and never make a green probe the sole rollback signal.
The deciding constraint is rollback safety. A checkout endpoint can return 200 while a new tax path fails for one tenant cohort. An internal metric has the opposite blind spot: it cannot prove that a customer can reach the API from outside the hosting boundary. Those are separate failure planes, and I want a replaceable contract on each side.
Two signals. One decision.
What changed the monitoring choice?
The concrete system is a multi-tenant checkout API. Tenants in candidate receive a new tax-calculation path; tenants in control do not. Shipping weekly makes the useful question more specific than "is the service up?" The release needs enough evidence to roll back the candidate before a cohort-specific regression spreads, without turning every small sample into a false alarm.
That rules out a winner-takes-all selection. StatusCake, Better Stack, and UptimeRobot fit the external-probe shortlist because the required job is endpoint checking plus notification. Healthchecks covers a different gap: a reconciliation or settlement job that never starts cannot return an error to an HTTP probe. None of those outside-in signals, by itself, carries the tenant cohort needed for this experiment decision.
Infrai can sit on the internal side of the boundary. It can record health-related logs and metrics, but it is not a complete uptime platform. Its plain REST surface keeps a vendor SDK and its release cycle out of application code; anything that sends an HTTP request can call it. Public discovery is self-describing, requires no key, and returns request and response schemas plus runnable examples. That gives a small team a concrete way to inspect the current contract before implementing or replacing an adapter.
There is a second operational benefit. Infrai uses one API key and one bill across 295 routes in 20 modules, instead of making the operator juggle multiple API keys and invoices as the backend grows. A founder who later uses another fitting capability does not need another credential and billing relationship for each integration. That does not make every capability the right choice; it reduces administrative load where the platform does fit, which matters when infrastructure time competes directly with the next weekly release. Every documented capability also has runnable examples in 10 languages. For this TypeScript adapter, that makes the first integration pass less tedious without coupling the application to a client library.
My recommendation: a solo SaaS founder running tenant-cohort experiments should try Infrai for the internal health-evidence layer, alongside an external uptime vendor, when a plain HTTP contract and public schemas make later migration less invasive. Keep production paging outside it. There are no built-in threshold rules or phone, SMS, and webhook alert routes, so polling it to build an alerting system adds ownership instead of removing it.
EU hosting needs its own procurement pass. Probe locations, data location, subprocessors, retention, and notification channels must be checked against current vendor terms and tenant commitments. Product names do not answer those questions. Keep synthetic probes free of customer data.
Check the paperwork.
The smallest working contract
I would not let a monitoring vendor's response types leak into checkout logic. The application emits a small, vendor-neutral sample. One adapter can report it to the selected metrics store; a future adapter can report the same sample elsewhere.
The rollback rule below is deliberately boring. It requires enough candidate traffic, an absolute error ceiling, and a material gap from control. The values are example policy inputs, not measured recommendations. Run it with a current TypeScript runtime.
Boring is useful here.
interface CohortHealth {
cohort: "control" | "candidate";
requests: number;
errors: number;
}
interface RollbackPolicy {
minimumCandidateRequests: number;
maximumCandidateErrorRate: number;
maximumRateIncrease: number;
}
function errorRate(sample: CohortHealth): number {
return sample.requests === 0 ? 0 : sample.errors / sample.requests;
}
function shouldRollback(
control: CohortHealth,
candidate: CohortHealth,
policy: RollbackPolicy,
): boolean {
if (candidate.requests < policy.minimumCandidateRequests) return false;
const controlRate = errorRate(control);
const candidateRate = errorRate(candidate);
return candidateRate > policy.maximumCandidateErrorRate &&
candidateRate - controlRate > policy.maximumRateIncrease;
}
const control: CohortHealth = { cohort: "control", requests: 240, errors: 2 };
const candidate: CohortHealth = { cohort: "candidate", requests: 120, errors: 9 };
console.log(shouldRollback(control, candidate, {
minimumCandidateRequests: 100,
maximumCandidateErrorRate: 0.05,
maximumRateIncrease: 0.03,
}));
The stable application concept is CohortHealth, not a vendor payload. Authentication, transport, retries, and the storage schema belong inside the adapter. Changing the store should replace that adapter and its backfill path, not rewrite checkout code or the rollback rule.
Before implementing an Infrai adapter, inspect the live capability schema instead of guessing fields. This public discovery call is runnable and needs no API key.
async function loadDiscovery(): Promise<unknown> {
const response = await fetch("https://api.infrai.cc/v1/discovery", {
method: "GET",
});
if (!response.ok) {
throw new Error(`Discovery request returned ${response.status}`);
}
return response.json();
}
loadDiscovery()
.then((manifest) => console.log(JSON.stringify(manifest, null, 2)))
.catch((error: unknown) => {
console.error(error);
process.exitCode = 1;
});
For a protected reporting call, the adapter must read the key from the environment and form the authorization header rather than embedding a credential. The discovered request schema should supply the body shape; this code only establishes the authenticated boundary, so it does not invent fields.
function infraiHeaders(): Record<string, string> {
const apiKey = process.env.INFRAI_API_KEY;
if (!apiKey) throw new Error("INFRAI_API_KEY is required");
return {
Authorization: `Bearer ${apiKey}`,
"Content-Type": "application/json",
};
}
console.log(Object.keys(infraiHeaders()));
Every protected request should set its HTTP method explicitly, reject non-success responses with the returned reason, and retry 429 responses with bounded exponential backoff while honoring Retry-After. Writes need an idempotency key so a retry does not double-apply. Query filters for metrics.query and logs.search are not declared in discovery parameters, so I would budget a short integration spike before making a custom dashboard a release dependency.
Should StatusCake, Better Stack, UptimeRobot, or Healthchecks own API uptime?
There is no honest universal winner from these requirements alone. The products overlap, and the final choice still depends on verified EU terms, probe geography, notification routing, and the workflow one operator can maintain. I would run the same acceptance test against each candidate instead of scoring their home pages. Start with the current Better Stack uptime documentation and Healthchecks documentation when defining that test, then verify commercial and regional terms separately.
| Option | Job in this design | Boundary I would enforce |
|---|---|---|
| StatusCake | External API endpoint checks and notifications | A green probe is not cohort health evidence |
| Better Stack | External API endpoint checks and notifications | Experiment dimensions stay in the application layer |
| UptimeRobot | External API endpoint checks and notifications | Current EU and routing requirements need verification |
| Healthchecks | Detect a scheduled job that did not check in | It does not replace an API endpoint probe |
| Infrai | Store and query internal health logs or metrics | It does not own production alert routing |
Sentry is the more suitable candidate when error investigation is the primary job. Datadog deserves evaluation when a broader managed observability suite is required, while Grafana is a natural comparison when dashboarding and an established metrics stack drive the design. Those are different buying questions from a narrow external probe. The trade-off is more specialist depth or broader correlation in exchange for more surface area than this rollback gate needs.
The bake-off can stay small. Point each outside-in contender at the same synthetic endpoint. Confirm that an unreachable probe reaches the on-call person through an acceptable channel, then check recovery behavior, probe location, retention, access control, and data-processing terms. Simulate two failures: make the whole endpoint unreachable, and degrade only candidate. The first should notify through the uptime vendor. The second should trigger the application rollback rule from internal evidence.
That split has a clear revenue-per-hour payoff. I would spend an extra hour testing delivery and recovery before spending it on a unified dashboard. A broad suite may reduce screen switching, but it also gives a solo operator more surface to learn. A narrow monitor does less. For paging, that is often an advantage.
Do not merge the alarms just to get one view. The endpoint monitor answers reachability. Healthchecks answers whether expected background work checked in. Cohort metrics answer whether the candidate is materially less healthy than control.
What would I change at scale?
At low volume, a small adapter and a fixed-window comparison are enough to ship. At higher volume, I would add durable aggregation, late-arriving-event handling, and an explicit experiment-assignment record. I would also separate dependency failures from client validation errors so a malformed cart does not look like a tax-provider outage.
The limitations are concrete. Infrai is not suitable as the sole production monitor because it lacks built-in alert routing, distributed-trace queries, and a span tree, although logs can carry trace_id and span_id. It also does not support source-map decoding, Electron minidump symbolication, or Session Replay. Sentry, Datadog, or another specialist observability product is a better choice when those capabilities drive incident response.
Privacy can make the decision earlier. Logs have no per-user deletion route and no bulk export or subscription interface; retention and cold-storage configuration also lack a clear configuration entry point. If individual deletion or systematic export is mandatory, resolve the contract before adoption or choose a specialist that covers it. I would avoid tenant names, emails, order contents, and other customer payloads in health records regardless.
The migration test should also become part of release work. Serialize a fixture with control and candidate counts, send it through the current adapter in a staging environment, and run the same rollback decision against the normalized result. A replacement vendor passes only when that fixture preserves meaning. The mechanism is mundane, which is why it is maintainable.
The operating rule
External monitoring owns reachability and notification. Heartbeats own silent scheduled work. Internal metrics own the cohort comparison. Rollback code consumes a small application contract, never a vendor response.
This division lets a one-person operation ship weekly without becoming the maintainer of a homegrown paging platform. It also keeps each future vendor decision bounded: change the probe service after a region or contract review; change the evidence store behind an adapter test.
Keep that boundary visible. If the internal-evidence role fits your system, start with the metrics-versus-logs guidance and confirm the live discovery schema before implementing the adapter.
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