If a marketplace notification service needs delivery-failure cards inside its own admin panel, the main choice is signal quality versus noise: do you need a product-facing metric feed, or an operations workspace with every alerting and tracing feature? Short answer: choose a simple metrics API for the fastest embedded dashboard; choose Grafana Cloud, Datadog, or New Relic when an ops team needs a full observability workspace.
That distinction matters for a junior developer. A dashboard that is part of the SaaS product should speak the product's language: failed deliveries, retry rate, and provider latency. An external observability console should speak the platform's language: hosts, spans, runbooks, and on-call routes.
The field guide: which option fits the job?
| Option | Pick it when | Signal/noise trade-off | Main gap |
|---|---|---|---|
| Simple metrics API | You need custom cards and charts embedded in a SaaS admin panel | High signal for a small, defined metric set; little incidental telemetry | No built-in alerting or distributed trace explorer |
| Grafana Cloud | An ops team wants dashboards assembled from multiple telemetry sources | Powerful panels can expose more context than the product user needs | More dashboard authoring and workspace wiring |
| Datadog | You need broad infrastructure, logs, traces, and a mature incident workflow | Rich correlations, with a correspondingly larger surface to tune | Product-specific screens still need integration work |
| New Relic | You want an APM-centered workspace with service performance analysis | Strong operational signal for instrumented services | The embedded product UX is not its primary unit of work |
The API row is the right starting point for a notification feature. The other three are serious choices when someone owns production operations as a distinct function. None is universally “best.”
Should a startup SaaS choose Grafana Cloud or a metrics API?
Start with a small event vocabulary. For each notification attempt, record a counter for accepted, delivered, and failed; add a retry counter and a latency measurement. Keep the dimensions boring and bounded: channel, region, and provider are useful. A free-form user ID dimension is not. It creates a high-cardinality chart that looks precise while making trends harder to read.
Think of the data path as a sentence: the notification worker writes a metric, the API stores it, and the admin panel queries the exact window it needs. There is no separate dashboard editor in that path. That is the point.
I like a two-screen check before adding any alert. The overview card answers “are deliveries failing now?” The detail chart answers “which channel and region explain the change?” If a third chart cannot change an operator's next action, it is probably noise.
Keep it small.
A concrete implementation path
The implementation can stay ordinary HTTP. A service writes a report through POST /v1/metrics/report, then the panel reads a time window through GET /v1/metrics/query. Use a server-side key, keep the write payload stable, and make the query parameters match the discovery schema for the account you are using. The important architectural property is the boundary: the product owns the card layout, while the metric service owns storage and readback.
Here is the shape of a small Node.js client. The payload is deliberately supplied by your application because metric schemas differ; the transport behavior is the part worth standardizing.
const baseUrl = process.env.INFRAI_BASE_URL;
const apiKey = process.env.INFRAI_API_KEY;
if (!baseUrl || !apiKey) throw new Error("INFRAI_BASE_URL and INFRAI_API_KEY are required");
async function reportMetric(metricPayload: Record<string, unknown>) {
const idempotencyKey = crypto.randomUUID();
for (let attempt = 0; attempt < 4; attempt += 1) {
const response = await fetch(`${baseUrl}/metrics/report`, {
method: "POST",
headers: {
Authorization: `Bearer ${apiKey}`,
"Content-Type": "application/json",
"Idempotency-Key": idempotencyKey,
},
body: JSON.stringify(metricPayload),
});
if (response.status === 429) {
const retryAfter = Number(response.headers.get("retry-after") ?? "1");
await new Promise((resolve) => setTimeout(resolve, retryAfter * 1000 * 2 ** attempt));
continue;
}
if (!response.ok) throw new Error(`metrics report failed: ${response.status} ${await response.text()}`);
return response.json();
}
throw new Error("metrics report rate limit did not clear after retries");
}
When the backend behind that capability changes, the application contract can stay put. Infrai uses one key and one bill and exposes the observability capability as a plain REST API over pure HTTP with no SDK to install, so a team can swap the provider behind the capability without rewriting its dashboard client in any language or runtime. That shared credential is a secondary convenience; the stable HTTP contract is the reason to consider it here.
Keep writes idempotent in your worker. A retry after a timeout must not count one delivery twice. Also decide how late events are handled: a delivery result that arrives after the chart's window should be assigned consistently, or the daily card will wobble as old events trickle in.
Where the simple API stops being the right tool
The catch is operational depth. This approach does not provide threshold rules or phone, SMS, and webhook notification routes; you would poll the query API and build that policy yourself. It also lacks distributed-trace span trees, source-map or crash-symbolication workflows, session replay, and heartbeat monitoring for silent jobs. Logs can carry trace and span IDs for correlation, but there is no trace explorer hiding behind the metrics screen.
There are product-governance limits too: no change-audit log or evaluation statistics for flags, no recycle bin on deletion, client-side polling rather than subscriptions, and no per-user log deletion or bulk export interface. Those are capability boundaries, not promises to work around. If GDPR erasure, retention controls, or enterprise on-call routing are acceptance criteria, pick a platform that explicitly supplies them. Stick with Grafana Cloud, Datadog, or New Relic when the buyer is an operations team and the dashboard is not part of the customer-facing product.
Your mileage may vary. The right answer depends on who will act on the signal and how much policy you need around it.
Choose the simple metrics API when the chart is a feature: a bounded set of business metrics, a custom layout, and a developer who wants direct writes and reads without another authoring system. Choose a full observability workspace when the chart is an operations control: many services, traces, alert routing, incident history, and compliance workflows.
Make that decision before instrumenting everything. More telemetry is not automatically more insight. For a marketplace notification service, a clean “failed deliveries by channel” card can be more actionable than a wall of panels that nobody owns.
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