How to set up Datadog monitoring for a Webflow Cloud app

Webflow Cloud applications can be instrumented with Datadog despite lacking direct infrastructure access by sending custom metrics through outbound requests from Next.js Route Handlers. Setup requires a Datadog API key, the correct regional Datadog site, Webflow Cloud environment variables, and a deliberate plan for only a few meaningful metrics, since billing depends on unique metric-and-tag combinations. A custom function can post metrics to Datadog’s series API using timestamps in seconds and appropriate metric types, while errors should be logged rather than allowed to affect application requests. To avoid adding monitoring latency or competing with Webflow Cloud’s limited outbound connections, metric submissions should use Cloudflare’s waitUntil mechanism after the response is sent. Tags should represent useful aggregate dimensions such as environment, route, status, or region rather than high-cardinality values like user IDs or request IDs, which can sharply increase costs. Effective monitoring also requires alerts configured for both unhealthy thresholds and missing data, because a fully unavailable application may emit no metrics at all. Common problems include sending data to the wrong Datadog site, using millisecond timestamps, awaiting monitoring calls in request handlers, and accumulating expensive high-cardinality tags; after basic metrics and alerts work, error tracking, logs, browser monitoring, and synthetic tests are recommended additions.

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