Use a low, request-level baseline sample for routine visibility, then add ordered trace rules for the paths or debug requests that matter most. Cloudflare decides whether to trace when each request arrives, so it cannot currently retain only requests that later become slow or fail. For one investigation, match a custom debug header at 100% sampling, and choose separately whether traces are persisted in Cloudflare, exported to OpenTelemetry destinations, or both.
What Cloudflare Traces samples
Cloudflare Traces uses head-based, request-level sampling. The sampling decision is made as a request arrives, before Cloudflare knows its final latency, status code, or exception outcome. If the request is selected, Cloudflare records the full supported request path for that request rather than collecting only a small span fragment.
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The default rate is a percentage. A 10% setting means approximately 10 requests out of every 100 are selected over time; it does not mean that every tenth request is guaranteed to be recorded. Lowering the rate reduces routine trace volume, while a higher rate gives better statistical coverage at the cost of more ingestion and storage.
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Set a conservative baseline sample
Start with the smallest percentage that still answers your ordinary production questions. A baseline is useful for identifying recurring paths, service dependencies, and broad latency patterns; it is not a guarantee that every rare failure will appear.
- Open the domain’s Cloudflare Traces configuration.
- Set the default sample rate to a percentage appropriate for your request volume and diagnostic needs. Cloudflare’s documentation uses 10% as an example, which captures about 10 of 100 requests.
- Save the configuration and watch the resulting trace volume and ingestion usage.
- Increase the baseline only when the sampled population is too small for the question you are asking. Decrease it when routine traces are consuming capacity without improving diagnosis.
The configuration API represents the zone sampling ratio as a decimal from 0 to 1: 0 means no requests are selected by that baseline and 1 means every request is selected. Rules use the same 0-to-1 ratio. Keep the percentage shown to operators and the decimal used by automation clearly distinguished so that a value of 0.1 is not mistaken for 10 requests or for a 0.1% rate.
Use ordered trace rules for valuable traffic
A single global rate is rarely the best long-term design. Use rules to preserve more detail for a small, known population while leaving the broad baseline low.
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Because the first matching rule is applied, a broad rule placed first can prevent later, more specific rules from ever being used. Place a path, host, method, environment, or header condition that identifies a high-value request ahead of a catch-all rule. Review the resulting order before deployment; the configuration interface supports drafting a rule so its scope can be checked before it becomes active.
Examples of useful rule scopes
- Critical application paths: sample checkout, authentication, payment callbacks, or other flows where a missing trace would be costly.
- Debug environments: give a staging hostname or test header a high rate without raising production-wide volume.
- Rare tenants or request classes: target a customer, API version, method, or route that is difficult to reproduce.
- Fallback traffic: leave unmatched requests at the conservative default rather than creating a second broad high-rate rule.
Rules still make a head-based decision. A rule that matches a route samples that route regardless of whether an individual request eventually succeeds, fails, or exceeds a latency threshold.
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Capture one request at 100%
For a specific investigation, first use the request’s Ray ID to find it in the Cloudflare dashboard. If the request was not selected by the existing rate, filtering cannot recreate a trace that was never captured. To guarantee capture of a reproduction, Cloudflare documents a custom debug-header rule with a 100% sample rate.
- Choose a header name that your diagnostic client can add only when you are intentionally reproducing a problem.
- Create a trace rule that matches that header and set the rule’s sample rate to 100% (a ratio of
1in API configuration). - Place the debug rule ahead of any broader rule that could match the same request.
- Send the reproduction with the header, record its Ray ID, and inspect the resulting trace.
- Remove, disable, or narrow the rule after the investigation so an accidentally propagated header cannot create sustained high-volume capture.
This workflow is guaranteed capture for requests that satisfy the header condition; it is not error-only sampling. A qualifying request is captured whether its response is successful or unsuccessful.
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Cloudflare captures header names and header operations, but not header values. URLs and query strings are captured. Treat the debug header as a control signal, not as a place to put a secret, identifier, or diagnostic payload that you expect to appear in the trace.
Configure tracing for Cloudflare Workers
Workers tracing has its own enablement and head-sampling settings in Wrangler. The documented range for observability.traces.head_sampling_rate is 0 to 1. A value of 0 samples no invocations, and 1 samples all requests. If the setting is omitted, the Workers documentation says the default is 1, so explicitly set a lower value when you want to control volume.
[observability.traces]
enabled = true
head_sampling_rate = 0.1Use the equivalent syntax supported by the Wrangler configuration format and version in your project. The important controls are:
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enabled = trueturns Workers tracing on for the Worker.head_sampling_rate = 0.1requests roughly a 10% head-sampling rate.head_sampling_rate = 1captures every Worker invocation and should be reserved for narrowly scoped diagnostic periods or low-volume workloads.
If a trace appears to stop at a Worker, verify that tracing is enabled for that Worker before looking for an application bug. A Worker without Workers tracing enabled will not contribute the expected Worker segment.
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Choose persistence, export, or both
Sampling controls how many requests are selected. Storage controls determine where those selected traces go. “Persist to Cloudflare” saves traces so they can be viewed in Cloudflare’s dashboard. Export destinations send traces to configured, account-level OpenTelemetry destinations. These are separate choices and can be enabled together.
| Configuration | Where the selected traces are available | When it fits |
|---|---|---|
| Persist only | Cloudflare’s trace interface | You want investigation and retention inside Cloudflare and do not need an external trace backend. |
| Export only | Your configured OpenTelemetry destination | An external observability system is the system of record and Cloudflare persistence should be off. |
| Persist and export | Cloudflare plus the configured OpenTelemetry destinations | You need Cloudflare’s request context as well as centralized traces elsewhere. |
The API documentation allows up to 100 OpenTelemetry destination identifiers. Configure only destinations that you operate and monitor; each additional sink adds another place where sampled data may be retained and governed.
If your policy is that traces should live only in an external system, turn off Cloudflare persistence rather than assuming export automatically disables it. Conversely, disabling export does not prevent persisted traces from appearing in Cloudflare when persistence remains enabled.
Understand retention and future usage charges
Cloudflare documents seven-day retention for Workers traces. That retention period limits how long a persisted Worker trace remains available; it does not change the number of requests selected by the sampling rate.
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Cloudflare says persisted traces begin counting toward account-level Observability ingestion and storage usage on December 1, 2026. Its datasets documentation states that logs and traces begin using the same pricing model on that date. The date is a transition point, not a universal price: the amount you pay depends on your plan and actual ingestion and storage.
Free accounts have a daily ingestion limit. Cloudflare states that ingestion stops for the rest of the day after the limit is reached, but the documented material does not provide one account-independent numerical threshold. Do not build a budget or alert around an assumed number. Check the current pricing and the usage data for the account that will run the traces.
A practical cost-control loop
- Estimate incoming request volume for the domain or Worker.
- Choose a baseline rate and multiply it by that volume to estimate the number of selected requests.
- Add the traffic covered by high-rate rules, especially any 100% debug-header rule.
- Decide whether persistence, export, or both are necessary for each class of traffic.
- Review actual ingestion and storage after deployment, then lower broad sampling or remove temporary rules if the resulting data is not being used.
This calculation is an operational estimate, not a bill quote. Trace size varies by request path, and account pricing can change with plan and usage context.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why you cannot sample only slow requests or errors
Cloudflare Traces does not currently support tail-based sampling. Because selection happens before the request outcome is known, a rule cannot say “retain this request only if it later returns a 5xx” or “keep it only when latency exceeds one second.” A 100% rule captures all matching requests, including successful and fast ones, so it cannot be used as an outcome filter.
To investigate failures, combine the available controls: keep a useful baseline, increase sampling for the affected route or environment, and use a debug-header rule when you can reproduce a case. This improves the chance of capturing the complete path without claiming that every historical error is recoverable.
Diagnose missing or incomplete trace segments
The request has no trace
- Check whether its traffic matched a rule with a zero or very low rate.
- Confirm that the intended rule was above any earlier matching rule.
- For a reproduction, send the documented debug header and use a 100% rule.
- Verify that Workers tracing is enabled when the missing portion should come from a Worker.
The origin span is absent
If the response was served from cache, Cloudflare did not contact the origin. In that case, an outbound-origin span is not expected and its absence does not by itself indicate instrumentation failure.
The span layout changed
Cloudflare notes that span names and structure can change. Avoid building automation that depends on an exact, permanent shape of Cloudflare-emitted spans. Prefer stable request identifiers and documented attributes, and review consumers when Cloudflare changes the emitted structure.
Handle incoming trace context carefully
Incoming trace context defaults to Reject in the configuration documentation. If you change the setting to accept incoming context, Cloudflare warns that it does not verify that the context came from a trusted caller. Treat joined traces as untrusted input and limit acceptance to environments and callers where you understand the security and correlation implications.
Cloudflare Traces is not Cloudflare Trace
Cloudflare Traces records actual production requests. Cloudflare Trace, the separate Rules tool, simulates how a configuration would handle a request; it does not show production traffic. Use Traces when you need observed request execution and use the simulator when you need to test rule evaluation. Confusing the two can lead you to believe that a simulated result proves a production trace exists.
Sampling choices at a glance
| Choice | Baseline percentage | Scope | Storage destination | Primary purpose |
|---|---|---|---|---|
| Low default rate | Any ratio from 0 to 1; for example, 0.1 is about 10% | All unmatched requests for the domain or Worker | Cloudflare, OpenTelemetry, or both | Routine statistical visibility with controlled volume |
| Selective trace rule | A rule-specific ratio from 0 to 1 | Matching path, host, method, environment, or other filter | Same persistence/export choices | More detail for high-value traffic without raising the global rate |
| Debug-header rule | 1 (100%) | Only requests carrying the chosen header | Same persistence/export choices | Guaranteed capture of a reproducible diagnostic request |
| Outcome-based rule | Not available | Cannot be evaluated after latency or status is known | Not applicable | Slow-only or error-only retention is not supported today |
An operating pattern that stays affordable
- Enable tracing for the Workers that need request-level diagnostics.
- Set an explicit, conservative baseline rather than relying on an omitted Workers setting that defaults to 1.
- Write narrow high-rate rules for critical routes and place them before broad rules.
- Keep a disabled or temporary 100% debug-header rule ready for reproducible incidents.
- Choose persistence and export independently, based on where investigators actually work.
- Review seven-day Worker retention, ingestion, and storage usage against the account’s plan, especially ahead of December 1, 2026.
- Remove incident rules and lower unused high-rate coverage when the investigation ends.
This pattern preserves detailed traces where they are actionable while avoiding the assumption that Cloudflare can retroactively find every slow or failed request.
Bottom line
Control Cloudflare trace volume with a low head-sampling baseline, ordered exceptions, and a 100% custom-header rule for individual reproductions. Keep persistence and OpenTelemetry export as separate decisions, account for seven-day Workers retention and the December 1, 2026 Observability pricing transition, and do not design a policy around slow-only or error-only sampling because tail-based sampling is not currently supported.
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