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Set a conservative default sample rate for routine visibility, then use ordered trace rules to sample important paths or debug requests at higher rates. Cloudflare Traces makes this decision when a request arrives, so it cannot retain only requests that later become slow or fail. Choose separately whether selected traces are persisted in Cloudflare, exported to OpenTelemetry destinations, or both; this separation is the key to controlling storage and ingestion exposure.
What Cloudflare Traces samples
Cloudflare Traces uses request-level, head-based sampling. When a request arrives, Cloudflare decides whether to trace it using the applicable sample rate. If selected, the trace covers the supported request path rather than collecting only a fragment after an error occurs.
A 10% rate therefore means approximately 10 of every 100 requests are selected. It is a statistical rate, not a promise that every block of 100 requests will contain exactly 10 traces. A low rate reduces volume, but it also means a rare failure can pass through without being recorded.
The default sample rate is configured per domain. A custom trace rule can override that default for matching traffic. Rules are evaluated in order and the first matching rule wins, so rule order is part of the configuration, not an administrative detail.
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Choose a baseline that fits your traffic
Start with the smallest default percentage that still gives you useful routine visibility. The right number depends on request volume, how frequently you investigate production behavior, and how much trace data your account or external destination can absorb. Cloudflare does not prescribe one universal percentage.
- Estimate normal traffic. Use your domain’s request rate and the kinds of investigations your team performs. A percentage that is inexpensive for a low-volume API can be excessive for a high-volume public site.
- Pick a conservative default. Set the domain’s default sample rate to the percentage you can retain and review during normal operation. Cloudflare’s documented example of 10% would select about 10 requests in every 100.
- Identify high-value exceptions. List administrative paths, critical API operations, release canaries, or other traffic for which a higher rate is worth the additional volume.
- Create narrow overrides. Add rules for those exceptions rather than raising the global rate. Put the most specific conditions first.
- Review the scope before publishing. Drafting a rule lets you check its match conditions and ordering before it affects production traffic.
- Reassess after real usage. Watch the number of traces selected, the usefulness of the data, and ingestion or storage consumption. Adjust the baseline and exceptions independently.
The API represents sampling ratios from 0 to 1. A dashboard percentage such as 10% corresponds to an API ratio of 0.1. A ratio of 0 selects no requests, while 1 selects every matching request.
Keep the unit conversion visible in configuration reviews. Writing “10% (0.1)” in a runbook or pull request prevents an automation change from accidentally sending the value 10 to an API that expects 0.1. The same 0-to-1 convention applies to rule-level sampling ratios.
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Use ordered trace rules for selective detail
Trace rules let you preserve more detail where it has greater diagnostic value without tracing every request. A rule can narrow capture to a path or another request filter, or it can target a temporary debugging signal such as a custom header.
| Configuration choice | What it captures | Best use | Main trade-off |
|---|---|---|---|
| Low domain default | A small percentage of all arriving requests | Routine statistical visibility | Rare failures may not be selected |
| Higher rule for a path or filter | A larger percentage of matching traffic | Critical endpoints, canaries, or a service under investigation | More traces whenever that condition matches |
| Debug-header rule at 100% | Every request carrying the chosen header | Guaranteed capture of a deliberately marked request | Unsafe if the header is broad, leaked, or left enabled |
| External export with persistence disabled | Selected traces sent to configured OpenTelemetry destinations | Using an external trace system as the sole store | Cloudflare’s dashboard will not retain those traces for later viewing |
| Persistence and export together | Selected traces retained in Cloudflare and exported | Local investigation plus centralized observability | Two destinations consume operational capacity and may incur separate costs |
Why order matters
Because the first matching rule wins, place narrow rules above broad ones. For example, put a rule for one release-candidate path before a rule matching the entire API. If the broad rule comes first, the specific rule will never be reached for those requests.
When changing several rules, inspect their order as a set. A correct condition with an earlier, broader match can still produce an unexpected effective rate. A useful review records each rule’s position, condition, ratio, and intended traffic, then checks a few representative requests against that list.
Do not treat a rule as an additive percentage. A request does not receive the default sample chance and then an additional rule chance. The first matching rule determines the rate for that request; unmatched traffic falls through to the default.
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For a known request, begin with its Ray ID. Use the Ray ID as a filter in the Traces dashboard to locate any trace that was already selected. Filtering does not retroactively create a trace for a request that was skipped by sampling.
To guarantee selection for a diagnostic request, Cloudflare documents a custom debug-header rule with a 100% sample rate:
- Choose a header name reserved for controlled diagnostics, such as a team-specific debug header.
- Create a trace rule that matches the presence or expected value of that header.
- Set the rule’s sampling rate to 100% (an API ratio of 1).
- Place the rule ahead of broader rules so another match cannot determine the request’s rate first.
- Add the header only to the request you intend to investigate, then remove it when the capture is complete.
- Use the resulting Ray ID to find and examine the captured trace.
This is targeted head sampling, not error sampling. A request carrying the header is captured whether it succeeds, fails, or responds slowly. Treat the header as an operational control: document who may set it, avoid exposing it to untrusted clients, and prevent it from being added to automated traffic unintentionally.
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Header values are not included in captured attributes, although header names and operations on them are captured. That means the header can act as a selector without placing its value in the trace. Do not put a secret, token, customer identifier, or other sensitive value in the header expecting it to be available for later correlation. Use a fixed, non-sensitive marker and correlate the request with its Ray ID or your own controlled log.
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Why Cloudflare cannot sample only slow requests or errors
Cloudflare makes the sampling decision before the request outcome is known. Consequently, a rule cannot currently say “retain this request only if it exceeds a latency threshold” or “retain it only when it returns an error.” Cloudflare’s documentation states: “Tail-based sampling is not currently supported.”
If you need complete coverage of a suspected failure, temporarily raise the rate for the affected path or use the 100% debug-header workflow for a controlled reproduction. A 100% rule increases capture for every matching request; it does not inspect the eventual status or duration.
This limitation changes how to plan an incident. If a problem is intermittent, leave a sufficiently useful baseline in place or temporarily increase the affected scope before reproducing it. Waiting until an error appears and then searching for a trace cannot recover a request that was never selected. Conversely, a high rate on a broad path can create much more volume than the actual number of failures, so narrow the condition and lower it promptly after the investigation.
Does tracing add latency to requests?
Cloudflare surfaces latency as a reader concern, but the configuration controls do not provide a universal overhead number. Sampling determines which requests are captured; it does not turn a request into a tail-sampled transaction after completion. Validate performance in your own workload, especially when changing a Worker setting from a low ratio to 1 or enabling a broad 100% rule. Compare request latency and trace volume before and after the change, and avoid treating a temporary diagnostic configuration as a permanent production baseline.
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Persistence and export are separate settings.
Persist to Cloudflare
Persistence saves selected traces so you can view them in Cloudflare’s dashboard. Turn it on when the Cloudflare interface is part of your investigation workflow or when you need a short-lived local record. Persistence is a storage decision in addition to a sampling decision: only selected requests are eligible to be persisted, but every persisted trace contributes to the data retained in Cloudflare.
Export to OpenTelemetry destinations
Export sends traces to configured, account-level OpenTelemetry destinations. Cloudflare’s Workers tracing material names Honeycomb, Grafana Cloud, and Axiom as examples of compatible destinations; compatibility does not establish a particular provider’s plan, price, or availability for your account.
The API reference documents up to 100 OpenTelemetry destination identifiers. That is a configuration ceiling, not a recommendation to create a destination for every team or environment. Consolidate obsolete identifiers and verify delivery ownership so a rule does not send production traces to an unattended endpoint.
Use both or only the external destination
Cloudflare supports using persistence and export together. If the external system should be the sole trace store, turn off Cloudflare persistence. This avoids retaining a second copy in Cloudflare while still sending selected traces to the configured destination. Verify the external pipeline before disabling local persistence so an export outage does not silently remove your only copy.
Using both can be useful during a migration or incident: Cloudflare provides a nearby troubleshooting view while the external system supports cross-service correlation. It also means you should account for both destinations when reviewing data handling, retention, access, and possible charges.
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Workers-specific sampling and retention
For a Worker, set the head-sampling rate in Wrangler with observability.traces.head_sampling_rate. The valid range is 0 to 1: 0 samples no invocations, 1 samples every request, and an intermediate value samples that fraction. If the setting is omitted, the documented default is 1, so explicitly configure a lower value when you want to reduce a Worker’s volume.
observability.traces.head_sampling_rate = 0.1To see Worker spans, tracing must also be enabled for that Worker:
observability.traces.enabled = trueCloudflare documents seven-day retention for Workers traces. That is a retention window, not a guarantee that every invocation is stored: sampling happens first, and only selected traces enter retention. A seven-day window also means an investigation that starts later may no longer find an older selected trace, so export to an external destination when longer retention is required.
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Review both settings during deployment. Enabling tracing while leaving the sampling rate at its documented default of 1 can select every invocation. Conversely, setting the rate to 0 while expecting Worker spans produces no sampled invocations. Treat the rate and enabled flag as a pair in environment-specific configuration.
Understand the cost transition and account limits
Cloudflare says persisted traces will begin counting toward account-level Observability ingestion and storage usage on December 1, 2026. Its datasets documentation places logs and traces on the same pricing model from that date. The date is a stated transition point; it is not an account-independent price.
Free accounts have a daily ingestion limit. Cloudflare’s configuration documentation does not state a numerical threshold in the cited material, so do not use an assumed number in a budget or runbook. After a Free account reaches its daily limit, Cloudflare says it stops ingesting new traces for the rest of that day.
Actual cost and available capacity depend on your plan, traffic, selected rate, retention, and whether you also export data. For a bill estimate, use the account’s current Observability usage and pricing information rather than multiplying a generic per-request figure.
A simple planning worksheet can still help without pretending to predict a bill. Record requests per day, the baseline ratio, the approximate traffic matched by each override, the ratios for those overrides, whether persistence is enabled, and the number of exported destinations. Recheck those values against actual ingestion and storage dashboards. A narrow 100% rule used for ten requests is operationally different from a 100% rule matching an entire public endpoint, even though both display the same percentage.
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The API expresses both the zone sampling ratio and rule sampling ratios from 0 through 1. Keep the ratio notation consistent between automation and dashboard percentages to avoid a tenfold configuration error, such as entering 10 when the API expects 0.1.
The API reference documents up to 100 OpenTelemetry destination identifiers. If you approach that limit, consolidate destinations or remove obsolete identifiers before adding more. Destination count does not change the head-sampling decision; it changes where selected traces can be delivered.
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When automating changes, preserve rule order explicitly rather than sorting rules alphabetically or by identifier. Include a rollback value for the baseline and for temporary high-rate rules. A runbook should say who may activate a debug-header rule, how its scope is verified, and when it is removed.
Investigate missing or incomplete traces
No trace appears for a request
- Check whether the request was selected by the effective default or first matching rule. A low rate can legitimately omit it.
- Confirm that the Ray ID filter is correct.
- For a new reproduction, use the controlled debug-header rule at 100% rather than repeatedly retrying at a low default rate.
- Check whether the account has reached its daily ingestion limit, particularly on a Free account.
- Confirm that persistence is enabled if you are looking in Cloudflare’s dashboard; an export-only configuration sends selected traces elsewhere.
A Worker segment is missing
Confirm that Workers tracing is enabled with observability.traces.enabled = true. A Worker that is not enabled for tracing will not contribute its expected spans.
There is no outbound-origin span
If Cloudflare served the response from cache, it did not contact the origin. In that case, an outbound-origin span is not expected and does not by itself indicate a tracing failure.
Attributes do not contain the expected header value
Cloudflare captures header names and operations on them, but not header values. URLs and query strings are captured. Design a debug-header workflow around the presence or operation of the header, and do not expect the secret or identifying value itself to appear in trace attributes.
An integration breaks after a platform change
Cloudflare warns that span names and structure can change. Avoid hard-coding automation or dashboards to an exact Cloudflare-emitted span shape unless you are prepared to update it when the schema evolves.
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Incoming trace context defaults to Reject in the configuration documentation. If you change the setting to accept incoming context, Cloudflare cautions that it does not verify that the context came from a trusted caller. Treat joined traces as untrusted input and do not use an incoming trace identifier as proof of caller identity or authorization.
Accepting context can help connect a request to upstream telemetry, but it does not change the sampling limitation: Cloudflare still makes its own capture decision when the request arrives. Keep authorization, tenant identity, and security decisions on authenticated request data rather than on a caller-supplied trace context.
Do not confuse Traces with the Trace simulator
Cloudflare Traces records actual production requests. The separate Cloudflare Trace tool simulates how a request would be handled by configuration rules; it does not display production traffic or provide a sampled production trace. Use the production Traces interface when diagnosing live request behavior, and use the simulator when validating rule logic before deployment.
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- Normal operation: keep a modest domain or Worker default and export or persist only what your operational process can review.
- Release monitoring: add a narrowly scoped, higher-rate rule for a canary path or release marker, placing it before broader matches.
- Incident reproduction: mark one controlled request with the debug header and capture it at 100%, then remove the marker.
- Broad investigation: temporarily raise the rate for the affected path when a single request is insufficient, and lower it when the investigation ends.
- Cost review: compare selected volume, retention, export delivery, and account usage after the change rather than relying on the configured percentage alone.
- Post-incident cleanup: remove temporary rules, clear diagnostic headers from scripts and clients, and record the final effective order so the next incident starts from a known state.
Configuration checklist
- Set the default rate using a 0-to-1 API ratio or its equivalent dashboard percentage.
- Document which rules override the default and verify that the first match is intentional.
- Put specific rules ahead of broad rules.
- Use a protected, temporary debug header for guaranteed single-request capture.
- Do not promise slow-only or error-only retention; Cloudflare uses head sampling.
- Choose persistence, export, or both deliberately.
- For Workers, enable tracing and set
observability.traces.head_sampling_rateexplicitly when the default of 1 is too high. - Account for seven-day Workers retention and the December 1, 2026 Observability usage transition.
- Check your account’s actual ingestion limit and usage before forecasting cost.
- Expect cache-served responses to lack origin spans and expect header values to be absent.
- Treat accepted incoming trace context as untrusted and avoid dependencies on fixed span names.
- Verify an OpenTelemetry export before disabling Cloudflare persistence.
- Remove temporary 100% rules and debug headers after the diagnostic window closes.
Frequently Asked Questions
How do I reduce Cloudflare trace volume without losing important requests?
Lower the domain or Worker default to a conservative 0-to-1 ratio, then add ordered rules with higher ratios for critical paths, canaries, or controlled debug requests. Put narrow rules first because the first matching rule wins.
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No. Cloudflare makes its sampling decision before the request outcome is known, and tail-based sampling is not currently supported. Use a higher-rate path rule or a 100% debug-header rule when reproducing a problem.
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How do I capture the trace for a specific request?
Use the request’s Ray ID to search for a trace that was already selected. For a guaranteed new capture, send a controlled custom debug header that matches a rule with a 100% sample rate, positioned before broader rules.
Does a 100% debug-header rule capture only failed requests?
No. It captures every qualifying request, whether it succeeds, fails, or is slow. The rule is head-based and cannot evaluate the eventual status or duration.
What happens if I disable persistence?
Selected traces can still be exported to configured account-level OpenTelemetry destinations, but Cloudflare’s dashboard will not retain them. Confirm the external pipeline works before making it the sole store.
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Cloudflare documents seven-day retention for Workers traces. Sampling still happens first, so the window applies only to traces that were selected and stored.
What is the Free account ingestion limit?
Cloudflare states that Free accounts have a daily ingestion limit and stop ingesting new traces for the rest of the day after reaching it. The numerical threshold is account and documentation dependent; check current account information rather than relying on an assumed number.
When do persisted traces begin counting toward Observability usage?
Cloudflare states that persisted traces begin contributing to Observability ingestion and storage usage on December 1, 2026. Your actual cost depends on plan, traffic, retention, and configuration.
Why is an origin span missing?
If Cloudflare served the response from cache, it did not contact the origin, so an outbound-origin span is not expected.
Why is my Worker missing from the trace?
Ensure that Workers tracing is enabled with observability.traces.enabled = true. A Worker without tracing enabled will not contribute its expected spans.
Are header values visible in traces?
No. Cloudflare captures header names and operations, but not header values. Use a non-sensitive marker for debug-header selection and correlate with the Ray ID or controlled logs.
Can I rely on Cloudflare span names staying the same?
Cloudflare says span names and structure can change. Avoid hard dependencies on an exact emitted shape, or maintain the integration so it can be updated when the schema evolves.
What is the difference between Cloudflare Traces and Cloudflare Trace?
Cloudflare Traces records sampled production requests. Cloudflare Trace is a separate simulator for testing how configuration rules would handle a request; it does not show actual production traffic.
The Bottom Line
Use head sampling strategically: keep the baseline low, place narrow high-rate rules before broad ones, and reserve 100% capture for a protected debug header or a tightly scoped investigation. Persistence and OpenTelemetry export are independent choices. Check the account’s actual limits and usage, remember seven-day Workers retention, and plan for persisted traces to enter Observability ingestion and storage usage on December 1, 2026.
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