Use Cloudflare Traces to explain one real request. It shows the supported Cloudflare and Workers operations that request passed through, including where time was spent and where an operation failed. Use Workers Analytics Engine to measure events your application defines. A Worker writes selected events and dimensions, then you query them with SQL for customer usage, feature adoption, health scores, or billing.
They are not competing versions of the same product. Traces provide request-level execution evidence; Analytics Engine provides application-defined analytical data. Many teams use both: Traces for incident diagnosis and Analytics Engine for durable product and operational analytics.
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Cloudflare Traces and Analytics Engine at a glance
| Question | Best fit | Why |
|---|---|---|
| Why did this production request fail or slow down? | Cloudflare Traces | Follows the request through supported operations and exposes a span hierarchy with durations, statuses and attributes. |
| How long did this Worker spend on fetches, KV, R2 or RPC calls? | Cloudflare Traces with Workers tracing enabled | Workers tracing adds runtime spans for supported handler calls, outbound fetches, bindings and RPC operations. |
| How many signups, purchases or feature activations occurred per customer? | Workers Analytics Engine | Your Worker chooses the events and dimensions to write, and SQL queries the resulting dataset. |
| What is aggregate request or invocation health? | Built-in Workers metrics and analytics | Cloudflare separates its standard platform metrics from custom Analytics Engine data. |
| How can telemetry be sent to another observability system? | Workers OpenTelemetry export | Workers can export configured traces and logs, subject to destination configuration and trace-context limitations. |
A trace is tied to an actual request and its execution path. An Analytics Engine row exists only because application code deliberately wrote it. Choosing between them starts with whether you are investigating execution or analyzing events.
What Cloudflare Traces shows
The path of a real production request
The production Traces view presents supported operations as a hierarchy. Depending on the request, that hierarchy can include Cloudflare rules, routing, cache activity, a Worker invocation and an origin connection. Selecting a span exposes details such as status, service, trigger, identifiers, duration and other attributes.
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When investigating a particular request, filter by its Ray ID. This lets you move from a user-visible failure or latency report to the exact request record rather than an average across traffic.
Worker runtime detail requires a separate setting
Cloudflare’s edge-level trace does not automatically expose every operation inside your Worker. Enable Workers tracing for that Worker to add runtime spans. Cloudflare documents automatic instrumentation for supported handler calls, outbound fetch calls, binding operations such as KV and R2 interactions, and RPC operations. You can add custom spans around application logic that is not covered by automatic instrumentation.
The result is a nested view: the outer request path can show that a Worker ran, while Worker tracing can show which subrequest or binding operation consumed time within that invocation.
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Do not confuse production Traces with the simulator
Cloudflare also provides a separate “Cloudflare Trace” simulation. That simulator is useful for evaluating how configuration would process a request, but it does not show actual production traffic. Use the production trace view when you need evidence about what happened to a live request.
What Workers Analytics Engine stores
Application-selected events and dimensions
Analytics Engine is a custom analytics store. Your Worker decides what a data point means and which dimensions to attach. Typical dimensions include a customer identifier, plan, feature name, region, event type or deployment version. Values can represent signups, purchases, usage units, application health events or any other event your code can define.
This flexibility is also the boundary of the product: Analytics Engine cannot answer a question about an event you never wrote. It does not automatically reconstruct every request’s execution tree.
Non-blocking writes, then SQL queries
A Worker writes data points through the built-in Analytics Engine API. The SQL API then queries those points for reports, dashboards or scheduled analysis. Cloudflare states: “Writes to Analytics Engine are non-blocking and do not add latency to your Worker.” That is a vendor-documented behavior, not an independent performance benchmark; validate the effect in your own workload and account configuration.
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Questions Analytics Engine is designed for
- Usage-based billing calculated from events attributed to an account or customer.
- Customer-facing analytics, such as activity over time or usage by feature.
- Feature adoption, conversion funnels and release-version comparisons.
- Per-customer health or service-level indicators assembled from application events.
- Aggregate operational measures whose definition belongs to your application rather than to Cloudflare’s request pipeline.
Choose by the question you need to answer
Choose Cloudflare Traces when the unit of investigation is a request
- A user reports a timeout and you need to locate the slow operation.
- A request failed and you need to distinguish routing, cache, Worker or origin behavior.
- You need to inspect a Worker fetch, KV read, R2 operation or RPC call in context.
- You have a Ray ID and want a request-specific execution record.
Choose Analytics Engine when the unit of analysis is an event or population
- You need counts or rates by customer, plan, feature, geography or release.
- You want to calculate billable usage from application-defined actions.
- You need a historical product metric that is not represented by a standard platform metric.
- You want SQL exploration over dimensions chosen by your team.
Use built-in metrics before creating custom data
For ordinary aggregate request and invocation health, start with Workers’ built-in metrics and analytics. They already represent platform-level traffic and runtime measures. Add Analytics Engine when the metric requires business context or custom dimensions that those built-in views do not provide.
Enable and investigate Workers traces
1. Turn tracing on in Wrangler
In the Worker configuration, set the observability tracing flag to true:
[observability.traces]
enabled = trueUse the equivalent configuration format supported by your current Wrangler version. Configuration labels can evolve, so confirm the generated deployment configuration before enabling it broadly.
2. Set a head-sampling rate
Workers tracing uses head-based sampling: the decision is made when the request arrives, before Cloudflare knows whether the request will be slow or fail. The documented default is 1 when tracing is enabled, which records every request. A value such as 0.05 selects approximately five percent of arriving requests.
Sampling is a traffic-volume decision, not a slow-request filter. Tail-based sampling, which waits for the outcome and then keeps only errors or slow requests, is not currently supported. A sampled-out request cannot be recovered later, even if it eventually fails.
3. Add trace rules for important traffic
Trace rules can override the default rate for matching requests. Use rules to prioritize a narrow diagnostic route, tenant, header, deployment, or other supported match condition while keeping a lower baseline rate for ordinary traffic. Document the rule order and expected volume so an emergency rule does not unexpectedly exhaust an account limit.
4. Reproduce or locate the request
- Obtain the request’s Ray ID from the response, log record or incident report.
- Open the production Cloudflare Traces view and filter by that Ray ID.
- Expand the operation hierarchy from the edge entry point through routing, cache, Worker and origin operations.
- Select suspicious spans and compare their status, duration, service, trigger and attributes.
- If Worker internals are absent, verify that Workers tracing was enabled for the deployed version and that the request was sampled.
- Use custom spans for application sections whose work is not represented by automatic instrumentation.
Design an Analytics Engine dataset
1. Define the event contract first
Write down the event name, timestamp, numeric measurements and dimensions before adding instrumentation. For example, a usage event might include an account ID, plan, feature, region, deployment version and units consumed. Keep identifiers consistent and decide whether a value is a count, duration, amount or categorical label.
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Do not treat a trace span name as an Analytics Engine schema. Traces describe operations Cloudflare observed; Analytics Engine describes events your application intentionally emits.
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2. Write points from the Worker
Use the built-in Analytics Engine binding or API in the Worker to write each event. Writes are asynchronous from the request’s perspective according to Cloudflare’s documentation, but your code still needs sensible handling for missing identifiers, malformed values and duplicate business events.
3. Query with SQL
Use the SQL API to aggregate points by the dimensions you selected. Build queries for totals, time buckets, customer cohorts, feature rates or billing calculations. Test queries against known events and specify the time zone and interval semantics used by downstream reports.
4. Treat the schema as an interface
Changing an event name, dimension meaning or unit can silently change historical comparisons. Version event definitions when a field changes meaning, and retain enough deployment context to explain a metric after a Worker release.
Sampling, retention and account implications
Head sampling affects what you can prove
With head sampling, every request has its keep-or-discard decision at arrival. A five-percent rate can provide representative volume for broad patterns, but it cannot guarantee that a particular incident appears in the dataset. During an incident, temporarily increasing the rate or adding a targeted trace rule can improve capture, subject to account limits and cost.
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Cloudflare documents seven-day retention for Workers traces. Treat the trace view as a short-lived debugging record: export or record the relevant evidence in your incident system before the window expires if the issue needs a longer audit trail.
Pricing changes on December 1, 2026
Cloudflare states that, beginning December 1, 2026, stored traces contribute to account-level ingestion and storage usage under Cloudflare Observability pricing. The exact amount and applicable account details can vary, so check the current pricing documentation for your account before enabling full-rate tracing.
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Cloudflare also documents a daily ingestion limit for Free accounts. When that limit is reached, new traces stop ingesting for the rest of that day. The limit amount is not specified in the available product material here; verify the current account documentation rather than assuming a universal number.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Exporting traces and logs with OpenTelemetry
Workers can export OpenTelemetry-compliant traces and logs to configured external destinations. This is useful when your organization already centralizes telemetry outside Cloudflare or needs retention and correlation workflows beyond the seven-day trace view. Cloudflare lists compatible destinations including Honeycomb, Grafana Cloud and Axiom.
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There is an important correlation limitation: Cloudflare says Workers trace IDs are not propagated to services outside Cloudflare when exporting to external platforms. A downstream service may therefore show a separate trace rather than one continuous cross-vendor trace. Preserve Ray IDs and your own request or correlation identifiers in logs when you need to join records manually.
Known gaps and how to interpret them
A missing span does not prove that no work occurred
Traces contain spans only for supported operations that actually ran. Some Cloudflare features do not yet have dedicated span-level detail. Worker spans also require tracing to be enabled and the request to be sampled.
A duration of 0 ms is a measurement limitation
Cloudflare documents that some non-I/O operations can report a duration of 0 ms because of runtime timing protections. Read that value as “below the available measurement resolution or protected by the runtime,” not as proof that the operation consumed no time.
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Span names and structure are not a stable API
Cloudflare says span names and their structure may change as the product evolves. Use them for investigation and dashboards that tolerate change; avoid building brittle automation that depends on an exact span tree or name unless you are prepared to update it.
A practical combined workflow
- Use built-in Workers metrics to detect an aggregate change in errors, latency or invocation volume.
- Take a representative Ray ID from an affected request and open its Cloudflare production trace.
- Check the request hierarchy for routing, cache, Worker and origin delays or failures.
- Inspect Worker suboperations after confirming tracing and sampling settings.
- Add or adjust a targeted trace rule if the incident is not being captured reliably.
- Use Analytics Engine to measure how many customers, features or billable events were affected, provided those events are written by the application.
- Export OpenTelemetry data when longer retention or external correlation is required, while retaining a separate correlation ID because external trace IDs may not link automatically.
Troubleshooting common questions
“Why is there a gap in my trace?”
Check whether the missing operation is supported, whether Workers tracing was enabled for that deployment, and whether head sampling discarded the request. A gap can also represent work performed outside the instrumented path rather than a failure in the trace viewer.
“Can I sample only slow requests or errors?”
Not with the documented Workers Traces sampling model. Sampling is head-based, so the outcome is unknown when the decision is made. Use a higher baseline rate or trace rules that target traffic likely to matter, then control volume and account limits.
“Why does Analytics Engine show no event?”
Verify that the code path executed, the Analytics Engine binding is connected to the deployed Worker, required dimensions were populated, and the SQL query’s time range includes the write. Analytics Engine cannot display an event that application code did not send.
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No. Define durable events and dimensions that support a known analytical question. Request-level execution details belong in traces or logs; high-cardinality, unbounded log output can make an analytical dataset difficult to govern and query.
Bottom-line decision
Choose Cloudflare Traces for “What happened to this request, and where did it spend time?” Enable Workers tracing when you need handler, fetch, binding or RPC detail, and account for head sampling, seven-day retention and ingestion limits.
Choose Workers Analytics Engine for “Which events occurred, for whom, and how do they aggregate over time?” Define the event schema in your application, write the points deliberately and query them with SQL.
If your observability program needs both answers, do not force one product into the other’s role. Use traces to diagnose execution, Analytics Engine to analyze application-defined behavior, built-in metrics for broad platform health, and OpenTelemetry export when external retention or analysis is required.
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