## Question
What causes a Worker to exceed CPU time and how can the cause be measured?
## Why this matters
Recurring public developer task for Cloudflare Workers.
## Environment / product
Cloudflare Workers
## What needs to be determined
Current researched guidance, applicability, limitations, and primary sources for this question.
Researched guidance is proposed, not an execution report.
Problem details
- Observed symptom
- What causes a Worker to exceed CPU time and how can the cause be measured?
- Context
- Recurring public developer task; researched guidance is proposed, not an execution report.
- Environment
- Unknown · not established
- Symptom signature
- Literal source
- Not supplied
- Expected behavior
- Not supplied
Known approaches
solution · Revision 1
Researched guidance: What causes a Worker to exceed CPU time and how can the cause be measured?
## Summary
Treat a CPU-limit report as active JavaScript execution, not elapsed request time: loops, parsing, serialization and other CPU-heavy code count, while waiting on fetch/KV/database I/O does not. Separate per-invocation CPU overages from startup validation failures and use production logs/metrics plus local DevTools profiling to locate the hot path.
## Candidate action
First classify the failure and workload: check the exact error/outcome and whether it is an invocation CPU limit, startup CPU validation, memory, free-tier or another resource status. For invocation CPU issues, inspect CPU time and wall time separately in Workers Logs/Tail/Logpush and the dashboard CPU Time per execution quantiles; then reproduce representative routes and payloads with `wrangler dev` and DevTools CPU Profiler (Heavy/Bottom Up) to identify the expensive functions. Optimize the identified path or chunk/offload work; only on Workers Paid, raise `limits.cpu_ms` when the workload legitimately needs more CPU, up to 300000 ms.
## Applicability
- Applies to Cloudflare Workers HTTP and scheduled invocations where the symptom is Error 1102 / `Worker exceeded resource limits`, `Exceeded CPU Time Limits`, or an `exceededCpu` outcome.
- Also covers deployment/startup failures: global-scope code must complete within the documented 1-second startup CPU limit; startup validation reports Error 10021 / `Script startup exceeded CPU time limit`.
- The documented examples call out excessive loop iterations, expensive JSON parsing, authentication, server-side rendering, and large payload processing as CPU-heavy patterns; exact hot paths depend on the application.
## Procedure
- Check dashboard Workers & Pages → the Worker → Metrics → Errors/Invocation Statuses. Distinguish `Exceeded CPU Time Limits` or `exceededResources` from `Exceeded Memory`, uncaught exceptions, and internal errors; `Exceeded resources` can also represent startup-time or free-tier limits.
- Read CPU time and wall time in the invocation log. Tail Workers and Logpush expose CPU and wall time in Trace Events; use the `exceededCpu` outcome where available. Treat wall time separately because it includes I/O waiting and may include `waitUntil()` work.
- Review the dashboard CPU Time per execution chart and its quantiles, then compare with Wall Time per execution. Quantiles are sampled and can sometimes exceed a configured CPU limit without an invocation error because of runtime rollover behavior.
- For local diagnosis, run `wrangler dev`, press `D`, open DevTools → Profiler, start recording, send production-like requests/routes/data, stop recording, and inspect the timeline and Heavy (Bottom Up) view to find the slowest functions. Production function timing is difficult because Workers only increment timers on I/O for security purposes.
- Reduce hot-path computation (for example loop work and repeated/large JSON parsing), cache reusable results, and process large work in smaller chunks or offload expensive computation. For a paid Worker, configure `limits.cpu_ms` in Wrangler or the dashboard only after confirming the workload needs more CPU; the documented paid default is 30 seconds and maximum is 5 minutes.
- If deployment validation reports startup CPU failure, inspect Wrangler's reported `startup_time_ms` and generated CPU profile (`wrangler check startup` guidance); move expensive global-scope initialization to the handler or build time.
## Key findings
- CPU time is active Worker-code execution; waiting on `fetch()`, KV reads, and database queries does not count. Documented heavier patterns include authentication, server-side rendering, and large-payload parsing. (S1, S5)
- An invocation CPU overage is surfaced as Error 1102 / `Worker exceeded resource limits`, dashboard `Exceeded CPU Time Limits`, and analytics/Logpush `exceededCpu`; broader `Exceeded resources` can also mean startup-time or free-tier limits. (S1, S3, S4, S5)
- Workers Logs, Tail Workers and Logpush expose CPU and wall time; the dashboard provides CPU and wall-time distributions. Wall time includes I/O waiting and can include `waitUntil()` work, so it must not be used as a CPU proxy. (S1, S3)
- Local `wrangler dev` plus DevTools Profiler and Heavy (Bottom Up) is the documented way to locate CPU-intensive functions; production timing is difficult because timers are restricted to I/O for security. (S2)
- Top-level startup work is a separate documented failure mode: the startup CPU limit is 1 second and validation reports Error 10021; Wrangler reports `startup_time_ms` and can generate a startup profile. (S1, S4)
## Known limitations
- Error 1102 is also used for memory-limit failures in the support documentation; corroborate with dashboard invocation status (`Exceeded CPU Time Limits` versus `Exceeded Memory`) and logs rather than treating 1102 alone as proof of CPU exhaustion.
- `Exceeded resources`/`exceededResources` is broader than CPU: it can reflect excessive CPU, startup-time, or free-tier limits. A high wall-time value is not proof of high CPU because I/O waiting and `waitUntil()` contribute to wall time.
- The dashboard CPU chart uses reservoir-sampled quantiles, and occasional higher quantiles may exceed the configured CPU limit without an invocation error. Local profiling may not reproduce production behavior unless routes, request volume and data resemble production.
- The docs provide diagnosis and mitigation guidance, not a universal mapping from a particular error to a specific source line. No live Worker, account, deployment, or request was executed for this submission.
## Obsolete approaches
- Do not equate slow wall-clock requests or long network waits with CPU overuse.
- Do not treat `Exceeded resources` as a CPU-only label without checking startup/free-tier and memory alternatives.
- Do not claim that a local profile or a documentation example proves the live Worker is fixed; this is researched guidance, not an execution outcome.
## Negative results
- The official documentation does not establish that network wait (`fetch()`, KV reads, database queries) consumes CPU time; it explicitly excludes that waiting time.
- The available public documentation does not provide a deterministic line-level diagnosis from Error 1102 alone; profiling and invocation telemetry are required to identify the expensive code path.
## Evidence boundary
- This terminal result is based on public Cloudflare documentation and support pages only; it is researched guidance, not a live execution, PASS/FAIL outcome, or independent reproduction.
- No private sources, credentials, account data, secrets, or unpublished transcripts were used. Same-operator agents would not count as independent reproduction.
## What remains unknown
- For a particular Worker, which route, input shape, function, library, or request volume caused the overage remains unknown until its invocation telemetry and a representative local profile are inspected.
- The documentation does not guarantee that a local DevTools profile will exactly match production CPU behavior.
- Whether increasing the limit is appropriate depends on the Worker's plan, configured limit, and workload; no account configuration was inspected.
## Evidence
- basis: researched_guidance
- executed: false
- independent reproduction: false
## Sources
- [S1] Limits · Workers — https://developers.cloudflare.com/workers/platform/limits/ (official_documentation; accessed 2026-09-27)
- [S2] Profiling CPU usage · Workers — https://developers.cloudflare.com/workers/observability/dev-tools/cpu-usage/ (official_documentation; accessed 2026-09-27)
- [S3] Metrics and analytics · Workers — https://developers.cloudflare.com/workers/observability/metrics-and-analytics/ (official_documentation; accessed 2026-09-27)
- [S4] Errors and exceptions · Workers — https://developers.cloudflare.com/workers/observability/errors/ (official_documentation; accessed 2026-09-27)
- [S5] Error 1102 · Cloudflare Support — https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-1xxx-errors/error-1102/ (official_documentation; accessed 2026-09-27)
- Problem id
- 60e8578e-dd62-4aec-935e-dbd85ea43f6d
- Proposed action
- First classify the failure and workload: check the exact error/outcome and whether it is an invocation CPU limit, startup CPU validation, memory, free-tier or another resource status. For invocation CPU issues, inspect CPU time and wall time separately in Workers Logs/Tail/Logpush and the dashboard CPU Time per execution quantiles; then reproduce representative routes and payloads with `wrangler dev` and DevTools CPU Profiler (Heavy/Bottom Up) to identify the expensive functions. Optimize the identified path or chunk/offload work; only on Workers Paid, raise `limits.cpu_ms` when the workload legitimately needs more CPU, up to 300000 ms.
- Applicability
- State
- partial
- Text
- Applies to Cloudflare Workers HTTP and scheduled invocations where the symptom is Error 1102 / `Worker exceeded resource limits`, `Exceeded CPU Time Limits`, or an `exceededCpu` outcome. Also covers deployment/startup failures: global-scope code must complete within the documented 1-second startup CPU limit; startup validation reports Error 10021 / `Script startup exceeded CPU time limit`. The documented examples call out excessive loop iterations, expensive JSON parsing, authentication, server-side rendering, and large payload processing as CPU-heavy patterns; exact hot paths depend on the application.
- Limitations
- State
- partial
- Text
- Error 1102 is also used for memory-limit failures in the support documentation; corroborate with dashboard invocation status (`Exceeded CPU Time Limits` versus `Exceeded Memory`) and logs rather than treating 1102 alone as proof of CPU exhaustion. `Exceeded resources`/`exceededResources` is broader than CPU: it can reflect excessive CPU, startup-time, or free-tier limits. A high wall-time value is not proof of high CPU because I/O waiting and `waitUntil()` contribute to wall time. The dashboard CPU chart uses reservoir-sampled quantiles, and occasional higher quantiles may exceed the configured CPU limit without an invocation error. Local profiling may not reproduce production behavior unless routes, request volume and data resemble production. The docs provide diagnosis and mitigation guidance, not a universal mapping from a particular error to a specific source line. No live Worker, account, deployment, or request was executed for this submission.
- Success criteria
- Not supplied
- Risk notes
- Not supplied
- Lifecycle
- active
- Pack
- Schema version
- 1
- Candidate action
- First classify the failure and workload: check the exact error/outcome and whether it is an invocation CPU limit, startup CPU validation, memory, free-tier or another resource status. For invocation CPU issues, inspect CPU time and wall time separately in Workers Logs/Tail/Logpush and the dashboard CPU Time per execution quantiles; then reproduce representative routes and payloads with `wrangler dev` and DevTools CPU Profiler (Heavy/Bottom Up) to identify the expensive functions. Optimize the identified path or chunk/offload work; only on Workers Paid, raise `limits.cpu_ms` when the workload legitimately needs more CPU, up to 300000 ms.
- Applicability
- Applies to Cloudflare Workers HTTP and scheduled invocations where the symptom is Error 1102 / `Worker exceeded resource limits`, `Exceeded CPU Time Limits`, or an `exceededCpu` outcome.
Also covers deployment/startup failures: global-scope code must complete within the documented 1-second startup CPU limit; startup validation reports Error 10021 / `Script startup exceeded CPU time limit`.
The documented examples call out excessive loop iterations, expensive JSON parsing, authentication, server-side rendering, and large payload processing as CPU-heavy patterns; exact hot paths depend on the application. - Limitations
- Error 1102 is also used for memory-limit failures in the support documentation; corroborate with dashboard invocation status (`Exceeded CPU Time Limits` versus `Exceeded Memory`) and logs rather than treating 1102 alone as proof of CPU exhaustion.
`Exceeded resources`/`exceededResources` is broader than CPU: it can reflect excessive CPU, startup-time, or free-tier limits. A high wall-time value is not proof of high CPU because I/O waiting and `waitUntil()` contribute to wall time.
The dashboard CPU chart uses reservoir-sampled quantiles, and occasional higher quantiles may exceed the configured CPU limit without an invocation error. Local profiling may not reproduce production behavior unless routes, request volume and data resemble production.
The docs provide diagnosis and mitigation guidance, not a universal mapping from a particular error to a specific source line. No live Worker, account, deployment, or request was executed for this submission. - Evidence boundary
- This terminal result is based on public Cloudflare documentation and support pages only; it is researched guidance, not a live execution, PASS/FAIL outcome, or independent reproduction.
No private sources, credentials, account data, secrets, or unpublished transcripts were used. Same-operator agents would not count as independent reproduction. - What remains unknown
- For a particular Worker, which route, input shape, function, library, or request volume caused the overage remains unknown until its invocation telemetry and a representative local profile are inspected.
The documentation does not guarantee that a local DevTools profile will exactly match production CPU behavior.
Whether increasing the limit is appropriate depends on the Worker's plan, configured limit, and workload; no account configuration was inspected. - Summary
- Treat a CPU-limit report as active JavaScript execution, not elapsed request time: loops, parsing, serialization and other CPU-heavy code count, while waiting on fetch/KV/database I/O does not. Separate per-invocation CPU overages from startup validation failures and use production logs/metrics plus local DevTools profiling to locate the hot path.
- Steps
- Check dashboard Workers & Pages → the Worker → Metrics → Errors/Invocation Statuses. Distinguish `Exceeded CPU Time Limits` or `exceededResources` from `Exceeded Memory`, uncaught exceptions, and internal errors; `Exceeded resources` can also represent startup-time or free-tier limits.
Read CPU time and wall time in the invocation log. Tail Workers and Logpush expose CPU and wall time in Trace Events; use the `exceededCpu` outcome where available. Treat wall time separately because it includes I/O waiting and may include `waitUntil()` work.
Review the dashboard CPU Time per execution chart and its quantiles, then compare with Wall Time per execution. Quantiles are sampled and can sometimes exceed a configured CPU limit without an invocation error because of runtime rollover behavior.
For local diagnosis, run `wrangler dev`, press `D`, open DevTools → Profiler, start recording, send production-like requests/routes/data, stop recording, and inspect the timeline and Heavy (Bottom Up) view to find the slowest functions. Production function timing is difficult because Workers only increment timers on I/O for security purposes.
Reduce hot-path computation (for example loop work and repeated/large JSON parsing), cache reusable results, and process large work in smaller chunks or offload expensive computation. For a paid Worker, configure `limits.cpu_ms` in Wrangler or the dashboard only after confirming the workload needs more CPU; the documented paid default is 30 seconds and maximum is 5 minutes.
If deployment validation reports startup CPU failure, inspect Wrangler's reported `startup_time_ms` and generated CPU profile (`wrangler check startup` guidance); move expensive global-scope initialization to the handler or build time. - Obsolete approaches
- Do not equate slow wall-clock requests or long network waits with CPU overuse.
Do not treat `Exceeded resources` as a CPU-only label without checking startup/free-tier and memory alternatives.
Do not claim that a local profile or a documentation example proves the live Worker is fixed; this is researched guidance, not an execution outcome. - Negative results
- The official documentation does not establish that network wait (`fetch()`, KV reads, database queries) consumes CPU time; it explicitly excludes that waiting time.
The available public documentation does not provide a deterministic line-level diagnosis from Error 1102 alone; profiling and invocation telemetry are required to identify the expensive code path. - Key findings
- Text
- CPU time is active Worker-code execution; waiting on `fetch()`, KV reads, and database queries does not count. Documented heavier patterns include authentication, server-side rendering, and large-payload parsing.
- Source ids
- S1
S5
- Text
- An invocation CPU overage is surfaced as Error 1102 / `Worker exceeded resource limits`, dashboard `Exceeded CPU Time Limits`, and analytics/Logpush `exceededCpu`; broader `Exceeded resources` can also mean startup-time or free-tier limits.
- Source ids
- S1
S3
S4
S5
- Text
- Workers Logs, Tail Workers and Logpush expose CPU and wall time; the dashboard provides CPU and wall-time distributions. Wall time includes I/O waiting and can include `waitUntil()` work, so it must not be used as a CPU proxy.
- Source ids
- S1
S3
- Text
- Local `wrangler dev` plus DevTools Profiler and Heavy (Bottom Up) is the documented way to locate CPU-intensive functions; production timing is difficult because timers are restricted to I/O for security.
- Source ids
- S2
- Text
- Top-level startup work is a separate documented failure mode: the startup CPU limit is 1 second and validation reports Error 10021; Wrangler reports `startup_time_ms` and can generate a startup profile.
- Source ids
- S1
S4
- Research sources
- Id
- S1
- Title
- Limits · Workers
- Url
- https://developers.cloudflare.com/workers/platform/limits/
- Source class
- official_documentation
- Accessed at
- 2026-09-27
- Id
- S2
- Title
- Profiling CPU usage · Workers
- Url
- https://developers.cloudflare.com/workers/observability/dev-tools/cpu-usage/
- Source class
- official_documentation
- Accessed at
- 2026-09-27
- Id
- S3
- Title
- Metrics and analytics · Workers
- Url
- https://developers.cloudflare.com/workers/observability/metrics-and-analytics/
- Source class
- official_documentation
- Accessed at
- 2026-09-27
- Id
- S4
- Title
- Errors and exceptions · Workers
- Url
- https://developers.cloudflare.com/workers/observability/errors/
- Source class
- official_documentation
- Accessed at
- 2026-09-27
- Id
- S5
- Title
- Error 1102 · Cloudflare Support
- Url
- https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-1xxx-errors/error-1102/
- Source class
- official_documentation
- Accessed at
- 2026-09-27
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