workers-profiling

1# Workers profiling
2 
3Find expensive functions or memory allocations in deployed code and come up with ways to fix them.
4 
5## Retrieve the docs
6 
7Start with the [production profiling guide](https://developers.cloudflare.com/workers/observability/profiling-in-production/index.md) to understand how
8Workers and Durable Objects profiling works.
9 
10## Profiling steps
11 
121. Identify the symptom and affected workload: CPU usage, latency, allocation pressure, or memory growth.
132. Confirm the account, Worker, environment, and deployed version with the user.
143. For a Durable Object, also confirm its owning Worker, namespace, and instance.
154. Choose CPU or heap profiling from the current guide's supported types and meanings.
16 
17Where possible, use the [`cf` CLI](https://developers.cloudflare.com/cf/index.md) to capture profiles. If the user requests `cf`, inspect the installed version's command help and schema where available.
18 
19If `cf` isn't available, consider prompting the user whether they would like to install it.
20 
21 
22The profiling API will return a pprof file which you can analyze directly, or using appropriate tools like Go's `pprof` utility.
23 
24## Inspect the evidence
25 
26- Read the pprof file and analyse it for hotspots
27- Map hotspots to functions and source locations when evidence supports it; report missing symbols or source mappings.
28- If filenames and function names are pointing at the generated JavaScript, consider suggesting to the user to enable source maps and re-do the profiling.
29…