Azure Functions: No job functions found. Try making your job classes
The host started but indexed zero functions, so there is nothing to run. The message talks about public classes, which is a .NET in-process hint, yet the real cause is usually elsewhere: FUNCTIONS_WORKER_RUNTIME not matching the code, a .NET isolated app deployed with the in-process setting, a Python v2 app whose function_app.py failed to import, or a deployment that published the project folder instead of the build output.
Quick fix
Read the commands before running them. Anything that restarts a service, deletes data or changes permissions should be tried on a non-production system first.
# What does the app think it is running?
az functionapp config appsettings list -n my-func -g my-rg \
--query "[?name=='FUNCTIONS_WORKER_RUNTIME' || name=='FUNCTIONS_EXTENSION_VERSION']"
# .NET isolated must say dotnet-isolated, Python must say python
az functionapp config appsettings set -n my-func -g my-rg --settings FUNCTIONS_WORKER_RUNTIME=dotnet-isolated
# Run locally with verbose logging to see the import or indexing error
func start --verbose
# Python v2: an import error in function_app.py hides every function
python -c "import function_app"
# Publish the build output, not the source tree
func azure functionapp publish my-funcHow to diagnose Serverless errors
Serverless errors are shaped by hard platform limits: execution duration, deployment package size, memory, and concurrency. Unlike a server you control, these cannot be tuned away. The fix is to restructure the workload. VPC-attached functions add a second class of problem, because they lose default internet access and depend on ENI capacity and NAT configuration.
If the quick fix above does not resolve it, work through these steps. They apply to this whole class of error, not just to this one message, which is usually what saves the time.
- Check the platform limit before changing code: timeout, package size and memory are all documented, and the error is usually the limit being reported literally.
- For timeouts, add timing logs around each external call. A function that times out is nearly always waiting on one downstream dependency.
- Reduce package size with layers, tree-shaking, and by excluding dev dependencies and the provider SDK that the runtime already includes.
- For VPC functions with no internet access, confirm there is a NAT Gateway or the relevant VPC endpoints. A function in a private subnet cannot reach the public internet by default.
- Measure cold start separately from warm invocation in your metrics, and use provisioned concurrency only after confirming cold starts are the actual problem.
Tools worth reaching for
CloudWatch Logs Insightsaws lambda get-function-configurationX-Ray / distributed tracingsam local invoke
Authoritative references
Primary documentation for this error, worth reading before applying any fix in production.
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Something missing or wrong?
This entry is maintained by hand. If the fix is out of date, incomplete, or you have a better one, email a correction and it will be reviewed.