Implement Azure Functions metadata detection
- Dominant language
- Gherkin
- Stars
- 427
- Forks
- 125
- PR merge metrics
- No merged PRs in 30d
Description
# Description
See:
* https://github.com/elastic/apm/blob/main/specs/agents/metadata.md#azure-functions
* Gherkin spec: https://github.com/elastic/apm/blob/main/tests/agents/gherkin-specs/azure_functions_metadata.feature
* https://github.com/elastic/apm/pull/712
## Agent Issues
- [ ] https://github.com/elastic/apm-agent-java/issues/2964 
- [x] https://github.com/elastic/apm-agent-dotnet/issues/1974 
- [ ] https://github.com/elastic/apm-agent-nodejs/issues/3089 
- [ ] https://github.com/elastic/apm-agent-python/issues/1722 
- [ ] https://github.com/elastic/apm-agent-go/issues/1369 
- [ ] https://github.com/elastic/apm-agent-php/issues/849 
- [ ] https://github.com/elastic/apm-agent-ruby/issues/1348 
Contributor guide
No contributing guide indexed for this repository
Research direction
Read the Azure Functions section of specs/agents/metadata.md and the Gherkin scenario in tests/agents/gherkin-specs/azure_functions_metadata.feature. Use the referenced pull request and unchecked agent issues to identify the target agent repository, then implement the specified metadata detection there. Done means the Azure Functions metadata scenario passes for the relevant agent.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- azure
- Domain
- cloud
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100