OpenTelemetry Semantic Conventions for GenAI Operations - Support Overview

[ThomasVitale]

Based on the Semantic Conventions 1.27.0. See docs. This issue is to keep track of the work I've been doing for the Spring AI initial adoption of the OpenTelemetry Semantic Conventions for GenAI Operations.

Traces

Span Names

Span Name	Spring AI	Requirement
{gen_ai.operation.name} {gen_ai.request.model}	✅	Recommended

Span Kinds

Span Kind	Spring AI	Requirement	Comments
CLIENT/INTERNAL	✅	Required	The kind is currently INTERNAL (background info on why: https://github.com/open-telemetry/semantic-conventions/issues/1315).

Span Attributes

Span Attribute	Type	Spring AI	Requirement	Comments
gen_ai.operation.name	string	✅	Required
gen_ai.request.model	string	✅	Required
gen_ai.system	string	✅	Required
error.type	string	⬇️	Conditionally Required if the operation ended in an error	There isn't currently a plan to support it in Spring AI. You can find error information as a span event and also in the child HTTP span auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.
server.port	int	⬇️	Conditionally Required If server.address is set.	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information in the child HTTP span auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.
gen_ai.request.frequency_penalty	double	✅	Recommended
gen_ai.request.max_tokens	int	✅	Recommended
gen_ai.request.presence_penalty	double	✅	Recommended
gen_ai.request.stop_sequences	string[]	✅	Recommended
gen_ai.request.temperature	double	✅	Recommended
gen_ai.request.top_k	double	✅	Recommended
gen_ai.request.top_p	double	✅	Recommended
gen_ai.response.finish_reasons	string[]	✅	Recommended
gen_ai.response.id	string	✅	Recommended
gen_ai.response.model	string	✅	Recommended
gen_ai.usage.input_tokens	int	✅	Recommended
gen_ai.usage.output_tokens	int	✅	Recommended
server.address	string	⬇️	Recommended	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information in the child HTTP span auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.

Event Names

Event Name	Spring AI	Requirement	Comments
gen_ai.content.prompt	✅	Optional	Coming soon. Being implemented right now.
gen_ai.content.completion	✅	Optional	Coming soon. Being implemented right now.

Event Attributes

Event Attribute	Type	Spring AI	Requirement	Comments
gen_ai.prompt	string	✅	Conditionally Required if and only if corresponding event is enabled	Coming soon. Being implemented right now. Currently, it's available as a span attribute.
gen_ai.completion	string	✅	Conditionally Required if and only if corresponding event is enabled	Coming soon. Being implemented right now. Currently, it's available as a span attribute.

Metrics

Metric: Token Usage

Metric Name	Type	Unit	Spring AI	Requirement	Comments
gen_ai.client.token.usage	Histogram	{token}	🔮	Recommended	Coming soon. Being implemented right now. Currently, it's available, but not following the naming strategy.

Metric Attribute	Type	Spring AI	Requirement	Comments
gen_ai.operation.name	string	✅	Required
gen_ai.request.model	string	✅	Required
gen_ai.system	string	✅	Required
gen_ai.token.type	string	✅	Required
server.port	int	⬇️	Conditionally Required If server.address is set.	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information as part of the HTTP metrics auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.
gen_ai.response.model	string	✅	Recommended
server.address	string	⬇️	Recommended	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information as part of the HTTP metrics auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.

Metric: Operation Duration

Metric Name	Type	Unit	Spring AI	Requirement	Comments
gen_ai.client.operation.duration	Histogram	s	🔮	Recommended	Coming soon. Being implemented right now. Currently, it's available, but not following the naming strategy.

Metric Attribute	Type	Spring AI	Requirement	Comments
gen_ai.operation.name	string	✅	Required
gen_ai.request.model	string	✅	Required
gen_ai.system	string	✅	Required
error.type	string	⬇️	Conditionally Required if the operation ended in an error.	There isn't currently a plan to support it in Spring AI. You can find this information as part of the HTTP metrics auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.
server.port	int	⬇️	Conditionally Required If server.address is set.	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information as part of the HTTP metrics auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.
gen_ai.response.model	string	✅	Recommended
server.address	string	⬇️	Recommended	This attribute is optional. There isn't currently a plan to support it in Spring AI. You can find this information as part of the HTTP metrics auto-configured by Spring Boot. If you encounter a use-case in production where that is not enough, we would like to hear from you. Please, let us know by raising an issue and describing your scenario, so that we can get additional context and evaluate if and how to add this attribute to meet your needs.

[lmolkova]

User application may be configured to disable (not enable/suppress/sample-out/drop) HTTP/gRPC/underlying protocol.

That's the main reason that OTel uses kind client, but also one of the reasons to have server.address|port and error.type on the LLM spans/metrics.

Other reasons to report server.address|port and error.type on LLM telemetry are:

• HTTP client metrics don't have context to differentiate operations
• error rate on HTTP layer does not represent error rate for logical LLM (LLM operations are retrying under)
• same on latency/throughput
• generic HTTP instrumentations have limited capacity to describe streaming calls - they don't always know when/if the stream ends and are likely to record duration to headers (not to end-of-stream). As a result, they won't include errors that happen when connection drops/times out during SSE stream
• users would have much easier time analyzing their telemetry if they could build LLM-specific dashboards/alerts (i.e. were able to differentiate endpoints and errors on LLM telemetry as opposed to deriving it from HTTP one)

[ThomasVitale]

@lmolkova thank you for sharing more details about how those attributes would be used, it was helpful. I have updated the table with a better description of the current adoption state and suggestion for future changes.

Considering that most Spring applications will have HTTP metrics and traces enabled, and that adding those HTTP attributes would require a major refactoring of the framework (including considerations for avoiding a raise in the time series due to information duplications), I think it would be beneficial to hear from the community a bit more about their observability needs and use cases that would require those additional attributes before making any change.

In any case, I'd like to point out the overview above is to keep track of the work I've been doing right now as a contributor to this project for the initial observability support in Spring AI. It's not an official or even comprehensive roadmap, and it's definitely not a final task. It's a start :)

[codefromthecrypt]

took your demo for a spin. ping back when you've span events as I'll be interested to take a second look.

[piotrooo]

OFFTOPIC: @codefromthecrypt what tool do you use for the traces?

[codefromthecrypt]

@piotrooo https://github.com/ymtdzzz/otel-tui otherwise known as "missing 1000 github stars". It is technically an otel collector extension, bundled for convenience into one binary.