Request Logs: Span Attributes

Understanding Span Attributes

Each span you query from LLM Gateway captures key request and model details. Recognizing these attributes helps you analyze and debug usage effectively.

Core Span Attributes

Attribute	Description
`tfy.span_type`	Type of span, with possible values: • `"ChatCompletion"` - Complete chat request lifecycle • `"Completion"` - Text completion requests without chat context • `"MCP"` - Model Context Protocol server interactions and tool calls • `"Rerank"` - Document reranking operations for search relevance • `"Embedding"` - Vector embedding generation operations • `"Model"` - Actual LLM model inference processing • `"AgentResponse"` - Multi-tool agent orchestration workflows • `"Guardrail"` - Safety, compliance, and content validation checks
`tfy.input`	Complete input data sent to the model, mcp_server, guardrail, etc..
`tfy.output`	Complete output response from the model, mcp_server, guardrail, etc..
`tfy.input_short_hand`	Abbreviated version of the input for display purposes
`tfy.error_message`	Error message if the request failed
`tfy.prompt_version_fqn`	FQN of the prompt version used (if applicable)
`tfy.prompt_variables`	Variables used in prompt templating
`tfy.triggered_guardrail_fqns`	String array of the fully qualified names of the guardrails that were triggered during the request. Emitted on `ChatCompletion`, `AgentResponse`, and `MCPGateway` spans — see Triggered guardrails on request spans.

Request Context Attributes

Attribute	Description
`tfy.request.model_name`	Name of the model that was requested
`tfy.request.created_by_subject`	Subject (user/service account) that made the request
`tfy.request.created_by_subject_teams`	Teams associated with the requesting subject
`tfy.request.metadata`	Additional metadata associated with the request (e.g., `{'foo': 'bar'}`)
`tfy.request.conversation_id`	Unique identifier for the conversation (if part of a chat)

Model Attributes

Attribute	Description
`tfy.model.id`	Unique identifier of the model
`tfy.model.name`	Display name of the model
`tfy.model.fqn`	Fully qualified name of the model
`tfy.model.request_url`	URL endpoint used for the model request
`tfy.model.streaming`	Whether the request used streaming mode
`tfy.model.request_type`	Type of request (e.g., `"ChatCompletion", "Completion", "Embedding", "Rerank", "AgentResponse", "MCPGateway", "CreateModelResponse"`)
`tfy.model.metric.cache_read_input_tokens`	Number of input tokens served from the cache, billed at a lower cache read rate instead of the standard input rate
`tfy.model.metric.cache_creation_input_tokens`	Number of input tokens written to the cache, billed at a higher cache write rate to cover the cost of storage

Model Performance Metrics

Attribute	Description
`tfy.model.metric.time_to_first_token_in_ms`	Time taken to receive the first token (streaming)
`tfy.model.metric.latency_in_ms`	Total request latency in milliseconds
`tfy.model.metric.input_tokens`	Number of tokens in the model input
`tfy.model.metric.output_tokens`	Number of tokens in the model output
`tfy.model.metric.cost_in_usd`	Cost of the request in USD
`tfy.model.metric.inter_token_latency_in_ms`	Average latency between tokens (streaming)

Load Balancing Attributes

Attribute	Description
`applied_loadbalance_rule_ids`	IDs of load balancing rules that were applied (e.g., `['gpt-4-dev-load']`)

Budget Control Attributes

Attribute	Description
`applied_budget_rule_ids`	IDs of budget rules that were applied to this request (e.g., `['virtualaccount1-monthly-budget']`)

Rate Limiting Attributes

Attribute	Description
`applied_ratelimit_rule_ids`	IDs of all rate limiting rules that were applied (e.g., `['virtualaccount1-daily-ratelimit']`)

MCP (Model Context Protocol) Server Attributes

Attribute	Description
`tfy.mcp_server.id`	Unique identifier of the MCP server
`tfy.mcp_server.name`	Display name of the MCP server
`tfy.mcp_server.url`	URL endpoint of the MCP server
`tfy.mcp_server.fqn`	Fully qualified name of the MCP server
`tfy.mcp_server.server_name`	Internal name of the MCP server
`tfy.mcp_server.method`	MCP method that was called
`tfy.mcp_server.primitive_name`	Name of the MCP primitive used
`tfy.mcp_server.error_code`	Error code if the MCP call failed
`tfy.mcp_server.is_tool_call_execution_error`	Whether the error was from tool call execution

MCP Server Metrics

Attribute	Description
`tfy.mcp_server.metric.latency_in_ms`	Latency of the MCP server call in milliseconds
`tfy.mcp_server.metric.number_of_tools`	Number of tools available in the MCP server

Guardrail Attributes

Attribute	Description
`tfy.guardrail.id`	Unique identifier of the guardrail
`tfy.guardrail.name`	Display name of the guardrail
`tfy.guardrail.fqn`	Fully qualified name of the guardrail
`tfy.guardrail.result`	Outcome of the guardrail check. See the value table below.
`tfy.guardrail.enforcing_strategy`	The enforcement strategy the guardrail ran under: `enforce`, `enforce_but_ignore_on_error`, or `audit`

Guardrail result values

Value	Meaning
`flag`	The guardrail flagged the content and the request was blocked
`error`	The guardrail failed to run and the request was blocked. Only possible under the `enforce` strategy
`mutation`	The guardrail modified the content, for example by redacting or masking it
`ignored_error`	The guardrail failed to run but the request continued. This is what an error becomes under `enforce_but_ignore_on_error` and `audit`
`pass`	The guardrail ran and raised nothing. Appears on individual `Guardrail` spans only
`audit_mode_flag`	The guardrail would have blocked, but ran in `audit` mode so the request continued. Appears on individual `Guardrail` spans only

Triggered guardrails on request spans

Individual guardrail checks each get their own Guardrail child span. Their outcomes are also rolled up onto the enclosing request span, so you can find requests affected by a guardrail without expanding the trace. The roll-up sets both tfy.triggered_guardrail_fqns and tfy.guardrail.result, and applies to ChatCompletion, AgentResponse, and MCPGateway spans. A few things to know when querying it:

pass and audit_mode_flag are not rolled up. Only outcomes that actually affected the request appear — flag, error, mutation, and ignored_error. A request whose guardrails all passed carries neither attribute.
Errors are included on purpose, so a guardrail that failed to run is distinguishable from one that ran and passed.
tfy.guardrail.result on a request span is a single worst-case value. When several guardrails trigger, precedence is flag > error > mutation > ignored_error. Per-guardrail detail stays on the Guardrail child spans.
Each guardrail appears once in tfy.triggered_guardrail_fqns. A guardrail that triggers on both input and output is deduplicated, keeping its most severe outcome.
The roll-up does not extend to other request types. Endpoints such as /v1/messages, /v1/responses, embeddings, and rerank still run guardrails and still record Guardrail child spans, but emit no request-span roll-up. Query the child spans for those.

The child Model span does not carry these attributes either. For a /chat/completions request the roll-up lives on the ChatCompletion root span, not on the Model: <model> span beneath it.

Guardrail Applied Entity Attributes

Attribute	Description
`tfy.guardrail.applied_on_entity.type`	Type of entity the guardrail was applied to
`tfy.guardrail.applied_on_entity.id`	ID of the entity
`tfy.guardrail.applied_on_entity.name`	Name of the entity
`tfy.guardrail.applied_on_entity.fqn`	FQN of the entity
`tfy.guardrail.applied_on_entity.scope`	Scope of the entity

Guardrail Metrics

Attribute	Description
`tfy.guardrail.metric.latency_in_ms`	Time taken for the guardrail check in milliseconds

HTTP Response Attributes

Attribute	Description
`http.response.status_code`	HTTP status code of the response

GenAI attributes

The gateway can also dual-write OpenTelemetry GenAI semantic convention attributes (gen_ai.*). See GenAI span attributes for enabling the feature, the full attribute mapping, content/privacy behavior, and current limitations.

Get Started

LLM Gateway

MCP Registry and Gateway

Skills Registry

Prompt Registry

Guardrails and Security

Observability

Deployment

Admin Guide

Chat

Messages

Embeddings

Rerank

Responses

Image

Audio

Batch

Files

Fine-tuning

Moderations

Models

Request Logs: Span Attributes

Understanding Span Attributes

Core Span Attributes

Request Context Attributes

Model Attributes

Model Performance Metrics

Load Balancing Attributes

Budget Control Attributes

Rate Limiting Attributes

MCP (Model Context Protocol) Server Attributes

MCP Server Metrics

Guardrail Attributes

Guardrail result values

Triggered guardrails on request spans

Guardrail Applied Entity Attributes

Guardrail Metrics

HTTP Response Attributes

GenAI attributes

References

​Understanding Span Attributes

​Core Span Attributes

​Request Context Attributes

​Model Attributes

​Model Performance Metrics

​Load Balancing Attributes

​Budget Control Attributes

​Rate Limiting Attributes

​MCP (Model Context Protocol) Server Attributes

​MCP Server Metrics

​Guardrail Attributes

​Guardrail result values

​Triggered guardrails on request spans

​Guardrail Applied Entity Attributes

​Guardrail Metrics

​HTTP Response Attributes

​GenAI attributes

​References

Understanding Span Attributes

Core Span Attributes

Request Context Attributes

Model Attributes

Model Performance Metrics

Load Balancing Attributes

Budget Control Attributes

Rate Limiting Attributes

MCP (Model Context Protocol) Server Attributes

MCP Server Metrics

Guardrail Attributes

Guardrail result values

Triggered guardrails on request spans

Guardrail Applied Entity Attributes

Guardrail Metrics

HTTP Response Attributes

GenAI attributes

References