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Monitoring

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Note

AI Gateway requires the AI Governance Add-On. As of Coder v2.32, deployments without the add-on will not be able to access AI Gateway.

AI Gateway records the last user prompt, token usage, model reasoning, and every tool invocation for each intercepted request. Each capture is tied to a single "interception" that maps back to the authenticated Coder identity, making it easy to attribute spend and behaviour.

User Prompt logging

User Leaderboard

We provide an example Grafana dashboard that you can import as a starting point for your metrics. See the Grafana dashboard README.

These logs and metrics can be used to determine usage patterns, track costs, and evaluate tooling adoption.

Provider metrics

AI Gateway (the in-process daemon) and AI Gateway Proxy (the external proxy) each export Prometheus metrics describing the configured provider pool and its reload loop. See Provider Configuration for the lifecycle these metrics describe.

Metric	Type	Labels	Purpose
`coder_ai_gateway_provider_info`	gauge	`provider_name`, `provider_type`, `status`	One series per configured provider. Value is always `1`; the `status` label (`enabled`, `disabled`, `error`) carries the alertable signal.
`coder_ai_gateway_providers_last_reload_timestamp_seconds`	gauge		Unix timestamp of the last reload attempt, success or failure.
`coder_ai_gateway_providers_last_reload_success_timestamp_seconds`	gauge		Unix timestamp of the last reload that successfully refreshed the pool.
`coder_ai_gateway_proxy_provider_info`	gauge	`provider_name`, `provider_type`, `status`	Same shape as `coder_ai_gateway_provider_info` but reported by the external proxy.
`coder_ai_gateway_proxy_providers_last_reload_timestamp_seconds`	gauge		Last reload attempt timestamp in the external proxy.
`coder_ai_gateway_proxy_providers_last_reload_success_timestamp_seconds`	gauge		Last successful reload timestamp in the external proxy.
`coder_ai_gateway_proxy_connect_sessions_total`	counter	`type` (`mitm`, `tunneled`)	CONNECT sessions established by the proxy.
`coder_ai_gateway_proxy_mitm_requests_total`	counter	`provider`	MITM requests handled.
`coder_ai_gateway_proxy_inflight_mitm_requests`	gauge	`provider`	In-flight MITM requests.
`coder_ai_gateway_proxy_mitm_responses_total`	counter	`code`, `provider`	MITM responses by HTTP status code.

Important

The AI Gateway metric prefixes were renamed: coder_aibridged_* became coder_ai_gateway_* and coder_aibridgeproxyd_* became coder_ai_gateway_proxy_*. This rename covers every AI Gateway metric, including the interception, token, prompt, tool, and circuit-breaker counters listed in the Prometheus reference. The legacy coder_aibridged_* and coder_aibridgeproxyd_* names are still emitted with identical values during the v2.35 and v2.36 deprecation window. They are planned for removal in v2.37. Migrate dashboards and alerts to the new names now. Do not relabel new names back to old names while legacy names are still emitted, because that creates duplicate legacy series in the same scrape. After legacy names are removed, use metric_relabel_configs only if you need a temporary compatibility bridge for dashboards that still use the old names:

metric_relabel_configs:
  # Proxy rule must come first; the gateway regex below also matches proxy metrics.
  - source_labels: [__name__]
    regex: 'coder_ai_gateway_proxy_(.*)'
    target_label: __name__
    replacement: 'coder_aibridgeproxyd_${1}'
  - source_labels: [__name__]
    regex: 'coder_ai_gateway_(.*)'
    target_label: __name__
    replacement: 'coder_aibridged_${1}'

Suggested alerts

Alert on any provider entering a non-enabled status:

sum by (provider_name, status) (coder_ai_gateway_provider_info{status!="enabled"}) > 0

Alert when the reload loop is firing but failing to refresh the pool for longer than a few minutes:

(coder_ai_gateway_providers_last_reload_timestamp_seconds
  - coder_ai_gateway_providers_last_reload_success_timestamp_seconds) > 300

Repeat the same query against coder_ai_gateway_proxy_* if you run the external proxy.

Structured Logging

AI Gateway can emit structured logs for every interception event to your existing log pipeline. This is useful for exporting data to external SIEM or observability platforms. See Structured Logging in the setup guide for configuration and a full list of record types.

Exporting Data

AI Gateway interception data can be exported for external analysis, compliance reporting, or integration with log aggregation systems.

REST API

You can retrieve AI Gateway sessions via the Coder API, with filtering and pagination support.

curl -X GET "https://coder.example.com/api/v2/ai-gateway/sessions" \
  -H "Coder-Session-Token: $CODER_SESSION_TOKEN"

Available query filters:

client - Filter by client name.
Possible client values

[!NOTE] Client classification is done on best effort basis using the User-Agent header; not all clients send these headers in an easily-identifiable manner.
- Claude Code
- Codex
- Zed
- GitHub Copilot (VS Code)
- GitHub Copilot (CLI)
- Kilo Code
- Coder Agents
- Mux
- Cursor
- OpenCode
- Unknown
initiator - Filter by user ID or username
provider - Filter by AI provider (e.g., openai, anthropic)
model - Filter by model name
started_after - Filter sessions after a timestamp
started_before - Filter sessions before a timestamp

See the API documentation for full details.

Data Retention

AI Gateway data is retained for 60 days by default. Configure the retention period to balance storage costs with your organization's compliance and analysis needs.

For configuration options and details, see Data Retention in the AI Gateway setup guide.

Tracing

AI Gateway supports tracing via OpenTelemetry, providing visibility into request processing, upstream API calls, and MCP server interactions.

Enabling Tracing

AI Gateway tracing is enabled when tracing is enabled for the Coder server. To enable tracing set CODER_TRACE_ENABLE environment variable or --trace CLI flag:

export CODER_TRACE_ENABLE=true

coder server --trace

What is Traced

AI Gateway creates spans for the following operations:

Span Name	Description
`CachedBridgePool.Acquire`	Acquiring a request bridge instance from the pool
`Intercept`	Top-level span for processing an intercepted request
`Intercept.CreateInterceptor`	Creating the request interceptor
`Intercept.ProcessRequest`	Processing the request through the bridge
`Intercept.ProcessRequest.Upstream`	Forwarding the request to the upstream AI provider
`Intercept.ProcessRequest.ToolCall`	Executing a tool call requested by the AI model
`Intercept.RecordInterception`	Recording creating interception record
`Intercept.RecordPromptUsage`	Recording prompt/message data
`Intercept.RecordTokenUsage`	Recording token consumption
`Intercept.RecordToolUsage`	Recording tool/function calls
`Intercept.RecordInterceptionEnded`	Recording the interception as completed
`ServerProxyManager.Init`	Initializing MCP server proxy connections
`StreamableHTTPServerProxy.Init`	Setting up HTTP-based MCP server proxies
`StreamableHTTPServerProxy.Init.fetchTools`	Fetching available tools from MCP servers

Example trace of an interception using Jaeger backend:

Trace of interception

Capturing Logs in Traces

Note

Enabling log capture may generate a large volume of trace events.

To include log messages as trace events, enable trace log capture by setting CODER_TRACE_LOGS environment variable or using --trace-logs flag:

export CODER_TRACE_ENABLE=true
export CODER_TRACE_LOGS=true

coder server --trace --trace-logs