Monitoring

Conduit exposes operational metrics in the Prometheus exposition format — the de-facto standard scraped natively by Prometheus, Grafana Alloy, the OpenTelemetry Collector, Datadog, VictoriaMetrics, Telegraf, and the managed Prometheus services of the major clouds. The same metrics are also pushed over OTLP to every instance-level OpenTelemetry exporter configured in Settings → Instance → Telemetry (and to one configured via the standard OTEL_EXPORTER_OTLP_* environment variables), alongside the traces and events Conduit already sends — see Telemetry Export. If your observability backend ingests OTLP, you get these metrics with no extra configuration; the scrape endpoint below is for Prometheus-style pull pipelines. Metrics are aggregates over the whole instance, so they are not part of what a workspace’s own exporters receive.

Enabling the endpoint

Set CONDUIT_METRICS_ADDR to start a dedicated listener serving /metrics:

docker run -p 7272:7272 \
  -e CONDUIT_METRICS_ADDR=0.0.0.0:9464 \
  ghcr.io/pipedreamhq/conduit

Unset (the default), no listener starts and nothing is exposed. On Kubernetes with the Helm chart, set metrics.enabled: true — it sets the variable and adds a metrics container port (9464). The port is deliberately not part of the chart’s Service or Ingress: scraping happens at the pod IP, and the endpoint can never be exposed through the public entry point by accident.

Security posture

The endpoint is unauthenticated by design — the standard posture for scrape endpoints across self-hosted software (scrapers are robots; access control is network position). It reveals operational shape (connector kinds and ids, and in a single-workspace deployment connector names; request rates, session counts) but never payloads, secrets, or per-user data. Treat it accordingly:

Bind a private interface, or rely on network segmentation (on Kubernetes, a NetworkPolicy restricting the port to your monitoring namespace).
Never route it through a public ingress or load balancer.
If your network is flat and you need transport auth, front the port with an authenticating proxy — Prometheus supports bearer tokens, basic auth, OAuth2, and mutual TLS in scrape_config.

Scraping

A minimal Prometheus scrape_config:

scrape_configs:
  - job_name: conduit
    static_configs:
      - targets: ["conduit.internal:9464"]

On Kubernetes, any pod-scraping mechanism works. With annotation-based discovery, add to the chart’s podAnnotations:

podAnnotations:
  prometheus.io/scrape: "true"
  prometheus.io/port: "9464"

With the Prometheus operator, a PodMonitor selecting the release’s pod labels and the metrics port does the same job. Each replica is scraped individually and reports its own counters — that is the Prometheus model, not a limitation. Aggregate across replicas in queries: sum by (connector_kind, connector_id) (rate(conduit_mcp_tool_calls_total[5m])).

Restarts and counter resets

Metrics are aggregated in memory and reset to zero when the process restarts. Consumers are built for this: rate() and increase() detect and splice across resets, and at most the few seconds since the last scrape are lost. Durable history lives in your monitoring backend, not in Conduit — anything Conduit must count exactly (usage dashboards, the audit log) is stored in its database independently of these metrics.

Metric reference

Conventions: counters end in _total, durations are histograms in seconds (exposed as _bucket, _sum, and _count series), and every label has a small, bounded value set — metrics never carry user, client, or per-request identifiers.

Gateway

Metric	Description
`conduit_mcp_tool_calls_total`	Counter of tool calls served by the MCP gateway, by `connector_kind`, `connector_id` and `outcome`. Outcomes: `ok`, `error` (the call ran and failed), and `denied` (blocked by access policy before running).
`conduit_mcp_tool_call_duration_seconds`	Histogram of executed tool-call duration, by `connector_kind` (plus `connector_id` and `connector` in a single-workspace deployment), including the upstream round trip. Denied calls never run, so they record no duration.
`conduit_mcp_prompt_gets_total`	Counter of prompt fetches (`prompts/get`) served by the MCP gateway, by `connector_kind`, `connector_id` and `outcome` (`ok`, `error`, `denied`).
`conduit_mcp_resource_reads_total`	Counter of resource reads (`resources/read`) served by the MCP gateway, by `connector_kind`, `connector_id` and `outcome` (`ok`, `error`, `denied`).
`conduit_mcp_auth_failures_total`	Counter of rejected MCP requests, by `reason`: `missing_token`, `invalid_token`, `session_expired`, `org_ambiguous`, `client_revoked`, `client_not_allowed`, `sign_in_not_accepted`, `sign_in_too_old`, `sign_in_provider_gone`, `sign_in_password_off`, or `rate_limited`. A burst of the credential reasons is the signature of a client with a broken credential — or of someone guessing; `client_revoked` and `client_not_allowed` are a workspace refusing a valid token’s client (a workspace revoke, or its policy against dynamically registered clients); the `sign_in_*` reasons are a workspace’s sign-in policy refusing how the token’s holder signed in, or the way they signed in being turned off (a provider disabled or deleted, or password sign-in turned off).
`conduit_mcp_sse_sessions`	Gauge of currently connected MCP SSE sessions on this replica. A sudden drop to zero while the process is up usually means a load balancer or proxy severed the streams.

A connector is labeled by its kind and id. connector_kind is builtin (Conduit’s own tools), pipedream, custom (a connector a workspace configured), local (a stdio connector the Conduit CLI runs), or unknown (no single connector resolved: a call naming a connector that doesn’t exist, or one that is disabled or failed to load, or a local connector the CLI reported that matches no stdio connector). connector_id is a custom or local connector’s id — connector.id on traces and events, and id in the connectors table — and empty otherwise. In a single-workspace deployment, where the one workspace is the instance, every gateway metric also carries the connector’s name in a connector label. In a multi-workspace deployment the name belongs to the workspace that chose it and is never a label, and the duration histogram leaves out connector_id too, to bound its series: break latency down per connector with traces (connector.id on mcp.upstream.send) instead.

HTTP

Metric	Description
`http_server_request_duration_seconds`	Histogram of API, OAuth, and SCIM request duration, by `http_route` (the matched route pattern, never the raw URL), `http_request_method`, and `http_response_status_code`. Health probes, static assets, and the long-lived MCP streams are excluded — they would only skew a request-duration distribution.

Database

Each database metric is reported per database (db is main or usage) and per connection pool (pool is read or write):

Metric	Description
`conduit_db_connections_open`	Gauge of open connections.
`conduit_db_connections_in_use`	Gauge of connections currently executing a query.
`conduit_db_connections_waits_total`	Counter of times a request had to wait for a free connection — the pool-saturation signal.
`conduit_db_connections_wait_duration_seconds_total`	Counter of total time spent waiting for connections. Growing wait time with flat traffic means the pool is undersized for the workload.

Process

Metric	Description
`conduit_build_info`	Gauge with constant value `1`, labeled with the running `version`. Join other metrics against it to see which version each replica runs — most useful mid-rollout.
`conduit_usage_recorder_dropped_total`	Counter of usage events dropped because the internal buffer was full. Sustained growth means the usage pipeline (the durable store behind the in-product dashboards) is shedding load.

Standard Go runtime and process metrics (go_* — goroutines, memory, GC — and process_* — CPU, RSS, file descriptors, start time) are exposed alongside the application metrics.

Useful starting queries

Paste these into the Prometheus Graph tab or a Grafana panel. Most of them also make sensible first alert rules — thresholds depend on your traffic, so chart them for a while before alerting.

Tool-call error rate

The fraction of executed tool calls that failed, per connector. A single connector spiking usually means an upstream outage or an expired credential; everything spiking at once points at the gateway or its network.

sum by (connector_kind, connector_id) (rate(conduit_mcp_tool_calls_total{outcome="error"}[5m]))
  / sum by (connector_kind, connector_id) (rate(conduit_mcp_tool_calls_total[5m]))

Tool-call latency

The 99th-percentile duration of executed tool calls. Aggregating _bucket series with sum by (le) makes this correct across replicas; add connector_kind (and, in a single-workspace deployment, connector) to the by clause to break it down.

histogram_quantile(0.99,
  sum by (le) (rate(conduit_mcp_tool_call_duration_seconds_bucket[5m])))

Policy denials

Calls blocked by access policy. A steady trickle is normal (clients probe tools they can’t see); a step change after a policy edit means the edit cut off something real, and a sustained stream is a client misconfigured or probing.

sum by (connector_kind, connector_id) (rate(conduit_mcp_tool_calls_total{outcome="denied"}[5m]))

Authentication failures

Rejected MCP requests by reason. Alert on sustained invalid_token volume — that’s either a fleet of clients with stale credentials or someone guessing bearer tokens.

sum by (reason) (rate(conduit_mcp_auth_failures_total[5m]))

Replica health

Prometheus synthesizes an up series per scrape target — no Conduit metric needed. This is the first alert to configure.

up == 0

Database pool saturation

Time spent waiting for a database connection, per second. Zero is the healthy steady state; any sustained non-zero value means requests are queuing for the pool and latency is following.

rate(conduit_db_connections_wait_duration_seconds_total[5m])

Usage pipeline drops

Usage events dropped because the recorder’s buffer was full. Anything above zero means the in-product usage dashboards are undercounting under load.

rate(conduit_usage_recorder_dropped_total[5m]) > 0

Use Conduit

Administer Conduit

Deploy Conduit

Conduit Cloud

Enabling the endpoint

Security posture

Scraping

Restarts and counter resets

Metric reference

Gateway

HTTP

Database

Process

Useful starting queries

Tool-call error rate

Tool-call latency

Policy denials

Authentication failures

Replica health

Database pool saturation

Usage pipeline drops

​Enabling the endpoint

​Security posture

​Scraping

​Restarts and counter resets

​Metric reference

​Gateway

​HTTP

​Database

​Process

​Useful starting queries

​Tool-call error rate

​Tool-call latency

​Policy denials

​Authentication failures

​Replica health

​Database pool saturation

​Usage pipeline drops

Enabling the endpoint

Security posture

Scraping

Restarts and counter resets

Metric reference

Gateway

HTTP

Database

Process

Useful starting queries

Tool-call error rate

Tool-call latency

Policy denials

Authentication failures

Replica health

Database pool saturation

Usage pipeline drops