Wakey Metrics Recipes

Use Grafana Explore with your Prometheus-compatible data source and the Code query editor. These recipes assume standard OTLP-to-Prometheus name conversion. Discover your actual series first:

count by (__name__, job) ({__name__=~"wakey[._].*"})

With Alloy's Prometheus exporter, service names normally become job, and agent instance IDs become instance. Inspect the returned labels before adding filters. For example, append {job="wakey-agent"} to a metric selector only if that is the job value you actually see. Metrics export every 30 seconds; use a time range that includes recent activity and allow at least two exports for rate queries.

The Three Types

Type	What it records	How to read it
Counter	Cumulative events or bytes since process startup	`rate` for per-second throughput; `increase` for a window's estimated total
UpDownCounter	Adds and subtracts from a current quantity	Read the current value directly; do not use `rate` for active sessions
Histogram	Distribution of individual measurements	`_sum / _count` for an average; `_bucket` for estimated percentiles

Counter resets on restart are handled by rate and increase. Apply those functions before summing across instances so individual resets remain visible.

Operations

Completed attempts per second, including errors and timeouts:

sum by (job, operation, outcome) (rate(wakey_operations_total[5m]))

Estimated attempts over the last hour:

sum by (job, operation, outcome) (increase(wakey_operations_total[1h]))

Average duration over the last five minutes:

sum by (job, operation) (rate(wakey_operation_duration_seconds_sum[5m]))
/
sum by (job, operation) (rate(wakey_operation_duration_seconds_count[5m]))

Set Grafana's unit to seconds. This is a weighted average, not an average of instance averages. Both successful and unsuccessful attempts are included; add outcome="ok" to both selectors for successful attempts only.

Estimated p95 duration:

histogram_quantile(
  0.95,
  sum by (le, job, operation) (
    rate(wakey_operation_duration_seconds_bucket[5m])
  )
)

This needs classic histogram bucket series. Keep le in the grouping: it is the bucket boundary, in seconds. p95 is an estimate from those boundaries, not an exact sort of recorded durations. Few operations make percentiles noisy.

CC relay duration includes waiting for the agent; agent execution duration measures its dispatch separately. Do not sum both and call that user latency.

Terminals

Active PTY workers by agent, including detached sessions:

sum by (job, instance) (wakey_terminal_active)

Read this directly as a count. It is not a count of browser tabs or attachments.

PTY output bytes per second:

sum by (job, instance) (rate(wakey_terminal_output_bytes_total[5m]))

Input bytes per second:

sum by (job, instance) (rate(wakey_terminal_input_bytes_total[5m]))

Set the unit to bytes/sec. Output is measured at the PTY read, even while detached; it is not WebSocket wire traffic or confirmed browser delivery.

Relay queue-full encounters over the last fifteen minutes:

sum by (job, instance) (increase(wakey_terminal_backpressure_total[15m]))

This counts encounters, not their duration and not dropped chunks. A burst of image output can raise it while output still arrives intact through backpressure.

Average duration of completed backpressure episodes, in seconds:

sum by (job, instance, outcome) (
  rate(wakey_operation_duration_seconds_sum{operation="terminal_backpressure_wait"}[5m])
)
/
sum by (job, instance, outcome) (
  rate(wakey_operation_duration_seconds_count{operation="terminal_backpressure_wait"}[5m])
)

An episode starts when the output channel is full and ends when the pending backlog drains or the relay disconnects. It is not per-frame network latency; unfinished episodes do not appear until they end. Keep the outcome grouping so disconnected episodes are not confused with successfully drained ones.

Snapshots

Device entries in successfully sent snapshots over the last hour:

sum by (job, instance) (increase(wakey_snapshot_devices_total[1h]))

Repeated snapshots count the same devices again. This is collection volume, not unique devices, current fleet size, or confirmed CC persistence.

Empty or Strange Results

No series: generate the relevant activity, wait for export, and check the metrics pipeline.
Different names: use the discovery query; collector translation can change suffixes and labels.
NaN average: no operations occurred in the window, so the denominator is zero. Show a gap, not a fake zero latency.
Empty rate: it needs multiple samples. Try a longer window and check the time range.
Fractional increase: Prometheus extrapolates to the window boundaries; event counts can therefore appear fractional.
Stale active count: the last exported value is not an immediate liveness check after a crash or network loss.
No instance label: CC does not currently set a service instance ID; agent telemetry does.

5.4 KiB Raw Blame History