query-metrics

작성자: axiomhq

스크립트를 통해 Axiom MetricsDB에 메트릭 쿼리를 실행합니다. 사용 가능한 메트릭, 태그 및 태그 값을 탐색합니다. 메트릭 쿼리, 메트릭 탐색 등을 요청받았을 때 사용하세요.

npx skills add https://github.com/axiomhq/skills --skill query-metrics

Querying Axiom Metrics

All script paths are relative to this skill's folder; invoke as scripts/<name>. The target dataset must be of kind otel:metrics:v1.

Setup, prerequisites, and ~/.axiom.toml configuration: see README.md. Edge-deployment routing is automatic — the scripts read each dataset's edgeDeployment and route to the right regional endpoint without configuration.

Workflow

  1. scripts/datasets <deploy> --kind otel:metrics:v1 — list metrics datasets.
  2. scripts/metrics-specrequired before composing any query. MPL evolves; the spec is the source of truth. Also use it to answer general MPL/metrics questions.
  3. scripts/metrics-info <deploy> <dataset> metrics — list metrics with {type, temporality, unit} metadata. Read this before writing the query (see Choosing a Query Shape).
  4. scripts/metrics-info <deploy> <dataset> tags [<tag> values] — explore filter dimensions.
  5. scripts/metrics-query <deploy> '<MPL>' <start> <end> — execute. Iterate.

If the user names a specific entity (service, host, …), scripts/metrics-info <deploy> <dataset> find-metrics "<value>" finds the metrics carrying it. find-metrics searches tag values, not metric names — don't use it for general discovery.

Choosing a Query Shape

The metrics-info listing returns each metric's {type, temporality, unit}. Read these before composing — never assume a metric is a simple scalar.

FieldValuesDrives
typeGauge, CounterMonotonic, CounterNonMonotonic, HistogramRequired pre-aggregation operators.
temporalityCumulative, Delta, nullWhether counter values are running totals or per-interval deltas. null is normal for Gauges.
unitUCUM string (Cel, kW.h, s, %, [ppm], …) or nullDisplay unit; preserve when reporting results.

Rules per type (consult metrics-spec for exact operator names — they evolve):

  • Gauge — instantaneous value. Align directly with avg/min/max/sum. Don't apply a rate; you'd be averaging meaningless deltas of an instantaneous value.
  • CounterMonotonic + Cumulative — running total (resets aside). The raw values are rarely what you want. Convert to a per-second rate first, then align/aggregate.
  • CounterMonotonic + Delta — already per-interval. Sum/align without a rate step.
  • CounterNonMonotonic — can go up or down (queue depth, balance). Intent is ambiguous: rate, delta, or current value all make sense for different questions. Ask the user before picking one.
  • Histogram — not a scalar. align using avg produces nonsense. Use bucket … using with the histogram functions from metrics-spec; quantiles are float specs to those functions, and temporality selects the variant (Cumulative vs Delta interpolation). Consult metrics-spec for the exact signatures.
  • temporality: null — "not applicable for this instrument type" (the norm for Gauges), not "missing data".

When surfacing numbers, attach the unit (treat null as unitless). If you combine metrics with mismatched units in arithmetic, warn rather than silently producing a meaningless number.

Query Metrics

scripts/metrics-query [-w pixels] [--pixel-per-point n] <deploy> '<MPL>' <start> <end>
ParameterNotes
deployName from ~/.axiom.toml (e.g. prod).
MPLPipeline string. Dataset is parsed from the MPL itself.
start / endRFC3339 (2025-01-01T00:00:00Z) or relative (now-1h, now).
-w / --chart-width <px>Optional. Target chart width in pixels; lets the server resolve $__interval.
--pixel-per-point <n>Optional. Pixels per point (server default 10); with -w sets the bucket count.

Always single-quote the MPL string in the shell. MPL is full of backticks; inside double quotes the shell executes them as command substitution, silently mangling the query (or running whatever the identifier names).

Bound the output before grouping. group by <tag> returns one series per tag value with no cap — on a high-cardinality tag this floods the output. Check cardinality first (describe, or tags <tag> values) and prefer plain group using <agg> while exploring.

Examples:

scripts/metrics-query prod -w 1200 \
  '`my-dataset`:`http.server.duration` | align to $__interval using avg' \
  now-1h now

scripts/metrics-query prod -w 1200 \
  '`my-dataset`:`http.server.duration`
   | where `service.name` == "frontend" and method == "GET"
   | align to $__interval using avg
   | group by status_code using sum' \
  now-1d now

Adaptive resolution ($__interval)

Hardcoding a step (align to 5m) makes charts look wrong at other zoom levels — too sparse zoomed in, too dense zoomed out. Prefer the system parameter $__interval wherever a Duration is expected, and pass the chart width so the server picks the step:

scripts/metrics-query prod -w 1200 \
  '`my-dataset`:`http.server.duration` | align to $__interval using avg' \
  now-7d now

The metrics service computes $__interval from the query's time range and the target chart width, then snaps it up to a nice resolution from the ladder 1s, 5s, 10s, 15s, 30s, 1m, 5m, 10m, 15m, 30m, 1h, 12h, 1d, 1w, 1M, 1Y. It never drops below a metric's stored resolution.

  • No declaration needed — the server auto-registers $__interval; do not add param $__interval: Duration; (the edge forwards the query verbatim and the metrics service injects the parameter).
  • Bucket countchart-width / pixel-per-point (pixel-per-point default 10). Omit -w and the server targets ~500 buckets.
  • Works anywhere a Duration is valid, e.g. bucket to $__interval using histogram(0.5, 0.95).
  • Set -w to your render width (e.g. the metrics-chart skill's plot width) so one bucket ≈ one pixel column. The value is forwarded under the request body's queryOptions (chart-width, pixel-per-point).

Parameters

MPL can declare parameters (param $svc: string;). Pass values with repeated -p name=value. The script applies the API's param__ prefix; values are forwarded verbatim as MPL literals (string literals include their quotes).

scripts/metrics-query \
  -p svc='"frontend"' \
  -p window='5m' \
  prod \
  'param $svc: string; param $window: Duration;
   `otel-metrics`:`http.server.duration` | where `service.name` == $svc | align to $window using avg' \
  now-1h now

Required parameters must be supplied; optional ones may be omitted. Resulting request body shape:

{
  "apl": "param $svc: string; …",
  "startTime": "now-1h",
  "endTime": "now",
  "params": { "param__svc": "\"frontend\"", "param__window": "5m" }
}

Literal syntax per type lives in metrics-spec.

Discovery (metrics-info)

Time range defaults to the last 24h; override with --start / --end. Both accept RFC3339 (offsets allowed) or relative now / now-<N><unit> with <unit> in s m h d w, resolved to RFC3339 UTC client-side. This is narrower than metrics-query, which forwards times to the server unparsed and so also accepts forms like now-1y; in metrics-info anything outside now / now-<N>[smhdw] must already be RFC3339 or the request 400s.

CommandReturns
metrics-info <d> <ds> metricsAll metrics, keyed by name, with {type, temporality, unit}.
metrics-info <d> <ds> metrics --by-typeSame listing grouped by type (client-side reshape).
metrics-info <d> <ds> metrics --type Gauge --type HistogramFiltered listing (repeatable, OR semantics; composes with --by-type).
metrics-info <d> <ds> metrics <metric> infoSingle metric's {type, temporality, unit}. Non-zero exit if absent.
metrics-info <d> <ds> metrics <metric> describeBundle: metadata + all tags + tag values in one call (replaces 1+1+N round trips). Flags: --no-values (tag names only), --values-limit N (cap per-tag values; default 50, 0 = unlimited).
metrics-info <d> <ds> metrics <metric> tagsTags carried by a specific metric.
metrics-info <d> <ds> metrics <metric> tags <tag> valuesTag values for that metric.
metrics-info <d> <ds> metrics <metric> tags <tag> typeProbe whether the tag is int/float/string/bool. Returns {type, present_types}; mixed if multiple types coexist, absent if not present.
metrics-info <d> <ds> tagsAll tags in the dataset.
metrics-info <d> <ds> tags <tag> valuesAll values for a tag (across metrics).
metrics-info <d> <ds> find-metrics "<value>"Metrics that carry the given tag value (not metric name).

Error Handling

HTTP errors return JSON with code and message; some include a detail object:

{"code": 400, "message": "MPL syntax error: …"}

Syntax errors (400) include an annotated source pointer listing the valid operators at the failure position — read it, it usually names the fix.

CodeCause
400Invalid query syntax or bad dataset name
401Missing/invalid auth
403No permission
404Dataset not found
429Rate limited — back off and retry; don't tight-loop
500Internal error

Requests time out client-side after 120s (AXIOM_MAX_TIME to override; AXIOM_CONNECT_TIMEOUT for the 10s connect timeout).

On 500, re-run with curl -v to capture the traceparent / x-axiom-trace-id header and report it — the trace ID is what the backend team needs to debug.

Scripts

ScriptUsage
scripts/setupCheck requirements and config.
scripts/datasets <deploy> [--kind <kind>]List datasets with edge deployment.
scripts/metrics-specFetch the MPL query spec.
scripts/metrics-query [-w px] [--pixel-per-point n] <deploy> <mpl> <start> <end>Execute a query; use $__interval + -w for adaptive resolution.
scripts/metrics-info <deploy> <dataset> ...Discover metrics, tags, values.
scripts/axiom-api <deploy> <method> <path> [body]Low-level API calls.
scripts/resolve-url <deploy> <dataset>Resolve to the edge deployment URL.

Run any script without arguments for full usage.

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