Metricsql

MetricsQL

VictoriaMetrics PromQL superset. Syntactically backwards-compatible; semantically different for a subset of queries. Lead with the diffs — that's where users get burned. PromQL fundamentals live in the sibling promql skill; this covers only what PromQL doesn't.

References

• Behavioral diffs from PromQL — [${CLAUDE_SKILL_DIR}/references/behavioral-diffs.md] rate/increase/delta/changes diffs, _prometheus-suffixed variants, scalar/instant-vector unification, NaN handling, name retention, implicit conversions, auto-aligned subqueries, default_rollup lookback, staleness markers.
• MetricsQL-only extensions — [${CLAUDE_SKILL_DIR}/references/extensions.md] Rollup family, WITH templates, multiple-or filters, default/if/ifnot ops, group_left(*) prefix, keep_metric_names, [Ni] step, numeric suffixes, aggregate limit N, boundsLabel, fractional durations, Graphite, multi-line.
• Full function catalog — [${CLAUDE_SKILL_DIR}/references/functions-catalog.md] All rollup, transform, label-manipulation, aggregate functions by category, with PromQL/MetricsQL provenance.
• Query API enhancements — [${CLAUDE_SKILL_DIR}/references/api-enhancements.md] extra_label, extra_filters[], round_digits, limit, timestamp formats, stats response, cluster vmselect URL layout, multi-tenancy.

Read the relevant reference before proceeding.

What MetricsQL Is

• Strict syntactic superset of PromQL — every valid PromQL parses as MetricsQL.
• Not semantic superset — rate, increase, delta, changes differ.
• _prometheus-suffixed variants give byte-parity: rate_prometheus, increase_prometheus, delta_prometheus, changes_prometheus.
• Implemented by vmselect (cluster) or single-node binary; exposed via standard /api/v1/query and /api/v1/query_range.

The Five Behavioral Diffs That Bite

1. Lookbehind anchor. rate/increase use the last sample before the window for the first delta; Prometheus doesn't. For increase(metric[$__interval]) on a slow counter, Prometheus loses one delta per window. Use rate_prometheus/increase_prometheus for parity.
2. No extrapolation. Returns actual measured delta; Prometheus extrapolates to window edges, producing fractional results from integer counters. Affects alerts comparing increase() to integer thresholds.
3. Scalar = instant vector without labels. Prometheus's scalar/instant-vector distinction collapses. scalar(metric) coercion rarely needed; arithmetic on aggregation results works.
4. NaN drop. (-1)^0.5 returns empty in MetricsQL; Prometheus returns a NaN series. Grafana renders identically; programmatic consumers see different shapes.
5. Metric names retained for safe functions. min_over_time(foo), round(foo), abs(foo) keep foo. Prometheus strips.

Full mechanics, edge cases, implicit-conversion pipeline, per-function table: [${CLAUDE_SKILL_DIR}/references/behavioral-diffs.md].

Lookbehind Window — Auto-Selection

Omitting [d] is allowed:

• default_rollup and rate: max(step, scrape_interval) — prevents gaps when step < scrape_interval.
• All other rollups: step ($__interval in Grafana, 1i).
• rate(node_network_receive_bytes_total) ≡ rate(node_network_receive_bytes_total[$__interval]).

Silent behavior change across panels with different steps. For alerting and recording rules, always specify the window explicitly.

Implicit Query Conversions

VictoriaMetrics rewrites every query before evaluation (unless -search.disableImplicitConversion):

• Bare selectors → default_rollup: foo → default_rollup(foo).
• Selectors inside transform/aggregate get the same wrap: abs(temperature) → abs(default_rollup(temperature)), count(up) → count(default_rollup(up)).
• Rollups on non-selectors become subqueries: rate(sum(up)) → rate((sum(default_rollup(up)))[1i:1i]).
• Subqueries with missing step get 1i: avg_over_time(rate(m[5m])[1h]) → avg_over_time(rate(m[5m])[1h:1i]).

When debugging, mentally apply these first — the actual computation may differ from what was typed.

Full conversion list with disable flags: [${CLAUDE_SKILL_DIR}/references/behavioral-diffs.md].

The Rollup Family — MetricsQL-Only

• rollup(m[d]) — min/max/avg with rollup="..." label.
• rollup_rate(m[d]) — per-second rate min/max/avg over adjacent samples; better than irate for spike detection.
• rollup_increase(m[d]) / rollup_delta(m[d]) / rollup_deriv(m[d]) — same pattern.
• rollup_candlestick(m[d]) — OHLC.
• aggr_over_time(("func1","func2",...), m[d]) — multiple rollups in one pass.

Pair with keep_metric_names to preserve the original name.

keep_metric_names

Functions and binary ops strip the metric name. This causes duplicate time series errors when distinct names collapse into the same label set. Suffix with keep_metric_names:

• rate({__name__=~"foo|bar"}) keep_metric_names
• ({__name__=~"foo|bar"} / 10) keep_metric_names

Available on all rollups, transforms, and binary operators.

Multiple or in Series Selectors

PromQL {env="prod",job="a"} is a single AND. MetricsQL adds top-level disjunction:

{env="prod",job="a" or env="dev",job="b"}

Each or-group is an AND of matchers. Compose with comma within a group.

Multi-constant matching: status_code == (300, 301, 304) returns series where status_code is any listed value.

WITH Templates

Reusable named subexpressions:

WITH (
  errs = rate(http_requests_total{status=~"5.."}[5m]),
  total = rate(http_requests_total[5m]),
)
sum(errs) by (job) / sum(total) by (job)

String concat: WITH (commonPrefix="my_app_") {__name__=commonPrefix+"errors_total"}. Expanded at parse time.

Binary Operators Beyond PromQL

• q1 default q2 — fills gaps in q1 from q2.
• q1 if q2 — keeps q1 where q2 has a value (conditional masking).
• q1 ifnot q2 — keeps q1 where q2 has no value (inverse).

Compose with default-on-missing: (up{job="x"} default 0) == 0 reliably alerts on disappearing targets.

group_left(*) and Label Copy

kube_pod_info * on(namespace) group_left(*) prefix "ns_" kube_namespace_labels

Copies all labels from right side except those in on(...), prefixed with ns_. group_right(*) mirrors. Without prefix, collisions error.

Aggregate limit N

sum(http_requests_total) by (path) limit 10

Returns 10 paths total. Other series dropped silently. Distinct from topk(10, ...): limit N is order-arbitrary; topk keeps the top by value.

Grafana $__interval and [Ni] Syntax

• 1i = one step (Grafana step arg).
• [10i] = lookbehind covering ten steps.
• offset 5i = shift back five steps.
• Works in rollup windows, offsets, subquery step: rate(metric[10i] offset 5i).
• Use over hard-coded durations so panels scale with the time range.

Cluster Endpoint Structure

http://<vmselect>:8481/select/<accountID>/prometheus/api/v1/query
http://<vmselect>:8481/select/<accountID>/prometheus/api/v1/query_range

<accountID> is accountID or accountID:projectID (32-bit ints). Single-node uses unprefixed /api/v1/query. /prometheus/ prefix is optional but explicit.

Full URL layout (ingestion, federation, Graphite, vmstorage admin, vmalert proxy): [${CLAUDE_SKILL_DIR}/references/api-enhancements.md].

Query API Enhancements

• extra_label=<name>=<value> — adds {name="value"} to every selector. Repeatable. Used by auth proxies for tenant scoping.
• extra_filters[]=<selector> — adds a full selector with regex support: extra_filters[]={env=~"prod|staging"}.
• round_digits=N — rounds response values to N decimals.
• limit=N on /api/v1/labels, /api/v1/label/<name>/values, /api/v1/series.

Responses include stats with executionTimeMsec and seriesFetched. seriesFetched is approximate; vmalert uses it to flag never-firing rules.

Syntax Conveniences

• Underscore in numbers — 1_234_567_890 ≡ 1234567890
• Numeric suffixes — 8K (8000), 1.2Mi (1.2×1024²), supports K Ki M Mi G Gi T Ti
• Fractional durations — [1.5m], offset 0.5d
• Optional duration suffix — [300] is seconds: rate(m[300] offset 1800) ≡ rate(m[5m]) offset 30m
• Duration anywhere — sum_over_time(m[1h]) / 1h ≡ sum_over_time(m[1h]) / 3600
• Trailing commas — m{foo="bar",}, f(a, b,), WITH (x=y,) x all valid. Use in multi-line queries.
• Unicode in names — ტემპერატურა{πόλη="Київ"} is valid
• Escape sequences — foo\-bar{baz\=aa="b"}, \xXX, \uXXXX
• @ modifier anywhere — sum(foo) @ end(), foo @ (end() - 1h)

Histogram Extensions

histogram_quantile(phi, buckets, boundsLabel?) — optional third arg returns lower/upper bounds in boundsLabel. For plotting quantile confidence intervals.

histogram_over_time(gauge[d]) produces VictoriaMetrics-format histograms from gauge values:

histogram_quantile(0.5, sum(histogram_over_time(temperature[24h])) by (vmrange,country))

Computes quantiles over gauge distributions without re-instrumenting.

Application

When writing:

• Omit lookbehind only when panel-wide $__interval is appropriate. Otherwise use [5m] or [Ni] explicitly.
• For alerting/recording rules: always specify the lookbehind window. Implicit selection couples rule behavior to evaluation interval.
• Prefer default over or vector(0) — more readable, handles labels correctly.
• Use rollup_rate for counter spike detection over irate — min/max/avg in one query.

When migrating from Prometheus:

• Audit alerts comparing increase() to integer thresholds — exact integers may fire differently.
• Use *_prometheus variants only when byte-parity is required (cross-backend SLO consistency).
• Enable -search.logImplicitConversion to see rewrites.

When reviewing:

• Flag missing lookbehind windows in alerting/recording rules.
• Flag rate(sum(...)) — silent subquery formation.
• Flag bare selectors in arithmetic — silent default_rollup wrap.
• Cite the specific diff and show the fix inline.

Integration

promql — shared fundamentals (selectors, operators, aggregations, vector matching). This skill — MetricsQL extensions and diffs.

prometheus — instrumentation; this skill — query-time behavior.