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obz-vm

VictoriaMetrics provider for obz. Covers all 6 metric commands (query, list, info, labels, label-values, series) using MetricsQL, a PromQL superset with extensions like keep_metric_names and range_normalize. This skill should be used when the user mentions "VictoriaMetrics", "MetricsQL", "obz metric -p vm", or needs to query metrics from a VM backend.

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安装前可以查看交给 AI 代理的指令内容。

obz-vm: VictoriaMetrics Provider

Quick Reference

FieldValue
Aliasesvm, victoriametrics
SignalMetric
Query languageMetricsQL (PromQL superset)
AuthBearer token, Basic auth, or none
Provider flagsNone
Supported cmdsquery, list, info, labels, label-values, series

Supported Commands

All six core metric commands work with this provider:

obz metric query        # Run an instant or range MetricsQL query
obz metric list         # List available metric names
obz metric info         # Show metadata for a specific metric
obz metric labels       # List all known label names
obz metric label-values # List values for a given label
obz metric series       # List matching time series

Authentication

Configure auth in config.yaml under providers.<name>.auth. Supports bearer token, basic auth, or no auth.

# config.yaml
providers:
  vm:
    endpoint: http://localhost:8428
    auth:
      token: ${env:VM_TOKEN}

Then query with just -p:

obz metric query -p vm -q 'up'

MetricsQL Guide

MetricsQL is fully compatible with PromQL and adds useful extensions.

Standard PromQL (works as-is)

rate(http_requests_total[5m])
sum by (job) (up)
histogram_quantile(0.99, rate(http_duration_seconds_bucket[5m]))

MetricsQL Extensions

keep_metric_names preserves the original metric name through functions that normally drop it:

rate(http_requests_total[5m]) keep_metric_names

label_set adds or overrides labels in results:

label_set(up, "env", "production")

range_normalize scales values to a 0..1 range across the time window:

range_normalize(cpu_usage_percent)

default fills gaps with a fallback value:

absent_over_time(up[5m]) default 0

Day/week suffixes: MetricsQL supports d for days and w for weeks, which standard PromQL doesn't:

avg_over_time(cpu_idle[7d])

Subquery shorthand with trailing [range:step]:

max_over_time(rate(errors_total[5m])[1h:1m])

Common Pitfalls

  • MetricsQL auto-aligns [range] to the query step. If you see unexpected smoothing, set an explicit step with --step.
  • keep_metric_names only works on functions returning a single series per input series. Aggregations like sum() ignore it.
  • Label filters are case-sensitive. {job="API"} won't match job="api".

Examples

Instant query:

obz metric query -p vm -q 'rate(http_requests_total[5m])' --from now-1h

Range query, 5m step:

obz metric query -p vm -q 'avg by (instance) (node_cpu_seconds_total)' \
  --from now-1d --to now --step 5m

List metric names matching a prefix:

obz metric list -p vm --match 'http_*'

Get metadata for a metric:

obz metric info -p vm http_requests_total

List all label names:

obz metric labels -p vm

List values of a specific label:

obz metric label-values -p vm job

Find series matching a selector:

obz metric series -p vm --match '{job="api", env="prod"}'

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