Metric Filter

Metric filter policies control which metrics pass through Edge. Use them to drop noisy metrics and cut cardinality costs.

Basic Structure

{
  "id": "policy-id",
  "name": "Human-readable name",
  "metric": {
    "match": [...],
    "keep": true
  }
}

Every metric policy has:

match: One or more matchers that identify target metrics
keep: Boolean (true to keep, false to drop)

Unlike log policies, metric policies don’t support percentage sampling or rate limiting. The keep value is a simple boolean.

Matchers

Matchers identify which metrics a policy applies to. When a policy has multiple matchers, all must match (AND logic).

Metric Fields

Match on well-known metric fields:

Field	Description
`name`	The metric name
`description`	Metric description
`unit`	Metric unit (e.g., `ms`, `bytes`, `1`)
`scope_name`	Instrumentation scope name
`scope_version`	Instrumentation scope version

{
  "id": "match-cpu-metrics",
  "name": "Match system CPU metrics",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^system\\.cpu\\."
      }
    ],
    "keep": false
  }
}

Metric Type

Match on metric type:

Type	Description
`METRIC_TYPE_GAUGE`	Instantaneous measurement
`METRIC_TYPE_SUM`	Cumulative or delta sum
`METRIC_TYPE_HISTOGRAM`	Distribution of values
`METRIC_TYPE_EXPONENTIAL_HISTOGRAM`	Exponential bucket histogram
`METRIC_TYPE_SUMMARY`	Pre-calculated quantiles

{
  "id": "match-histograms",
  "name": "Match histogram metrics",
  "metric": {
    "match": [
      {
        "metric_type": "METRIC_TYPE_HISTOGRAM"
      }
    ],
    "keep": false
  }
}

Aggregation Temporality

Match on how metrics report aggregated values:

Temporality	Description
`AGGREGATION_TEMPORALITY_DELTA`	Reports change since last report
`AGGREGATION_TEMPORALITY_CUMULATIVE`	Reports total since start

{
  "id": "match-delta-metrics",
  "name": "Match delta temporality metrics",
  "metric": {
    "match": [
      {
        "aggregation_temporality": "AGGREGATION_TEMPORALITY_DELTA"
      }
    ],
    "keep": true
  }
}

Datapoint Attributes

Match on data point attributes (dimensions/labels):

{
  "id": "match-prod-web-01",
  "name": "Match metrics from prod-web-01",
  "metric": {
    "match": [
      {
        "datapoint_attribute": "host.name",
        "exact": "prod-web-01"
      }
    ],
    "keep": true
  }
}

Resource Attributes

Match on resource attributes:

{
  "id": "match-api-gateway",
  "name": "Match api-gateway service metrics",
  "metric": {
    "match": [
      {
        "resource_attribute": "service.name",
        "exact": "api-gateway"
      }
    ],
    "keep": true
  }
}

Scope Attributes

Match on instrumentation scope attributes:

{
  "id": "match-otel-go",
  "name": "Match OpenTelemetry Go metrics",
  "metric": {
    "match": [
      {
        "scope_attribute": "library.name",
        "exact": "opentelemetry-go"
      }
    ],
    "keep": true
  }
}

Match Types

Exact Match

Match the exact string value:

{
  "id": "match-request-duration",
  "name": "Match HTTP request duration metric",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "exact": "http.request.duration"
      }
    ],
    "keep": true
  }
}

Regex Match

Match using RE2 regular expressions:

{
  "id": "drop-debug-metrics",
  "name": "Drop debug-prefixed metrics",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^debug\\."
      }
    ],
    "keep": false
  }
}

Exists Match

Match on field presence:

{
  "id": "match-internal-flag",
  "name": "Match metrics with internal attribute",
  "metric": {
    "match": [
      {
        "datapoint_attribute": "internal",
        "exists": true
      }
    ],
    "keep": false
  }
}

Negation

Invert any match with negate:

{
  "id": "drop-non-system-metrics",
  "name": "Drop metrics not starting with system",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^system\\.",
        "negate": true
      }
    ],
    "keep": false
  }
}

Policy Precedence

When multiple policies match the same metric, keep: false takes precedence over keep: true.

Examples

Drop Debug Metrics

{
  "id": "drop-debug-metrics",
  "name": "Drop debug-prefixed metrics",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^debug\\."
      }
    ],
    "keep": false
  }
}

Drop System Load Metrics

{
  "id": "drop-system-load",
  "name": "Drop system load metrics",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^system\\.load"
      }
    ],
    "keep": false
  }
}

Drop Histogram Metrics

{
  "id": "drop-histograms",
  "name": "Drop all histogram metrics",
  "metric": {
    "match": [
      {
        "metric_type": "METRIC_TYPE_HISTOGRAM"
      }
    ],
    "keep": false
  }
}

Drop by Datapoint Attribute

{
  "id": "drop-internal-metrics",
  "name": "Drop metrics with internal flag",
  "metric": {
    "match": [
      {
        "datapoint_attribute": "internal",
        "exists": true
      }
    ],
    "keep": false
  }
}

Drop by Service

{
  "id": "drop-test-service-metrics",
  "name": "Drop metrics from test services",
  "metric": {
    "match": [
      {
        "resource_attribute": "service.name",
        "regex": "^test-"
      }
    ],
    "keep": false
  }
}

Drop High-Cardinality Metrics

{
  "id": "drop-per-request-metrics",
  "name": "Drop per-request ID metrics",
  "metric": {
    "match": [
      {
        "datapoint_attribute": "request.id",
        "exists": true
      }
    ],
    "keep": false
  }
}

Keep Only Specific Metrics

Using negation to drop everything except what you want:

{
  "id": "keep-only-business-metrics",
  "name": "Drop non-business metrics",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^business\\.",
        "negate": true
      }
    ],
    "keep": false
  }
}

Combined Conditions

{
  "id": "drop-noisy-api-metrics",
  "name": "Drop high-frequency API metrics from non-prod",
  "metric": {
    "match": [
      {
        "metric_field": "name",
        "regex": "^http\\."
      },
      {
        "resource_attribute": "deployment.environment",
        "exact": "production",
        "negate": true
      }
    ],
    "keep": false
  }
}

Common Use Cases

Cost Reduction

Drop metrics you don’t query:

Debug and internal metrics
Per-request ID dimensions (high cardinality)
Redundant system metrics
Metrics from test/dev environments

Cardinality Control

High-cardinality metrics (many unique label combinations) are expensive. Drop metrics with:

Unique request IDs as labels
User IDs as labels
Timestamps as labels
Unbounded string values as labels

Compliance

Drop metrics that might contain sensitive information:

Metrics with PII in labels
Metrics from sensitive services
Internal topology information

Best Practices

Start with observability: Know what you’re dropping before you drop it
Use exact matches when possible: Faster than regex
Target high-volume metrics: Focus on metrics that cost the most
Be careful with negation: It makes it easy to drop metrics you meant to keep
Test in staging: Verify policies before production deployment

Introduction

Architecture

Distributions

How-to guides

Edge Reference

Policy Reference

Source

Basic Structure

Matchers

Metric Fields

Metric Type

Aggregation Temporality

Datapoint Attributes

Resource Attributes

Scope Attributes

Match Types

Exact Match

Regex Match

Exists Match

Negation

Policy Precedence

Examples

Drop Debug Metrics

Drop System Load Metrics

Drop Histogram Metrics

Drop by Datapoint Attribute

Drop by Service

Drop High-Cardinality Metrics

Keep Only Specific Metrics

Combined Conditions

Common Use Cases

Cost Reduction

Cardinality Control

Compliance

Best Practices

Next Steps

Log Filter

Log Transform

​Basic Structure

​Matchers

​Metric Fields

​Metric Type

​Aggregation Temporality

​Datapoint Attributes

​Resource Attributes

​Scope Attributes

​Match Types

​Exact Match

​Regex Match

​Exists Match

​Negation

​Policy Precedence

​Examples

​Drop Debug Metrics

​Drop System Load Metrics

​Drop Histogram Metrics

​Drop by Datapoint Attribute

​Drop by Service

​Drop High-Cardinality Metrics

​Keep Only Specific Metrics

​Combined Conditions

​Common Use Cases

​Cost Reduction

​Cardinality Control

​Compliance

​Best Practices

​Next Steps

Log Filter

Log Transform

Basic Structure

Matchers

Metric Fields

Metric Type

Aggregation Temporality

Datapoint Attributes

Resource Attributes

Scope Attributes

Match Types

Exact Match

Regex Match

Exists Match

Negation

Policy Precedence

Examples

Drop Debug Metrics

Drop System Load Metrics

Drop Histogram Metrics

Drop by Datapoint Attribute

Drop by Service

Drop High-Cardinality Metrics

Keep Only Specific Metrics

Combined Conditions

Common Use Cases

Cost Reduction

Cardinality Control

Compliance

Best Practices

Next Steps