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Last updated: May 29, 2026

Manage Check Rules as Code

Define and manage check rules using the Dash0 Operator for Kubernetes, Dash0 Terraform provider, and Dash0 CLI for version control, workflows, and automated deployment.

Check rules are Dash0 assets that can be versioned and managed as infrastructure as code. This approach enables version control, automated deployment pipelines, consistent configuration across environments, and code review for alert changes.

Dash0 Operator for Kubernetes

Define check rules as PrometheusRule custom resources that sync to Dash0, enabling workflows and native Kubernetes management. Dash0 uses the standard Prometheus Operator format (monitoring.coreos.com/v1), allowing you to reuse existing PrometheusRule definitions without modification.

Example

In the below, the PrometheusRule CRD is used, which is an open source standard. It can be used to design both alert rules (as in the case below), and recording rules.

yaml
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apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: frontend-latency
  namespace: monitoring
  labels:
    prometheus: example     # any labels you like; used for selecting/organizing the resource
    dash0.com/dataset: production
    role: alert-rules
spec:
  groups:
    - name: Alerting
      interval: 1m
      rules:
        - alert: Frontend P99 Latency
          expr: |
            histogram_quantile(0.99,
              sum(rate({otel_metric_name="dash0.spans.duration", service_name="frontend"}[5m]))
            ) * 1000 > $__threshold
          for: 2m
          keep_firing_for: 1m
          annotations:
            # You can interpolate various values in `summary` and `description`
            summary: "Frontend P99 latency is {{ $value }}ms"
            description: "P99 latency exceeded threshold for service {{ $labels.service_name }}"


            # You need to specify threshoilds if your PromQL query in `expr` uses the `$__threshold` symbol.
            # Threshold values are specified as annotations, so they need to be YAML strings
            dash0.com/threshold-degraded: "500"
            dash0.com/threshold-critical: "500"
            ## These work as well for backwards compatibility
            # threshold-degraded: "500"
            # threshold-critical: "1000"
            # dash0-threshold-degraded: "500"
            # dash0-threshold-critical: "1000"


            # optional; "false" to disable this rule without deleting it
            dash0-enabled: "true"


            # comma-separated notification channel ids. This is equivalent
            # to linking the check rule with the notification channels as
            # you can do via the UI
            dash0.com/notification-channel-ids: ded5721c-2bf0-4a10-ab33-511fef734b0f,56aaacb2-10c6-4cef-8aeb-d7c862ad863e
          labels:
            # Plain check-rule labels. Route by adding filters on these
            # labels to the notification channels in Dash0 — not 
            # via an annotation on the rule.
            team: platform
            service: frontend
            severity: high

The Dash0 Operator for Kubernetes watches for PrometheusRule resources and syncs them to your Dash0 dataset. The dataset to which the PrometheusRule resources are synched is the same defined by the Dash0Monitoring resource in the Kubernetes namespace in which the PrometheusRule resources reside. There are also Dash0-specific annotations for thresholds (dash0-threshold-degraded, dash0-threshold-critical) and notification channels.

Apply and Manage

PrometheusRule resources are synchronized with Dash0 by the Dash0 Operator for Kubernetes provided that:

  1. You have a Dash0Monitoring resource in the same namespace as the PrometheusRule resource
  2. You did not opt-out of the synching through the synchronizePrometheusRules setting

For more information, refer to the Managing Dash0 Check Rules documentation of the Dash0 Operator for Kubernetes.

bash
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# Apply the check rule
kubectl apply -f check-rule.yaml


# List all check rules
kubectl get prometheusrules -n monitoring


# View details
kubectl describe prometheusrule frontend-latency -n monitoring


# Update the check rule
kubectl edit prometheusrule frontend-latency -n monitoring


# Delete the check rule
kubectl delete prometheusrule frontend-latency -n monitoring

Dash0 Terraform Provider

Manage check rules in your Terraform infrastructure alongside other cloud resources for unified infrastructure management.

Basic Example

Note

The Dash0 Terraform Provider supports both the PrometheusRules CRD format, as well as plain Prometheus alerting rules. But the PrometheusRules CRD format is preferred.

hcl
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terraform {
  required_providers {
    dash0 = {
      source  = "dash0hq/dash0"
      version = "~> 1.0"
    }
  }
}


provider "dash0" {
  api_token = var.dash0_api_token
  endpoint  = "https://api.dash0.com"
}


resource "dash0_check_rule" "adservice_error_rate" {
  dataset = "production"


  # Currently only one group incl. one rule is supported
  check_rule_yaml = <<-EOF
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: adservice
spec:
  groups:
    - name: Alerting
      interval: 1m0s
      rules:
        - alert: adservice
          expr: (sum by (service_namespace, service_name) (increase({otel_metric_name = "dash0.spans", service_name = "adservice", service_namespace = "opentelemetry-demo", dash0_operation_name != "", otel_span_status_code = "ERROR"}[5m]))) / (sum by (service_namespace, service_name) (increase({otel_metric_name = "dash0.spans", service_name = "adservice", service_namespace = "opentelemetry-demo", dash0_operation_name != ""}[5m])) > 0)*100 > $__threshold
          for: 0s
          keep_firing_for: 0s
          annotations:
            summary: 'High error percentage for adservice: {{$value|printf "%.2f"}}%'
            description: 'High error percentage for adservice: {{$value|printf "%.2f"}}%'
            dash0-threshold-critical: "40"
            dash0-threshold-degraded: "35"
            dash0-enabled: true
          labels: {}
EOF
}

For related information, see the Dash0 Terraform provider documentation.

Dash0 CLI

Script check rule operations with the Dash0 CLI for automated deployments and batch operations.

Note

The Dash0 CLI supports both the PrometheusRules CRD format, as well as plain Prometheus alerting rules. But the PrometheusRules CRD format is preferred.

Create from File

bash
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# Create a check rule from a YAML file
dash0 create-checks create -f check-rule.yaml --dataset <id>

List Check Rules

bash
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# List all check rules
dash0 create-checks list --dataset <id>

Get Check Rule Details

bash
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# Get a single check rule as YAML
dash0 create-checks get <id> -o yaml --dataset <id>


# Get check rule in JSON format
dash0 create-checks get <id> -o json --dataset <id>

Update Check Rule

bash
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# Update an existing check rule
dash0 create-checks update <id> -f check-rule.yaml --dataset <id>

Delete Check Rule

bash
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# Delete a check rule
dash0 create-checks delete <id> --dataset <id>

Further Reading