Your team is standardizing observability across multiple Google Cloud environments by managing Cloud Monitoring dashboards as code. You need to construct a dashboard chart widget using Prometheus Query Language (PromQL) to visualize the fraction of regional Pub/Sub publisher quota consumed across all active regions. The visualization must meet the following technical requirements: Group metrics by both quota_metric and location. Dynamically adapt calculation windows based on the dashboard user's selected time range using the ${__interval} template variable. Compare per-second rate of net usage against per-minute quota limits using the consumer_quota monitored resource. Which PromQL expression should you configure in the dashboard definition?

sum by (quota_metric, location) (rate({"__name__"="serviceruntime.googleapis.com/quota/rate/net_usage", "monitored_resource"="consumer_quota", "service"="pubsub.googleapis.com", "quota_metric"="pubsub.googleapis.com/regionalpublisher"}[${__interval}])) / (max by (quota_metric, location) (max_over_time({"__name__"="serviceruntime.googleapis.com/quota/limit", "monitored_resource"="consumer_quota", "service"="pubsub.googleapis.com", "quota_metric"="pubsub.googleapis.com/regionalpublisher"}[${__interval}])) / 60): ### What this PromQL expression is This PromQL query calculates the dynamic quota utilization ratio by comparing the consumed usage rate against the effective allocated limit for Google Cloud APIs within Cloud Monitoring. ### How it meets all requirements - **Monitored Resource and Metrics**: It correctly targets the `consumer_quota` resource type alongside the specific Google Cloud metrics `serviceruntime.googleapis.com/quota/rate/net_usage` and `serviceruntime.googleapis.com/quota/limit`. - **Rate vs. Limit Normalization**: Quota net usage is tracked as a cumulative rate metric and converted to a per-second rate using `rate()`. Because API rate limits are represented as operations per minute (60 seconds), dividing the limit by `60` aligns the denominator to per-second units. - **Grouping and Dynamic Intervals**: The query aggregates by `sum by (quota_metric, location)` and `max by (quota_metric, location)`, properly breaking down utilization per region while leveraging the dashboard template variable `${__interval}` to adjust smoothly to user zoom levels. ### Key advantages - **Prevents division by unit mismatch**: Correctly handles unit normalization between per-second consumption rates and per-minute limit descriptors. - **Dashboard variable integration**: Automatically rescales time aggregation windows based on the active viewport interval. - **Multi-region breakdown**: Isolates quota exhaustion risks per Google Cloud region. - **Dashboards-as-code compatibility**: Uses standard Cloud Monitoring PromQL mapping syntax (`__name__` and label selectors) for programmatic JSON/Terraform dashboard definitions. ### Why this is optimal This approach directly reflects the native Cloud Monitoring data model for quota monitoring, providing accurate fractional utilization values (0.0 to 1.0+) that can easily drive color thresholds, charts, and automated alerts.

Promql Pubsub Consumer Quota Utilization Dashboard | Professional Cloud DevOps Engineer

Promql Pubsub Consumer Quota Utilization Dashboard

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Your team is standardizing observability across multiple Google Cloud environments by managing Cloud Monitoring dashboards as code. You need to construct a dashboard chart widget using Prometheus Query Language (PromQL) to visualize the fraction of regional Pub/Sub publisher quota consumed across all active regions.

The visualization must meet the following technical requirements:

Group metrics by both quota_metric and location.
Dynamically adapt calculation windows based on the dashboard user's selected time range using the ${__interval} template variable.
Compare per-second rate of net usage against per-minute quota limits using the consumer_quota monitored resource.

Which PromQL expression should you configure in the dashboard definition?

sum by (quota_metric, location) (rate({"name"="serviceruntime.googleapis.com/quota/rate/net_usage", "monitored_resource"="consumer_quota", "service"="pubsub.googleapis.com", "quota_metric"="pubsub.googleapis.com/regionalpublisher"}[${__interval}])) / (max by (quota_metric, location) (max_over_time({"name"="serviceruntime.googleapis.com/quota/limit", "monitored_resource"="consumer_quota", "service"="pubsub.googleapis.com", "quota_metric"="pubsub.googleapis.com/regionalpublisher"}[${__interval}])) / 60)

sum by (quota_metric, location) (increase({"name"="pubsub.googleapis.com/subscription/sent_message_count", "monitored_resource"="pubsub_subscription"}[${__interval}])) / (max by (quota_metric, location) (max_over_time({"name"="serviceruntime.googleapis.com/quota/limit"}[${__interval}])))

sum_over_time({"name"="pubsub.googleapis.com/subscription/delivery_latency_health_score", "monitored_resource"="pubsub_subscription", "subscription_id"="$SUBSCRIPTION"}[${__interval}]) > 0.8

avg(rate({"name"="kubernetes.io/anthos/container/cpu/core_usage_time", "monitored_resource"="k8s_container"}[1h])) by (location, quota_metric) / 60

Professional Cloud DevOps Engineer

Promql Pubsub Consumer Quota Utilization Dashboard

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