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+---
+title: "Rule evaluations via query frontend"
+linkTitle: "Rule evaluations via query frontend"
+weight: 10
+slug: rule-evalutions-via-query-frontend
+---
+
+This guide explains how to configure the Ruler to evaluate rules via Query Frontends instead of the Ingester/Store Gateway and the pros and cons of rule evaluation via Query Frontend.
+
+## How to enable
+
+By default, the Ruler queries both Ingesters and Store Gateway depending on the Rule time range for evaluating rules (alerting rules or recording rules). If you have set `-ruler.frontend-address` then the Ruler queries the Query Frontend for evaluation rules.
+The address should be the gRPC listen address in host:port format.
+
+
+You can configure via args:
+```
+-ruler.frontend-address=query-frontend.svc.cluster.local:9095
+```
+And via yaml:
+```yaml
+ruler:
+  frontend_address: query-frontend.svc.cluster.local:9095
+```
+
+In addition, you can configure gRPC client (Ruler -> Query Frontend) config, please refer to frontend_client section in [ruler config](../configuration/config-file-reference.md#ruler_config).
+
+## Configure query response format
+You can configure the query response format via `-ruler.query-response-format`, it is used to retrieve query results from the Query Frontend.
+The supported values are `protobuf` and `json`. We recommend using `protobuf`(default) because the retrieved query results containing native histograms are only supported on `protobuf`.
+
+
+## Pros and Cons
+If this feature is enabled, the query execute path is as follows:
+
+Ruler -> Query Frontend -> Query Scheduler -> Querier -> Ingester/Store Gateway
+
+There are pros and cons regarding query performance as more hops than before (Ruler -> Ingester/Store Gateway).
+### Pros
+- The rule evaluation performance could be improved in such a situation where the number of Queriers pulling queries from the Query Scheduler is good enough.
+If then, the queries in Query Scheduler are fetched in a reasonable time (i.e. a lot of hops are not a defect for query performance). In this environment, query performance could be improved as we can use Query Frontend features like the vertical query sharding.
+- The Ruler can use fewer resources as it doesn't need to run a query engine to evaluate rules.
+
+### Cons
+- If there are not enough Queriers, adding rule queries to Query Scheduler could cause query starvation problem (queries in Query Scheduler could not be fetched in a reasonable time), so rules cannot be evaluated in time.
+
+You can utilize the `cortex_prometheus_rule_evaluation_duration_seconds` metric whether to use `-ruler.frontend-address`.
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