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Knative Eventing metrics - Administrator metrics | Observability | Red Hat OpenShift Serverless 1.33
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Knative Eventing metrics

Cluster administrators can view the following metrics for Knative Eventing components.

By aggregating the metrics from HTTP code, events can be separated into two categories; successful events (2xx) and failed events (5xx).

Broker ingress metrics

You can use the following metrics to debug the broker ingress, see how it is performing, and see which events are being dispatched by the ingress component.

Metric name Description Type Tags Unit

event_count

Number of events received by a broker.

Counter

broker_name, event_type, namespace_name, response_code, response_code_class, unique_name

Integer (no units)

event_dispatch_latencies

The time taken to dispatch an event to a channel.

Histogram

broker_name, event_type, namespace_name, response_code, response_code_class, unique_name

Milliseconds

Broker filter metrics

You can use the following metrics to debug broker filters, see how they are performing, and see which events are being dispatched by the filters. You can also measure the latency of the filtering action on an event.

Metric name Description Type Tags Unit

event_count

Number of events received by a broker.

Counter

broker_name, container_name, filter_type, namespace_name, response_code, response_code_class, trigger_name, unique_name

Integer (no units)

event_dispatch_latencies

The time taken to dispatch an event to a channel.

Histogram

broker_name, container_name, filter_type, namespace_name, response_code, response_code_class, trigger_name, unique_name

Milliseconds

event_processing_latencies

The time it takes to process an event before it is dispatched to a trigger subscriber.

Histogram

broker_name, container_name, filter_type, namespace_name, trigger_name, unique_name

Milliseconds

InMemoryChannel dispatcher metrics

You can use the following metrics to debug InMemoryChannel channels, see how they are performing, and see which events are being dispatched by the channels.

Metric name Description Type Tags Unit

event_count

Number of events dispatched by InMemoryChannel channels.

Counter

broker_name, container_name, filter_type, namespace_name, response_code, response_code_class, trigger_name, unique_name

Integer (no units)

event_dispatch_latencies

The time taken to dispatch an event from an InMemoryChannel channel.

Histogram

broker_name, container_name, filter_type, namespace_name, response_code, response_code_class, trigger_name, unique_name

Milliseconds

Event source metrics

You can use the following metrics to verify that events have been delivered from the event source to the connected event sink.

Metric name Description Type Tags Unit

event_count

Number of events sent by the event source.

Counter

broker_name, container_name, filter_type, namespace_name, response_code, response_code_class, trigger_name, unique_name

Integer (no units)

retry_event_count

Number of retried events sent by the event source after initially failing to be delivered.

Counter

event_source, event_type, name, namespace_name, resource_group, response_code, response_code_class, response_error, response_timeout

Integer (no units)

Knative Kafka broker metrics

You can use the following metrics to debug and visualize the performance of Kafka broker.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-broker-receiver-sm-service", namespace="knative-eventing"}

Number of events received by a broker

Counter
name

broker name

namespace_name

broker namespace

event_type

event type

response_code

HTTP response code returned by the broker

response_code_class

HTTP response code class returned by the broker: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-broker-receiver-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a Kafka cluster

Histogram
name

broker name

namespace_name

broker namespace

event_type

event type

response_code

HTTP response code returned by the broker

response_code_class

HTTP response code class returned by the broker: 2xx, 3xx, 4xx, 5xx

Milliseconds

kafka_broker_controller_consumer_group_expected_replicas

Number of expected replicas for a given Kafka consumer group resource

Gauge
consumer_name

resource name

namespace_name

resource namespace

consumer_kind

resource Kind, enum: KafkaSource, Trigger, Subscription

In this context, resources refer to user facing entities such as Kafka source, trigger, and subscription. Avoid using internal or generated names when using these resources.

Dimensionless

kafka_broker_controller_consumer_group_ready_replicas

Number of ready replicas for a given Kafka consumer group resource

Gauge
consumer_name

resource name

namespace_name

resource namespace

consumer_kind

resource Kind, enum: KafkaSource, Trigger, Subscription

In this context, resources refer to user facing entities such as Kafka source, trigger, and subscription. Avoid using internal or generated names when using these resources.

Dimensionless

Knative Kafka trigger metrics

You can use the following metrics to debug and visualize the performance of Kafka triggers.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-broker-dispatcher-sm-service", namespace="knative-eventing"}

Number of events dispatched by a trigger to a subscriber

Counter
consumer_name

trigger name

namespace_name

trigger namespace

name

broker name

event_type

event type

response_code

HTTP response code returned by the trigger subscriber service

response_code_class

HTTP response code class returned by the trigger subscriber service: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-broker-dispatcher-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a subscriber

Histogram
consumer_name

trigger name

namespace_name

trigger namespace

name

broker name

event_type

event type

response_code

HTTP response code returned by the trigger subscriber service

response_code_class

HTTP response code class returned by the trigger subscriber service: 2xx, 3xx, 4xx, 5xx

Milliseconds

event_processing_latencies_ms_bucket{job="kafka-broker-dispatcher-sm-service", namespace="knative-eventing"}

The time spent processing and filtering an event

Histogram
consumer_name

trigger name

namespace_name

trigger namespace

name

broker name

event_type

event type

Milliseconds

Knative Kafka channel metrics

You can use the following metrics to debug and visualize the performance of Kafka channel.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-channel-receiver-sm-service", namespace="knative-eventing"}

Number of events received by a Kafka channel

Counter
name

Kafka channel name

namespace_name

Kafka channel namespace

event_type

event type

response_code

HTTP response code returned by the Kafka channel

response_code_class

HTTP response code class returned by the Kafka channel: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-channel-receiver-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a Kafka cluster

Histogram
name

Kafka channel name

namespace_name

Kafka channel namespace

event_type

event type

response_code

HTTP response code returned by the Kafka channel

response_code_class

HTTP response code class returned by the Kafka channel: 2xx, 3xx, 4xx, 5xx

Milliseconds

Knative Kafka subscription metrics

You can use the following metrics to debug and visualize the performance of subscriptions associated with the Kafka channel.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-channel-dispatcher-sm-service", namespace="knative-eventing"}

Number of events dispatched by a subscription to a subscriber

Counter
consumer_name

Subscription name

namespace_name

Subscription namespace

name

KafkaChannel name

event_type

event type

response_code

HTTP response code returned by the Subscription subscriber service

response_code_class

HTTP response code class returned by the Subscription subscriber service: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-channel-dispatcher-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a subscriber

Histogram
consumer_name

Subscription name

namespace_name

Subscription namespace

name

KafkaChannel name

event_type

event type

response_code

HTTP response code returned by the Subscription subscriber service

response_code_class

HTTP response code class returned by the Subscription subscriber service: 2xx, 3xx, 4xx, 5xx

Milliseconds

event_processing_latencies_ms_bucket{job="kafka-channel-dispatcher-sm-service", namespace="knative-eventing"}

The time spent processing an event

Histogram
consumer_name

Subscription name

namespace_name

Subscription namespace

name

KafkaChannel name

event_type

event type

Dimensionless

Knative Kafka source metrics

You can use the following metrics to debug and visualize the performance of Kafka sources.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-source-dispatcher-sm-service", namespace="knative-eventing"}

Number of events dispatched by a Kafka source

Counter
consumer_name

Kafka source name

namespace_name

Kafka source namespace

name

Kafka source name

event_type

event type

response_code

HTTP response code returned by the Kafka source sink service

response_code_class

HTTP response code class returned by the Kafka source sink service: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-source-dispatcher-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a sink

Histogram
consumer_name

Kafka source name

namespace_name

Kafka source namespace

name

Kafka source name

event_type

event type

response_code

HTTP response code returned by the Kafka source sink service

response_code_class

HTTP response code class returned by the Kafka source sink service: 2xx, 3xx, 4xx, 5xx

Milliseconds

event_processing_latencies_ms_bucket{job="kafka-source-dispatcher-sm-service", namespace="knative-eventing"}

The time spent processing an event

Histogram
consumer_name

Kafka source name

namespace_name

Kafka source namespace

name

Kafka source name

event_type

event type

Milliseconds

kafka_broker_controller_consumer_group_expected_replicas

Number of expected replicas for a given Kafka consumer group resource

Gauge
consumer_name

resource name

namespace_name

resource namespace

consumer_kind

resource Kind, enum: KafkaSource, Trigger, Subscription

In this context, resources refer to user facing entities such as Kafka source,trigger, and subscription. Avoid using internal or generated names when using these resources.

Dimensionless

kafka_broker_controller_consumer_group_ready_replicas

Number of ready replicas for a given Kafka consumer group resource

Gauge
consumer_name

resource name

namespace_name

resource namespace

consumer_kind

resource Kind, enum: KafkaSource, Trigger, Subscription

In this context, resources refer to user facing entities such as Kafka source,trigger, and subscription. Avoid using internal or generated names when using these resources.

Dimensionless

Knative Kafka sink metrics

You can use the following metrics to debug and visualize the performance of Kafka sinks.

Metric name Description Type Tags Unit

event_count_1_total{job="kafka-sink-receiver-sm-service", namespace="knative-eventing"}

Number of events received by a broker

Counter
name

Kafka sink name

namespace_name

Kafka sink namespace

event_type

event type

response_code

HTTP response code returned by the Kafka sink

response_code_class

HTTP response code class returned by the Kafka sink: 2xx, 3xx, 4xx, 5xx

Dimensionless

event_dispatch_latencies_ms_bucket{job="kafka-sink-receiver-sm-service", namespace="knative-eventing"}

The time spent dispatching an event to a Kafka cluster

Histogram
name

Kafka sink name

namespace_name

Kafka sink namespace

event_type

event type

response_code

HTTP response code returned by the Kafka sink

response_code_class

HTTP response code class returned by the Kafka sink: 2xx, 3xx, 4xx, 5xx

Milliseconds