Metrics¶

Numaflow provides the following prometheus metrics which we can use to monitor our pipeline and setup any alerts if needed.

Golden Signals¶

These metrics in combination can be used to determine the overall health of your pipeline

Traffic¶

These metrics can be used to determine throughput of your pipeline.

Data-forward¶

Metric name	Metric type	Labels	Description
`forwarder_data_read_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of messages read by a given Vertex from an Inter-Step Buffer Partition
`forwarder_read_bytes_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of bytes read by a given Vertex from an Inter-Step Buffer Partition
`forwarder_write_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of messages written to Inter-Step Buffer by a given Vertex
`forwarder_write_bytes_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of bytes written to Inter-Step Buffer by a given Vertex
`forwarder_ack_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of messages acknowledged by a given Vertex from an Inter-Step Buffer Partition
`forwarder_drop_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of messages dropped by a given Vertex due to a full Inter-Step Buffer Partition
`forwarder_drop_bytes_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides the total number of bytes dropped by a given Vertex due to a full Inter-Step Buffer Partition

Kafka Source¶

Metric name	Metric type	Labels	Description
`kafka_source_read_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages read by the Kafka Source Vertex/Processor.
`kafka_source_ack_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages acknowledged by the Kafka Source Vertex/Processor

Generator Source¶

Metric name	Metric type	Labels	Description
`tickgen_source_read_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages read by the Generator Source Vertex/Processor.

Http Source¶

Metric name	Metric type	Labels	Description
`http_source_read_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages read by the HTTP Source Vertex/Processor.

Kafka Sink¶

Metric name	Metric type	Labels	Description
`kafka_sink_write_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages written by the Kafka Sink Vertex/Processor

Log Sink¶

Metric name	Metric type	Labels	Description
`log_sink_write_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of messages written by the Log Sink Vertex/Processor

Latency¶

These metrics can be used to determine the latency of your pipeline.

Metric name	Metric type	Labels	Description
`source_forwarder_transformer_processing_time`	Histogram	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Provides a histogram distribution of the processing times of User Defined Source Transformer
`forwarder_udf_processing_time`	Histogram	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>`	Provides a histogram distribution of the processing times of User Defined Functions. (UDF's)
`forwarder_forward_chunk_processing_time`	Histogram	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>`	Provides a histogram distribution of the processing times of the forwarder function as a whole
`reduce_pnf_process_time`	Histogram	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `replica=<replica-index>`	Provides a histogram distribution of the processing times of the reducer
`reduce_pnf_forward_time`	Histogram	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `replica=<replica-index>`	Provides a histogram distribution of the forwarding times of the reducer

Errors¶

These metrics can be used to determine if there are any errors in the pipeline

Metric name	Metric type	Labels	Description
`forwarder_platform_error_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>`	Indicates any internal errors which could stop pipeline processing
`forwarder_read_error_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Indicates any errors while reading messages by the forwarder
`forwarder_write_error_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Indicates any errors while writing messages by the forwarder
`forwarder_ack_error_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>` `vertex_type=<vertex-type>` `replica=<replica-index>` `partition_name=<partition-name>`	Indicates any errors while acknowledging messages by the forwarder
`kafka_source_offset_ack_errors`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Indicates any kafka acknowledgement errors
`kafka_sink_write_error_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the number of errors while writing to the Kafka sink
`kafka_sink_write_timeout_total`	Counter	`pipeline=<pipeline-name>` `vertex=<vertex-name>`	Provides the write timeouts while writing to the Kafka sink
`isb_jetstream_read_error_total`	Counter	`partition_name=<partition-name>`	Indicates any read errors with NATS Jetstream ISB
`isb_jetstream_write_error_total`	Counter	`partition_name=<partition-name>`	Indicates any write errors with NATS Jetstream ISB
`isb_redis_read_error_total`	Counter	`partition_name=<partition-name>`	Indicates any read errors with Redis ISB
`isb_redis_write_error_total`	Counter	`partition_name=<partition-name>`	Indicates any write errors with Redis ISB

Saturation¶

NATS JetStream ISB¶

Metric name	Metric type	Labels	Description
`isb_jetstream_isFull_total`	Counter	`buffer=<buffer-name>`	Indicates if the ISB is full. Continual increase of this counter metric indicates a potential backpressure that can be built on the pipeline
`isb_jetstream_buffer_soft_usage`	Gauge	`buffer=<buffer-name>`	Indicates the usage/utilization of a NATS Jetstream ISB
`isb_jetstream_buffer_solid_usage`	Gauge	`buffer=<buffer-name>`	Indicates the solid usage of a NATS Jetstream ISB
`isb_jetstream_buffer_pending`	Gauge	`buffer=<buffer-name>`	Indicate the number of pending messages at a given point in time.
`isb_jetstream_buffer_ack_pending`	Gauge	`buffer=<buffer-name>`	Indicates the number of messages pending acknowledge at a given point in time

Redis ISB¶

Metric name	Metric type	Labels	Description
`isb_redis_isFull_total`	Counter	`buffer=<buffer-name>`	Indicates if the ISB is full. Continual increase of this counter metric indicates a potential backpressure that can be built on the pipeline
`isb_redis_buffer_usage`	Gauge	`buffer=<buffer-name>`	Indicates the usage/utilization of a Redis ISB
`isb_redis_consumer_lag`	Gauge	`buffer=<buffer-name>`	Indicates the the consumer lag of a Redis ISB

Prometheus Operator for Scraping Metrics:¶

You can follow the prometheus operator setup guide if you would like to use prometheus operator configured in your cluster.

You can also set up prometheus operator via helm.

Configure the below Service Monitors for scraping your pipeline metrics:¶

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  labels:
    app.kubernetes.io/part-of: numaflow
  name: numaflow-pipeline-metrics
spec:
  endpoints:
    - scheme: https
      port: metrics
      targetPort: 2469
      tlsConfig:
        insecureSkipVerify: true
  selector:
    matchLabels:
      app.kubernetes.io/component: vertex
      app.kubernetes.io/managed-by: vertex-controller
      app.kubernetes.io/part-of: numaflow
    matchExpressions:
      - key: numaflow.numaproj.io/pipeline-name
        operator: Exists
      - key: numaflow.numaproj.io/vertex-name
        operator: Exists

Configure the below Service Monitor if you use the NATS Jetstream ISB for your NATS Jetstream metrics:¶

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  labels:
    app.kubernetes.io/part-of: numaflow
  name: numaflow-isbsvc-jetstream-metrics
spec:
  endpoints:
    - scheme: http
      port: metrics
      targetPort: 7777
  selector:
    matchLabels:
      app.kubernetes.io/component: isbsvc
      app.kubernetes.io/managed-by: isbsvc-controller
      app.kubernetes.io/part-of: numaflow
      numaflow.numaproj.io/isbsvc-type: jetstream
    matchExpressions:
      - key: numaflow.numaproj.io/isbsvc-name
        operator: Exists