Metrics is a valuable tool for getting visibility into your Cloud deployment. StreamNative Cloud provides a broad range of metrics that you can use to help fine-tune performance and troubleshoot issues.

Metrics endpoint

StreamNative Cloud provides an endpoint that exposes real-time metrics in Prometheus metrics format. The following table displays the currently available metrics endpoints.

Metrics authorization

To access and scrape metrics from the Cloud endpoints, you must use a Super Admin service account or a normal service account with metrics-viewer role.

Super Admin service account

To create a super admin service account, please check the create a service account.

metrics-viewer role

To bind a service account with metrics-viewer, your can configure it through snctl or terraform.

snctl create serviceaccount metrics-account

snctl create rolebinding metrics-viewer --serviceaccount metrics-account --clusterrole metrics-viewer

snctl delete rolebinding metrics-viewer

Pulsar resource metrics

Source connector metrics

Sink connector metrics

Function metrics

Kafka Connect metrics

Health metrics

Metrics API integration

Prometheus integration

To collect Pulsar metrics into Prometheus, add the following to your Prometheus configuration file. The bearer tokens have a limited life cycle, therefore it is recommended to use the OAuth2 authentication method.

global:
  scrape_interval: 120s
  scrape_timeout: 60s
scrape_configs:
  - job_name: streamnative
    metrics_path: /v1/cloud/metrics/export
    scheme: https
    oauth2:
      client_id: '${client_id}'
      client_secret: '${client_secret}'
      token_url: https://auth.streamnative.cloud/oauth/token
      endpoint_params:
        grant_type: 'client_credentials'
        audience: '${audience}'
    static_configs:
      - targets: [metrics.streamnative.cloud]

You can find the values of client_id and client_secret in the Key file of a Super Admin Service Account. For more information, see work with service accounts.

The audience parameter is the Uniform Resource Name (URN), which is a combination of the urn:sn:pulsar, the organization name, and the Pulsar instance name at StreamNative:

"urn:sn:pulsar:${org_name}:${instance_name}"

OpenTelemetry collector integration

The OpenTelemetry collector, as described on its official page, is a vendor-agnostic agent process designed for gathering and sending telemetry data from various sources. StreamNative Cloud, which outputs its metrics in the Prometheus format, is compatible with the OpenTelemetry collector. To collect metrics from StreamNative Cloud, configure your OpenTelemetry collector to utilize the Prometheus Receiver, which is fully compatible with Prometheus's scape_config settings.

To configure your collector, refer to the guidance provided in the Prometheus Integration section. There, you will find instructions to create a scape_config for collecting metrics from StreamNative Cloud. This config should be placed in your collector's configuration file under the following section:

receivers:
  prometheus:
    config:

An example of such configuration is as follows:

receivers:
  prometheus:
    config:
      scrape_configs:
        - job_name: streamnative
          metrics_path: /v1/cloud/metrics/export
          scheme: https
          oauth2:
            client_id: '${client_id}'
            client_secret: '${client_secret}'
            token_url: https://auth.streamnative.cloud/oauth/token
            endpoint_params:
              grant_type: 'client_credentials'
              audience: '${audience}'
          static_configs:
            - targets: [metrics.streamnative.cloud]

The OpenTelemetry collector's versatility allows it to support a range of exporters, facilitating the routing of metrics from StreamNative Cloud to various observability platforms. A comprehensive list of supported exporters by the OpenTelemetry collector is available here.

NewRelic integration

You can use a Prometheus instance to forward metrics to NewRelic. To do this, add a remote_write entry to the prometheus.yml configuration file as described in the Prometheus Integration section:

remote_write:
  - url: https://metric-api.newrelic.com/prometheus/v1/write?prometheus_server=streamnative
    authorization:
      credentials: '${newrelic_ingest_key}'

Then by running a Prometheus instance, the Pulsar metrics are scraped from the StreamNative endpoint and forwarded to NewRelic:

prometheus --config.file=prometheus.yml

If you want to keep data from going into this Prometheus instance, you can setup a short retention time with the storage.tsdb.retention.time parameter:

prometheus --config.file=prometheus.yml --storage.tsdb.retention.time=15m

Grafana Cloud integration

You can use a Prometheus instance to forward metrics to Grafana Cloud. To do this, add a remote_write entry to the prometheus.yml configuration file as described in the Prometheus Integration section:

remote_write:
  - url: ${grafana_cloud_endpoint}/api/prom/push
    basic_auth:
      username: '${grafana_cloud_username}'
      password: '${grafana_cloud_api_key}'

You can find the grafana_cloud_endpoint and grafana_cloud_username values by selecting Prometheus at https://grafana.com/orgs/${grafana_org}. You can find grafana_cloud_api_key at https://grafana.com/orgs/${grafana_org}/api-keys.

Then by running a Prometheus instance, the Pulsar metrics are scraped from the StreamNative endpoint and forwarded to Grafana Cloud:

prometheus --config.file=prometheus.yml

If you want to keep data from going into this Prometheus instance, you can setup a short retention time with the storage.tsdb.retention.time parameter:

prometheus --config.file=prometheus.yml --storage.tsdb.retention.time=15m

Datadog integration

Integrate with Datadog Agent

Using Datadog Agent, you can connect Datadog to the StreamNative Cloud Metrics endpoint to start collecting metrics. Datadog Agent supports most platform to host and this documentation will mainly to demonstrate with Docker and Kubernetes.

init_config:
  service: docker

instances:
  - openmetrics_endpoint: https://metrics.streamnative.cloud/v1/cloud/metrics/export
    request_size: 900
    min_collection_interval: 180
    metrics:
      - pulsar_topics_count:
          type: gauge
          name: pulsar_topics_count
      - pulsar_subscriptions_count:
          type: gauge
          name: pulsar_subscriptions_count
      - pulsar_producers_count:
          type: gauge
          name: pulsar_producers_count
      - pulsar_consumers_count:
          type: gauge
          name: pulsar_consumers_count
      - pulsar_rate_in:
          type: gauge
          name: pulsar_rate_in
      - pulsar_rate_out:
          type: gauge
          name: pulsar_rate_out
      - pulsar_throughput_in:
          type: gauge
          name: pulsar_throughput_in
      - pulsar_throughput_out:
          type: gauge
          name: pulsar_throughput_out
      - pulsar_storage_size:
          type: gauge
          name: pulsar_storage_size
      - pulsar_storage_backlog_size:
          type: gauge
          name: pulsar_storage_backlog_size
      - pulsar_storage_offloaded_size:
          type: gauge
          name: pulsar_storage_offloaded_size
      - pulsar_storage_read_rate:
          type: gauge
          name: pulsar_storage_read_rate
      - pulsar_subscription_delayed:
          type: gauge
          name: pulsar_subscription_delayed
      - pulsar_storage_write_latency_le_0_5:
          type: histogram
          name: pulsar_storage_write_latency_le_0_5
      - pulsar_storage_write_latency_le_1:
          type: histogram
          name: pulsar_storage_write_latency_le_1
      - pulsar_storage_write_latency_le_5:
          type: histogram
          name: pulsar_storage_write_latency_le_5
      - pulsar_storage_write_latency_le_10:
          type: histogram
          name: pulsar_storage_write_latency_le_10
      - pulsar_storage_write_latency_le_20:
          type: histogram
          name: pulsar_storage_write_latency_le_20
      - pulsar_storage_write_latency_le_50:
          type: histogram
          name: pulsar_storage_write_latency_le_50
      - pulsar_storage_write_latency_le_100:
          type: histogram
          name: pulsar_storage_write_latency_le_100
      - pulsar_storage_write_latency_le_200:
          type: histogram
          name: pulsar_storage_write_latency_le_200
      - pulsar_storage_write_latency_le_1000:
          type: histogram
          name: pulsar_storage_write_latency_le_1000
      - pulsar_storage_write_latency_le_overflow:
          type: histogram
          name: pulsar_storage_write_latency_le_overflow
      - pulsar_entry_size_le_128:
          type: histogram
          name: pulsar_entry_size_le_128
      - pulsar_entry_size_le_512:
          type: histogram
          name: pulsar_entry_size_le_512
      - pulsar_entry_size_le_1_kb:
          type: histogram
          name: pulsar_entry_size_le_1_kb
      - pulsar_entry_size_le_4_kb:
          type: histogram
          name: pulsar_entry_size_le_4_kb
      - pulsar_entry_size_le_16_kb:
          type: histogram
          name: pulsar_entry_size_le_16_kb
    auth_token:
      reader:
        type: oauth
        url: https://auth.streamnative.cloud/oauth/token
        client_id: { your-admin-service-account-client-id }
        client_secret: { your-admin-service-account-client-secret }
        options:
          audience: urn:sn:pulsar:{your-organization}:{your-instance}
      writer:
        type: header
        name: Authorization
        value: Bearer <TOKEN>
        placeholder: <TOKEN>

docker run -d --name dd-agent \
-e DD_API_KEY={ your-Datadog-API-Key } \
-e DD_SITE={ your-Datadog-Site-region } \
-e DD_APM_NON_LOCAL_TRAFFIC=true \
-v {your-config-yaml-file-path}:/etc/datadog-agent/conf.d/openmetrics.d/conf.yaml:ro \
-v /var/run/docker.sock:/var/run/docker.sock:ro \
-v /proc/:/host/proc/:ro \
-v /sys/fs/cgroup/:/host/sys/fs/cgroup:ro \
-v /var/lib/docker/containers:/var/lib/docker/containers:ro \
datadog/agent:7.52.0

Bridge with OpenTelemetry

You can use OpenTelemetry Collector to collect the metrics from StreamNative Cloud and export them to Datadog.

To export metrics to Datadog, you can use the Datadog Exporter and add it to your OpenTelemetry Collector configuration. Use the example file which provides a basic configuration that is ready to use after you set your Datadog API key as the ${DD_API_KEY} variable:

receivers:
  prometheus:
    config:
      scrape_configs:
        - job_name: streamnative
          metrics_path: /v1/cloud/metrics/export
          scheme: https
          oauth2:
            client_id: '${client_id}'
            client_secret: '${client_secret}'
            token_url: https://auth.streamnative.cloud/oauth/token
            endpoint_params:
              grant_type: 'client_credentials'
              audience: '${audience}'
          static_configs:
            - targets: [metrics.streamnative.cloud]

processors:
  batch:
    send_batch_max_size: '10MiB'
    send_batch_size: 4096
    timeout: 120s

exporters:
  datadog:
    api:
      site: ${DD_SITE}
      key: ${DD_API_KEY}

service:
  pipelines:
    metrics:
      receivers: [prometheus]
      processors: [batch]
      exporters: [datadog]

Where ${DD_SITE} is your site, .

The above configuration enables the receiving of metrics from StreamNative Cloud, sets up a batch processor, which is mandatory for any non-development environment, and exports to Datadog. You can refer to this full documented example configuration file for all possible configuration options for Datadog Exporter.