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Send Metrics to SigNoz

By default, when you install SigNoz, only the Hostmetric receiver is enabled. Before you can query other metrics, you must first enable additional receivers in SigNoz.

There are two ways in which you can send metrics to SigNoz using OpenTelemetry:

Depending on your choice, use one of the sections below.

Enable a Specific Metric Receiver​

SigNoz supports all the receivers that are listed in the opentelemetry-collector-contrib GitHub repository. To configure a new metric receiver, you must edit the receivers section of the deploy/docker/clickhouse-setup/otel-collector-config.yaml file. The following example shows the default configuration in which the hostmetrics receiver is enabled:

receivers:
  otlp/spanmetrics:
    protocols:
      grpc:
        endpoint: "localhost:12345"
  otlp:
    protocols:
      grpc:
      http:
  jaeger:
    protocols:
      grpc:
      thrift_http:
  hostmetrics:
    collection_interval: 30s
    scrapers:
      cpu:
      load:
      memory:
      disk:
      filesystem:
      network:
processors:
  batch:
    send_batch_size: 1000
    timeout: 10s
# This file was truncated for brevity

To enable a new OpenTelemetry receiver, follow the steps below:

  1. Move into the directory in which you installed SigNoz, and open the deploy/docker/clickhouse-setup/otel-collector-config.yaml file in a plain-text editor.
  2. Configure your receivers. The following example shows how you can enable a receiver named examplereceiver:
    receivers:
      otlp/spanmetrics:
        protocols:
          grpc:
            endpoint: "localhost:12345"
      otlp:
        protocols:
          grpc:
          http:
      jaeger:
        protocols:
          grpc:
          thrift_http:
      hostmetrics:
        collection_interval: 30s
        scrapers:
          cpu:
          load:
          memory:
          disk:
          filesystem:
          network:
      examplereceiver:
        endpoint: 1.2.3.4:8080
    processors:
      batch:
        send_batch_size: 1000
        timeout: 10s
    # This file was truncated for brevity.
    For details about configuring OpenTelemetry receivers, see the README page of the opentelemetry-collector GitHub repository.

  3. Save the changes you’ve made and restart SigNoz. Depending on how you installed SigNoz, follow the steps in one of the sections below:

Enable a Prometheus Receiver​

SigNoz supports all the exporters that are listed on the Exporters and Integrations page of the Prometheus documentation. If you have a running Prometheus instance, and you expose metrics in Prometheus, then you can scrape them in SigNoz by configuring Prometheus receivers in the receivers.prometheus.config.scrape_configs section of the deploy/docker/clickhouse-setup/otel-collector-metrics-config.yaml file.

To enable a Prometheus receiver, follow the steps below:

  1. Open the deploy/docker/clickhouse-setup/otel-collector-metrics-config.yaml file in a plain-text editor.

  2. Enable a new Prometheus receiver. Depending on your use case, there are two ways in which you can enable a new Prometheus exporter:

    • By creating a new job: The following example shows how you can enable a Prometheus receiver by creating a new job named my-new-job:

      receivers:
        otlp:
          protocols:
            grpc:
            http:

        # Data sources: metrics
        prometheus:
          config:
            scrape_configs:
              - job_name: "otel-collector"
                scrape_interval: 30s
                static_configs:
                  - targets: ["otel-collector:8889"]
              - job_name: "my-new-job"
                scrape_interval: 30s
                static_configs:
                  - targets: ["localhost:8080"]          
      processors:
        batch:
          send_batch_size: 1000
          timeout: 10s
      # This file was truncated for brevity.

    • By adding a new target to an existing job: The following example shows the default otel-collector job to which a new target (localhost:8080) was added:

      receivers:
        otlp:
          protocols:
            grpc:
            http:

        # Data sources: metrics
        prometheus:
          config:
            scrape_configs:
              - job_name: "otel-collector"
                scrape_interval: 30s
                static_configs:
                  - targets: ["otel-collector:8889", "localhost:8080"]       
      processors:
        batch:
          send_batch_size: 1000
          timeout: 10s
      # This file was truncated for brevity.

      Note that all the jobs are scraped in parallel, and all targets inside a job are scraped serially. For more details about configuring jobs and targets, see the following sections of the Prometheus documentation:

  3. Save the changes you’ve made and restart SigNoz. Depending on how you installed SigNoz, follow the steps in one of the sections below:

Find Metrics available in SigNoz​

You can connect to SigNoz'a clickhouse instance and find the metrics SigNoz is storing. As of now this is bit of manual process, we are bringing capbilities to auto-suggest available metrics soon.

You can follow the below steps

  1. Install ClickHouse client

  2. Connect to the ClickHouse container

    docker exec -it clickhouse-setup_clickhouse_1 bash

  3. Run the clickhouse-client command to connect to the database service

    clickhouse client --host <SigNoz IP>  --port 9000

  4. Run the query to list metrics

    select DISTINCT(JSONExtractString(time_series.labels,'__name__')) as metrics from signoz_metrics.time_series

  5. If needed, dump in a csv file and parse it locally

    select DISTINCT(labels) from signoz_metrics.time_series INTO OUTFILE 'output.csv'

You can use this metrics to plot in the Dashboard section

Metrics from Hostmetrics receiver​

Metrics which are available if hostmetrics is enabled. This is enabled in SigNoz default installation.

MetricsDescription
system_filesystem_usage_total
system_network_dropped_total
system_cpu_time_total
system_disk_merged_total
system_disk_io_time_total
system_disk_operations_total
system_network_errors_total
system_network_io_total
system_disk_weighted_io_time_total
system_network_packets_total
system_disk_operation_time_total
system_cpu_load_average_5m
system_memory_usage_total
system_disk_pending_operations_total
system_disk_io_total
system_cpu_load_average_15m
system_cpu_load_average_1m

Get Help​

If you need help with the steps in this topic, please reach out to us on Slack.