Send Metrics to SigNoz Cloud

Methods to Send Metrics

There are two primary ways to send metrics to SigNoz:

From your application
From OpenTelemetry Collector

This document will cover sending metrics from the OpenTelemetry Collector.

Prerequisites

Before you begin, ensure you have the following:

A running instance of SigNoz Cloud.
OpenTelemetry Collector installed.
Appropriate access and permissions.

In this document, we will cover how to send metrics from OpenTelemetry Collector. The Collector is a swiss-army knife that can collect metrics from various sources and send them to SigNoz.

How does OpenTelemetry Collector collect data
Enable a Specific Metric Receiver
Enable a Prometheus Receiver
Find Metrics available in SigNoz
- Metrics from Hostmetrics receiver
Related Videos
Get Help

How does OpenTelemetry Collector collect data?

Data collection in OpenTelemetry Collector is facilitated through receivers. Receivers are configured via YAML under the top-level receivers section. To ensure a valid configuration, at least one receiver must be enabled.

Below is an example of an otlp receiver:

receivers:
  otlp:
    protocols:
      grpc:
      http:

The OTLP receiver accepts data through gRPC or HTTP in the OTLP format.

Here’s a sample configuration for an otlp receiver:

receivers:
  otlp:
    protocols:
      http:
        endpoint: "localhost:4318"
        cors:
          allowed_origins:
            - http://test.com
            # Origins can have wildcards with *, use * by itself to match any origin.
            - https://*.example.com
          allowed_headers:
            - Example-Header
          max_age: 7200

To see more configuration options for otlp receiver, you can checkout this link.

Once a receiver is configured, it needs to be enabled to start the data flow. This involves setting up pipelines within a service. A pipeline acts as a streamlined pathway for data, outlining how it should be processed and where it should go. A pipeline comprises of the following:

Receivers: These are entry points for data into the OpenTelemetry Collector, responsible for collecting data from various sources and feeding it into the pipeline.
Processors: Metrics data is processed using the batch processor. This processor batches metrics before exporting them, optimizing the data flow.
Exporters: Metrics processed through this pipeline are exported to the OTLP endpoint mentioned in the configuration file.

Below is an example pipeline configuration:

service:
  pipelines:
    metrics:
      receivers: [otlp, httpcheck]
      processors: [batch]
      exporters: [otlp]

Here’s a breakdown of the above metrics pipeline:

Receivers: This pipeline is configured to receive metrics data from two sources: OTLP and HTTP Check. The otlp receiver collects metrics using both gRPC and HTTP protocols, while the httpcheck receiver gathers metrics from the HTTP endpoint.
Processors: Metrics data is processed using the batch processor. This processor likely batches metrics before exporting them, optimizing the data flow.
Exporters: Metrics processed through this pipeline are exported to the OTLP destination. The otlp exporter sends data to an endpoint specified in the configuration.

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 and service::pipelines sections of the otel-collector-config.yaml file. The following example shows the default configuration in which the hostmetrics receiver is enabled:

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: localhost:4317
      http:
        endpoint: localhost:4318
  hostmetrics:
    collection_interval: 30s
    scrapers:
      cpu: {}
      disk: {}
      load: {}
      filesystem: {}
      memory: {}
      network: {}
      paging: {}
      process:
        mute_process_name_error: true
        mute_process_exe_error: true
        mute_process_io_error: true
      processes: {}
processors:
  batch:
    send_batch_size: 1000
    timeout: 10s
  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
  resourcedetection:
    detectors: [env, system, ec2] # include ec2 for AWS, gcp for GCP and azure for Azure.
    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
    timeout: 2s
    override: false
    system:
      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
exporters:
  otlp:
    endpoint: "ingest.{region}.signoz.cloud:443" # replace {region} with your region
    tls:
      insecure: false
    headers:
      "signoz-ingestion-key": "<SIGNOZ_INGESTION_KEY>"
  logging:
    verbosity: detailed
service:
  telemetry:
    metrics:
      address: localhost:8888
  pipelines:
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]
    metrics/hostmetrics:
      receivers: [hostmetrics]
      processors: [resourcedetection, batch]
      exporters: [otlp]

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

Open the otel-collector-config.yaml file in a plain-text editor.
Configure your receivers. The following example shows how you can enable a rabbitmq receiver:

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: localhost:4317
      http:
        endpoint: localhost:4318
  hostmetrics:
    collection_interval: 30s
    scrapers:
      cpu: {}
      disk: {}
      load: {}
      filesystem: {}
      memory: {}
      network: {}
      paging: {}
      process:
        mute_process_name_error: true
        mute_process_exe_error: true
        mute_process_io_error: true
      processes: {}
  rabbitmq:
    endpoint: http://localhost:15672
    username: <RABBITMQ_USERNAME>
    password: <RABBITMQ_PASSWORD>
    collection_interval: 30s
processors:
  batch:
    send_batch_size: 1000
    timeout: 10s
  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
  resourcedetection:
    detectors: [env, system, ec2] # include ec2 for AWS, gcp for GCP and azure for Azure.
    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
    timeout: 2s
    override: false
    system:
      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
exporters:
  otlp:
    endpoint: "ingest.{region}.signoz.cloud:443" # replace {region} with your region
    tls:
      insecure: false
    headers:
      "signoz-ingestion-key": "<SIGNOZ_INGESTION_KEY>"
  logging:
    verbosity: detailed
service:
  telemetry:
    metrics:
      address: localhost:8888
  pipelines:
    metrics:
      receivers: [otlp, rabbitmq]
      processors: [batch]
      exporters: [otlp]
    metrics/hostmetrics:
      receivers: [hostmetrics]
      processors: [resourcedetection, batch]
      exporters: [otlp]

For details about configuring OpenTelemetry receivers, see the README page of the opentelemetry-collector GitHub repository.

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 otel-collector-config.yaml file.

To enable a Prometheus receiver, follow the steps below:

Open the otel-collector-config.yaml file in a plain-text editor.

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:

  ...
  # 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"]
  ...
# 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:

  ...
  # Data sources: metrics
  prometheus:
    config:
      scrape_configs:
        - job_name: "otel-collector"
          scrape_interval: 30s
          static_configs:
            - targets: ["otel-collector:8889", "localhost:8080"]       
  ...
# 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:

If you'd like to learn more about how to monitor Prometheus Metrics with OpenTelemetry Collector, refer to this blog.

Find Metrics available in SigNoz

You can use this metrics to plot in the Dashboard section.

How to view Prometheus Metrics in SigNoz

Get Help

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

If you are a SigNoz Cloud user, please use in product chat support located at the bottom right corner of your SigNoz instance or contact us at cloud-support@signoz.io.