OpenTelemetry Custom Metrics

Coralogix provides a scalable Prometheus-compatible managed service for time-series data. Employ our custom metric endpoint, including serverless computing and quick cURL-like calls, to send counters, gauges, and histograms to Coralogix.

Overview

Coralogix supports ingesting metrics in multiple ways. Our most common integrations are Prometheus & OpenTelemetry, as well as metric-specific integrations such as CloudWatch metrics and AWS Kinesis Firehose. View a full list of available integrations here.

This tutorial presents a series of use cases employing our custom metric endpoint, referred to as the OpenTelemetry endpoint, to send your data to Coralogix. The examples below employ gRPCurl and OpenTelemetry Java SDK.

Coralogix metrics employs the Prometheus data model, wherein metrics sent can be in the form of counters, gauges, and histograms.

Prerequisites

If you are sending us your data using gRPCurl, you are required to have Git and gRPCurl installed.

Data Model

The custom logs API implementation is based on the OpenTelemetry metric specification. This ensures that our logging implementation adheres to industry best practices and can seamlessly integrate with other components and tools in the OpenTelemetry ecosystem.

Counter & Gauge Example

{
  "resource_metrics": {
    "resource": {
      "attributes": [
        {
          "key": "cx.application.name",
          "value": {
            "string_value": "my-test-application"
          }
        },
        {
          "key": "cx.subsystem.name",
          "value": {
            "string_value": "my-test-subsystem"
          }
        },
        {
          "key": "service.name",
          "value": {
            "string_value": "my-test-service"
          }
        }
      ]
    },
    "scope_metrics": {
      "metrics": [{
        "name": "grpc_sample_gauge1",
        "gauge": {
          "data_points": [{
            "as_double": 0.8,
            "start_time_unix_nano": 1657079957000000000,
            "time_unix_nano": 1657079957000000000
          }]
        }
      },{
        "name": "grpc_sample_counter1",
        "gauge": {
          "data_points": [{
            "as_int": 100,
            "start_time_unix_nano": 1657079957000000000,
            "time_unix_nano": 1657079957000000000
          }]
        }
      }]
    }
  }
}

Notes:

• Currently both timestamps as well as service.name are mandatory.

Sending Data With gRPCurl

gRPC is a modern way of calling APIs on top of HTTP/2. Similar to cURL, gRPCurl is a command-line tool used to communicate with gRPC services.

Coralogix currently supports gRPC for its custom metrics endpoint.

Assuming the example in the data model is saved as metrics.json, use the following command to send your data to Coralogix:

# Clone OpenTelemetry protobuf definitions
git clone https://github.com/open-telemetry/opentelemetry-proto.git
# Send metrics to Coralogix 
grpcurl -v -d @ \
  -rpc-header 'Authorization: Bearer <send-your-data-api-key>' \
  -proto opentelemetry-proto/opentelemetry/proto/collector/metrics/v1/metrics_service.proto \
  -import-path opentelemetry-proto \
  <open-telemetry-endpoint> \
  opentelemetry.proto.collector.metrics.v1.MetricsService/Export \
  < metrics.json

Notes:

• For <open-telemetry-endpoint>, input the Coralogix OpenTelemetry endpoint associated with your Coralogix domain.

• For the <send-your-data-api-key>, input your Coralogix Send-Your-Data API key.

• Set the start_time_unix_nano and the time_unix_nano in the metrics.json to a timestamp that is within the last 24 hours.

Sending Data Using the OpenTelemetry Java SDK

The example below guides you using OpenTelemetry Java SDK to send your custom traces to Coralogix. Others SDKs may also be used.

STEP 1. Add to your maven pom.xml the following libraries:

<dependency>
  <groupId>io.opentelemetry</groupId>
  <artifactId>opentelemetry-sdk-metrics</artifactId>
  <version><!-- put a recent version of opentelemetry sdk here --><version>
</dependency>
<dependency>
  <groupId>io.opentelemetry</groupId>
  <artifactId>opentelemetry-exporter-otlp</artifactId>
  <version><!-- put a recent version of opentelemetry sdk here --><version>
</dependency>

STEP 2. Use this code snippet to generate a counter and a gauge:

SdkMeterProvider meterProvider =
      SdkMeterProvider.builder()
        .registerMetricReader(
          PeriodicMetricReader.builder(
            OtlpGrpcMetricExporter.builder()
              .setEndpoint("https://<open-telemetry-endpoint>")
              .addHeader("Authorization", "Bearer <send-your-data-api-key>")
              .build()
          ).build()
        )
        .setResource(Resource.create(Attributes.of(
          ResourceAttributes.SERVICE_NAME, "my-test-service",
          AttributeKey.stringKey("cx.application.name"), "my-test-application",
          AttributeKey.stringKey("cx.subsystem.name"), "my-test-subsystem")))
        .build();

    Meter meter = meterProvider.meterBuilder("test").build();

    LongCounter counter = meter
      .counterBuilder("otlp_test_counter1")
      .setDescription("Processed jobs")
      .build();
    counter.add(100);

    meter
      .gaugeBuilder("otlp_test_gauge1")
      .buildWithCallback(measurement -> {
        measurement.record(0.8);
      });
    meterProvider.forceFlush();

Notes:

• Currently the service.name attribute is mandatory on each metric.

Limits & Quotas

• Coralogix places a hard limit of 10MB of data to our OpenTelemetry endpoints, with a recommendation of 2MB.

• Metric names must be a maximum of 255 characters.

• Attribute keys for metric data must be a maximum of 255 characters.

Limits apply to single requests, regardless of timespan.

Additional Resources

Support

Need help?

Our world-class customer success team is available 24/7 to walk you through your setup and answer any questions that may come up.

Feel free to reach out to us via our in-app chat or by sending us an email at [email protected].

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