# OpenTelemetry custom metrics Copy as Markdown[Open in ChatGPT](https://chatgpt.com/?q=Read%20https%3A%2F%2Fcoralogix.com%2Fdocs%2Fintegrations%2Fdata-ingestion%2Fopentelemetry-custom-metrics.md%20and%20help%20me%20with%20my%20question%20about%20this%20Coralogix%20documentation%20page.)[Open in Claude](https://claude.ai/new?q=Read%20https%3A%2F%2Fcoralogix.com%2Fdocs%2Fintegrations%2Fdata-ingestion%2Fopentelemetry-custom-metrics.md%20and%20help%20me%20with%20my%20question%20about%20this%20Coralogix%20documentation%20page.) 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[​](#overview "Direct link to Overview") Coralogix supports ingesting metrics in multiple ways. Our most common integrations are [Prometheus](https://coralogix.com/docs/docs/integrations/metrics/prometheus/.md) & [OpenTelemetry](https://coralogix.com/blog/tag/opentelemetry/), as well as metric-specific integrations such as [CloudWatch metrics](https://coralogix.com/docs/docs/integrations/aws/amazon-data-firehose/aws-cloudwatch-metric-streams-with-amazon-data-firehose/.md) and [AWS Kinesis Firehose](https://coralogix.com/docs/docs/integrations/aws/amazon-data-firehose/send-logs-using-amazon-data-firehose/.md). View a full list of available integrations [here](https://coralogix.com/integrations/). This tutorial presents a series of use cases employing our custom metric endpoint, referred to as the ingress.:443 endpoint, to send your data to Coralogix. The examples below employ gRPCurl and OpenTelemetry Java SDK. Coralogix metrics employs the [Prometheus data model](https://prometheus.io/docs/concepts/data_model/), wherein metrics sent can be in the form of counters, gauges, and histograms. ## Prerequisites[​](#prerequisites "Direct link to Prerequisites") If you are sending us your data using gRPCurl, you are required to have [Git](https://git-scm.com/) and [gRPCurl](https://github.com/fullstorydev/grpcurl) installed. ## Data model[​](#data-model "Direct link to Data model") The custom logs API implementation is based on the OpenTelemetry [metric specification](https://github.com/open-telemetry/opentelemetry-proto/blob/main/opentelemetry/proto/metrics/v1/metrics.proto). 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[​](#counter--gauge-example "Direct link to 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[​](#sending-data-with-grpcurl "Direct link to Sending data with gRPCurl") gRPC is a modern way of calling APIs on top of HTTP/2. Similar to cURL, [gRPCurl](https://github.com/fullstorydev/grpcurl) is a command-line tool used to communicate with gRPC services. Coralogix supports OTLP/gRPC and OTLP/HTTP (binary protobuf or JSON payloads) 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 ' \ -proto opentelemetry-proto/opentelemetry/proto/collector/metrics/v1/metrics_service.proto \ -import-path opentelemetry-proto \ ingress.eu2.coralogix.com:443 \ opentelemetry.proto.collector.metrics.v1.MetricsService/Export \ < metrics.json ``` **Notes**: * For ``, select the ingress.:443 endpoint that corresponds to your Coralogix [domain](https://coralogix.com/docs/docs/user-guides/account-management/account-settings/coralogix-domain/.md) using the domain selector at the top of the page. * For the ``, input your Coralogix [Send-Your-Data API key](https://coralogix.com/docs/docs/user-guides/account-management/api-keys/send-your-data-api-key/.md). * 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[​](#sending-data-using-the-opentelemetry-java-sdk "Direct link to 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](https://opentelemetry.io/docs/concepts/sdk-configuration/) may also be used. **STEP 1**. Add to your maven pom.xml the following libraries: ``` io.opentelemetry opentelemetry-sdk-metrics io.opentelemetry opentelemetry-exporter-otlp ``` **STEP 2**. Use this code snippet to generate a counter and a gauge: ``` SdkMeterProvider meterProvider = SdkMeterProvider.builder() .registerMetricReader( PeriodicMetricReader.builder( OtlpGrpcMetricExporter.builder() .setEndpoint("https://ingress.eu2.coralogix.com:443") .addHeader("Authorization", "Bearer ") .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[​](#limits--quotas "Direct link to Limits & quotas") * Coralogix places a **hard limit of 10MB** of data to our OpenTelemetry [endpoints](https://coralogix.com/docs/docs/integrations/coralogix-endpoints/.md), 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[​](#additional-resources "Direct link to Additional resources") | | | | ------------- | ------------------------------------------------------------------------------------------- | | Documentation | [Coralogix Endpoints](https://coralogix.com/docs/docs/integrations/coralogix-endpoints/.md) | | External | [GitHub](https://github.com/coralogix/custom-metrics-examples) |