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The OpenTelemetry Collector offers a vendor-agnostic way to gather observability data from a variety of instrumentation solutions and send that data to Honeycomb. Applications instrumented with OpenTelemetry SDKs or with Jaeger or Zipkin can use the OpenTelemetry Collector to send trace data to Honeycomb as events. Additionally, applications instrumented with OpenTelemetry SDKs or with metrics data from Prometheus, StatsD, Influx, and others can use the OpenTelemetry Collector to send metrics data to Honeycomb. A Collector can be used with any number of applications, and by default all OpenTelemetry SDK’s export telemetry to the Collector OTLP endpoint. Using a Collector allows for experimenting and setting up new instrumentation, as well as exporting to multiple backends that may include Honeycomb or even another Collector. A Collector can also help by offloading data and processing telemetry before it is sent on, using various processors for batching, transforming, and filtering data. Honeycomb supports receiving telemetry data via OpenTelemetry’s native protocol, OTLP, over gRPC, HTTP/protobuf, and HTTP/JSON. The minimum supported versions of OTLP protobuf definitions are 1.0 for traces, metrics, and logs. This means you can use the OpenTelemetry Collector and its standard OTLP exporter to send data to Honeycomb without any additional exporters or plugins. To send trace data to Honeycomb, configure an OTLP exporter with the Honeycomb API Key as a header, and include the exporter in the relevant pipeline: 
exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"

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Basic Configuration

The Collector consists of three components: receivers, processors, and exporters, which are then used to construct telemetry pipelines. To configure the components for the Collector, create a file called otel-collector-config.yaml.

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Receivers

Add receivers for OTLP trace output from applications instrumented with OpenTelemetry: 
receivers:

  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

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Processors

Include a batch processor to batch telemetry before sending to Honeycomb: 
processors:
  batch:

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Exporters

Configure an OTLP exporter with the Honeycomb API Key as a header: 
exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"

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Service Pipelines

Finally, configure a service pipeline for traces: 
service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]

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Full Configuration File For Basic Usage

The final result of adding receivers, processors, exporters, and pipelines will look like this: 
# otel-collector-config.yaml
receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

processors:
  batch:

exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]
If you are a Honeycomb Classic user, the Dataset also must be specified using the x-honeycomb-dataset header in the exporters section, in the line below the x-honeycomb-team. A Dataset is a bucket where data gets stored in Honeycomb.
exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
      "x-honeycomb-dataset": "YOUR_DATASET"

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Metrics and Logs Signals

The Collector can handle OTLP metrics and logs signals in addition to traces. Metrics require a dataset in the exporter. Logs will use the service.name associated with the trace from which it originated, or a dataset if provided. It is possible to send these to the same or to multiple places in Honeycomb. To set a different pipeline with the same type of exporter, append the exporter with /my-pipeline. The following example exports OTLP application metrics to a specified dataset, and exports logs to the same place as traces. 
receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

processors:
  batch:

exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
  otlp/metrics:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
      "x-honeycomb-dataset": "YOUR_METRICS_DATASET"

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp/metrics]
    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]

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Browser Telemetry

To receive browser telemetry, the Collector requires an enabled OTLP/HTTP receiver. The allowed_origins property is required to enable Cross-Origin Resource Sharing (CORS) from the browser to the collector. The Collector will need to be accessible by the browser. It is recommended to put an external load balancer in front of the collector, which will also need to be configured to accept requests from the browser origin. You can also configure the Collector to symbolicate your JavaScript stack traces. This translates obfuscated or minified names from your stack traces into human-readable formats. In the example below, the configuration allows for the OpenTelemetry Collector to accept browser OpenTelemetry tracing, and is required to get data from the browser to Honeycomb. 
receivers:
  otlp:
    protocols:
      http:
        endpoint: 0.0.0.0:4318
        cors:
          allowed_origins:
            - "http://*.<yourdomain>.com"
            - "https://*.<yourdomain>.com"

processors:
  batch:

exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp]
More configuration options can be found on the Collector Github Repository.
If you are a Honeycomb Classic user, the Dataset also must be specified using the x-honeycomb-dataset header in the exporters section, in the line below the x-honeycomb-team. A Dataset is a bucket where data gets stored in Honeycomb.
exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
      "x-honeycomb-dataset": "YOUR_DATASET"
Find out more about setting up browser instrumentation.

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Symbolicate Web, iOS, Android, and React Native stack traces

Honeycomb provides several Collector processors for symbolicating stack traces from your browser, iOS, Android, and React Native applications. This gives you human-readable errors and stack traces in your frontend launchpad’s Errors UI. For tutorials on setting up these processors, check out:

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Advanced Configuration

The Collector can receive telemetry from different applications in different formats, and also export to multiple backends. Image of otel collector from opentelemetry.io, showing receivers, extensions, processors, and exporters The following is a complete configuration file example for a Collector instance that accepts Jaeger and OpenTelemetry (over gRPC and HTTP) trace data, as well as Prometheus metrics. This example includes the batch processor and several extensions, and exports both trace and metric data to Honeycomb: 
receivers:
  jaeger:
    protocols:
      thrift_http:
        endpoint: "0.0.0.0:14268"
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318
  prometheus:
    config:
      scrape_configs:
        - job_name: "prometheus"
          scrape_interval: 15s
          static_configs:
            - targets: ["0.0.0.0:9100"]

processors:
  batch:

exporters:
  otlp:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
  otlp/metrics:
    endpoint: "api.honeycomb.io:443" # US instance
    #endpoint: "api.eu1.honeycomb.io:443" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"
      "x-honeycomb-dataset": "YOUR_METRICS_DATASET"

extensions:
  health_check:
    endpoint: 0.0.0.0:13133
  pprof:
  zpages:

service:
  extensions: [health_check, pprof, zpages]
  pipelines:
    traces:
      receivers: [jaeger, otlp]
      processors: [batch]
      exporters: [otlp]
    metrics:
      receivers: [prometheus]
      processors: []
      exporters: [otlp/metrics]
See the Collector documentation for more configuration options.

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Using HTTP/protobuf Instead of gRPC

The otlp exporter uses the gRPC protocol to send telemetry data. To use HTTP/protobuf instead of gRPC, use the otlphttp exporter, update the endpoint, and update the pipeline: 
receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

exporters:
  otlphttp:
    endpoint: "https://api.honeycomb.io" # US instance
    #endpoint: "https://api.eu1.honeycomb.io" # EU instance
    headers:
      "x-honeycomb-team": "YOUR_API_KEY"

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: []
      exporters: [otlphttp]

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Running the Collector

You can run the Collector in Docker to try it out locally. This is needed when adding instrumentation in development to send events to Honeycomb. For instance, if your configuration file is called otel_collector_config.yaml in the current working directory, the following command will run the Collector with open ports for sending OTLP protocol: 
docker run \
  -p 14268:14268 \
  -p 4317-4318:4317-4318 \
  -v $(pwd)/otel_collector_config.yaml:/etc/otelcol-contrib/config.yaml \
  ghcr.io/open-telemetry/opentelemetry-collector-releases/opentelemetry-collector-contrib:latest
When using the core collector image, which includes a more limited set of components, the configuration and image files will be slightly different: 
docker run \
  -p 14268:14268 \
  -p 4317-4318:4317-4318 \
  -v $(pwd)/otel_collector_config.yaml:/etc/otelcol/config.yaml \
  ghcr.io/open-telemetry/opentelemetry-collector-releases/opentelemetry-collector:latest
More details on running the Collector can be found in its documentation.

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Collector Deployment Patterns

There are various deployment patterns that can be considered for different use cases. We cover the two most common deployment patterns here.

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Gateway Mode

A Collector running in Gateway mode is a Collector instance running as a standalone service (for example, container or deployment), typically per cluster, data center, or region. You can then export telemetry data from this collector instance to one or more backends like Honeycomb. Diagram showing instrumented app to collector to honeycomb

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When to deploy the Collector in Gateway Mode

Deploy the Collector in Gateway Mode when:
  • You want to run a standalone collector deployment with configuration enforced by a central team, such as attribute redaction
  • You need to provide an API key or authentication for your exporters while also limiting egress points
  • You want to use the clustermetrics receiver to collect cluster-level metrics
You can scale the collector in gateway mode horizontally or vertically by running several instances of the collector behind a load balancer.

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Agent Mode

A Collector instance running in agent mode runs alongside the application or on the same host as the application. For example, binary, sidecar, or daemonset. Telemetry data from the collector instance (or multiple instances) can then be sent to a central collector to export to Honeycomb or directly to Honeycomb. Diagram showing sidecar collectors to central collector to honeycomb

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When to deploy the Collector in Agent Mode

Deploy the Collector in Agent Mode when:
  • You need to run the collector close to the application. When sending data to Honeycomb, this offloads the work of batching, retrying, and queuing from your application.
  • You need to reduce inter-node traffic within your cluster.
  • Different applications need different collector configurations. For example, you may want to use the k8sattributes processor, which adds metadata attributes to spans, metrics, and logs. These attributes can make it easier to correlate data in Honeycomb
  • You want to use the hostmetrics scraper to collect host metrics
Review the Collector Deployment documentation for more details on deployment options.

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Filtering Span Events and Other Data

If using version v0.66.0 (or higher) of the OpenTelemetry Collector-Contrib distribution, use the filterprocessor to filter Span Events or any other data before sending it to Honeycomb. The filterprocessor component can be especially helpful if using instrumentations that create a lot of noisy, unneeded data. To use, add the filterprocessor component as a processor in your OpenTelemetry Collector configuration file, such as otel-collector-config.yaml. Configure your OpenTelemetry Collector to filter Span Events, similar to: 
processors:
  # add the filterprocessor
  filter:
    #  tell it to operate on span data
    traces:
      # Filter out span events with the 'grpc' attribute,
      # or have a span event name with 'grpc' in it.
      spanevent:
        - 'attributes["grpc"] == true'
        - 'IsMatch(name, ".*grpc.*") == true'
Note that each individual line in the spanevent list is a separate filter. If any of the filters match, the span event will be filtered out. In other words, each line is an OR condition. Additionally, Honeycomb currently translates all fields with the instrumentation_scope.name field into library.name. To filter based on the value of an instrumentation scope, use instrumentation_scope.name instead of library.name. To require multiple conditions to be true, write a single filter that combines them, similar to: 
processors:
  filter:
    traces:
      # Filter out only span events with both the 'grpc' attribute and
      # that have a span event name with 'grpc' in it.
      spanevent:
        - 'attributes["grpc"] == true and IsMatch(name, ".*grpc.*") == true'
You can filter any OpenTelemetry signals, not only Span Events. This example filters data across spans, metrics, and logs: 
processors:
  filter:
    traces:
      span:
        - 'attributes["container.name"] == "app_container_1"'
        - 'resource.attributes["host.name"] == "localhost"'
        - 'name == "app_3"'
      spanevent:
        - 'attributes["grpc"] == true'
        - 'IsMatch(name, ".*grpc.*") == true'
    metrics:
      metric:
          - 'name == "my.metric" and attributes["my_label"] == "abc123"'
          - 'type == METRIC_DATA_TYPE_HISTOGRAM'
      datapoint:
          - 'metric.type == METRIC_DATA_TYPE_SUMMARY'
          - 'resource.attributes["service.name"] == "my_service_name"'
    logs:
      log_record:
        - 'IsMatch(body, ".*password.*") == true'
        - 'severity_number < SEVERITY_NUMBER_WARN'
The filtering language is done with the OpenTelemetry Transformation Language (OTTL). Learn more about the OTTL Processor.

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Scrubbing Sensitive Information

Sometimes you want to make sure that certain information does not escape your application or service. This could be for regulatory reasons regarding personally identifiable information, or you want to ensure that certain information does not end being stored with a vendor. Scrubbing attributes from a span is possible with the built-in Attributes Span Processor. Span processors in OpenTelemetry allow you to hook into the lifecycle of a span and modify the span contents before sending to a backend. The Attributes Span Processor can be configured with actions, and specifically the delete action can be used to remove span attributes. There are other actions that could be used, such as upsert to replace the value or hash to encrypt the value with a SHA1 hash. 
processors:
  attributes:
    actions:
      - key: my.sensitive.data
        action: delete

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Handling Large Requests

If request sizes are too large, there will be an error when trying to send to Honeycomb. The request size limit is 15MB. To help mitigate errors for requests being too large, it is recommended to set a limit on the batch size and use compression when exporting to Honeycomb.

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Configuring Max Batch Size

A Batch Processor has a configuration option for send_batch_size and send_batch_max_size. These options specify the number of data points, regardless of size, to include in a batch to be sent. A one-size-fits-all value does not exist for each of these, since different requests will vary in size. However, these are worth tuning to find the right limit to ensure data is being sent reliably.

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Enabling Compression

Collector exporters have configuration options to enable compression, including for both gRPC and HTTP. Current supported compression types include gzip, snappy, and zstd.

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Replacing the Old Honeycomb-Specific Exporter

Because Honeycomb supports OTLP, the old Honeycomb-specific exporter is no longer required and is no longer available in current versions of the Collector. The built-in OTLP exporter should be used instead to send trace data to Honeycomb.

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Choosing between gRPC and HTTP

Most OpenTelemetry SDKs have an option to export telemetry as OTLP either over gRPC or HTTP/protobuf, with some also offering HTTP/JSON. If you are trying to choose between gRPC and HTTP, keep in mind:
  • Some SDKs default to using gRPC, and it may be easiest to start with the default option.
  • Some firewall policies are not set up to handle gRPC and require using HTTP.
  • gRPC may improve performance, but its long-lived connections may cause problems with load balancing, especially when using Refinery.
gRPC default export uses port 4317, whereas HTTP default export uses port 4318.

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Troubleshooting

To explore common issues when sending data, visit Common Issues with Sending Data in Honeycomb.