Docs » Supported integrations in Splunk Observability Cloud » Collector components: Receivers » Kafka receiver

Kafka receiver 🔗

The Kafka receiver allows the Splunk Distribution of the OpenTelemetry Collector to collect metrics and logs (in OTLP format), and traces, from Kafka. Message payload encoding is configurable. The supported pipeline types are metrics, logs, and traces. See Process your data with pipelines for more information.

Note

Out-of-the-box dashboards and navigators aren’t supported for the Kafka receiver yet, but are planned for a future release.

Get started 🔗

Follow these steps to configure and activate the component:

  1. Deploy the Splunk Distribution of the OpenTelemetry Collector to your host or container platform:

  2. Configure the Kafka receiver as described in the next section.

  3. Restart the Collector.

Sample configuration 🔗

To activate the receiver, add kafka to the receivers section of your configuration file:

receivers:
  kafka:
    protocol_version: 2.0.0

To complete the configuration, include the receiver in one or more pipelines of the service section of your configuration file. For example:

service:
  pipelines:
    metrics:
      receivers: [kafka]

Main settings 🔗

The following setting is required:

  • protocol_version. The Kafka protocol version, for example 2.0.0.

The following settings are optional:

  • brokers. localhost:9092 by default. The list of Kafka brokers.

  • resolve_canonical_bootstrap_servers_only. false by default. Whether to resolve then reverse-lookup broker IPs during startup.

  • topic. Defaults: otlp_spans for traces, otlp_metrics for metrics, otlp_logs for logs. The name of the Kafka topic to read from. You can only use one telemetry type for a given topic.

  • encoding. otlp_proto by default. The encoding of the payload received from Kafka. The following encodings are available :

    • otlp_proto. The payload is deserialized to ExportTraceServiceRequest, ExportLogsServiceRequest or ExportMetricsServiceRequest respectively.

    • jaeger_proto. The payload is deserialized to a single Jaeger proto Span.

    • jaeger_json. The payload is deserialized to a single Jaeger JSON Span using jsonpb.

    • zipkin_proto. The payload is deserialized into a list of Zipkin proto spans.

    • zipkin_json. The payload is deserialized into a list of Zipkin V2 JSON spans.

    • zipkin_thrift. The payload is deserialized into a list of Zipkin Thrift spans.

    • raw``. Only for logs. The payload’s bytes are inserted as the body of a log record.

    • text. Only for logs. The payload is decoded as text and inserted as the body of a log record. By default, it uses UTF-8 to decode. You can use text_<ENCODING>, such as text_utf-8 or text_shift_jis, to customize this behavior.

    • json. Only for logs. The payload is decoded as JSON and inserted as the body of a log record.

    • azure_resource_logs. Only for logs. The payload is converted from Azure Resource Logs format to OTLP.

  • group_id. otel-collector by default. The consumer group the receiver consumes messages from.

  • client_id. otel-collector by default. The consumer client ID.

  • initial_offset. latest by default. The initial offset to use if no offset was previously committed. Possible values are latest or earliest.

  • auth. You can use the following options to authenticate:

    • plain_text. It has the following fields:

      • username. The username to use.

      • password. The password to use.

    • sasl. It has the following fields:

      • username. The username to use.

      • password. The password to use.

      • mechanism. The SASL mechanism to use: SCRAM-SHA-256, SCRAM-SHA-512, AWS_MSK_IAM or PLAIN.

      • aws_msk.region. If using AWS_MSK_IAM, AWS region.

      • aws_msk.broker_addr. If using AWS_MSK_IAM, MSK broker address.

    • tls. It has the following fields:

      • ca_file. Use only if insecure is set to false. Path to the CA cert. For a client it verifies the server certificate.

      • cert_file. Use only if insecure is set to false. Path to the TLS cert to use for TLS required connections.

      • key_file. Use only if insecure is set to false. Path to the TLS key to use for TLS required connections.

      • insecure. false by default. Disables the verification of the server’s certificate chain and host name, InsecureSkipVerify in the tls configuration.

      • server_name_override. Indicates the name of the server requested by the client in order to support virtual hosting.

    • kerberos. It has the following fields:

      • service_name. Kerberos service name.

      • realm. Kerberos realm.

      • use_keytab. If true, the keytab is used instead of the password.

      • username. The Kerberos username used to authenticate with KDC.

      • password. The Kerberos password used to authenticate with KDC.

      • config_file. Path to Kerberos configuration, for example /etc/krb5.conf.

      • keytab_file. Path to the keytab file, for example /etc/security/kafka.keytab.

      • disable_fast_negotiation. false by default. Disables the PA-FX-FAST negotiation (Pre-Authentication Framework - Fast). Some common Kerberos implementations do not support PA-FX-FAST negotiation.

  • metadata. It has the following fields:

    • full. true by default. Whether to maintain a full set of metadata. When disabled, the client does not make the initial request to broker at the startup.

    • retry. It has the following fields:

      • max. 3 by default. The number of retries to get metadata.

      • backoff. 250ms by default. How long to wait between metadata retries.

  • autocommit. It has the following fields:

    • enable. true by default. Whether or not to auto-commit updated offsets back to the broker.

    • interval. 1s by default. How frequently to commit updated offsets. Ineffective unless auto-commit is enabled.

  • message_marking. It has the following fields:

    • after. false by default. If true, the messages are marked after the pipeline is executed.

    • on_error. false by default. If false, only the successfully processed messages are marked. Note that this can block the entire partition in case a processed message returns a permanent error.

  • header_extraction. Determines how to extract headers. It has the following fields:

    • extract_headers. false by default. If true, header fields are attached to resource attributes.

    • headers. [] by default. List of headers you want to extract from the Kafka records. The matching pattern is exact. Regexes are not supported for the moment.

Configuration example: Connect to Kafka using SASL and TLS 🔗

This is an example of how to configure the receiver to connect to Kafka using SASL and TLS:

receivers:
  kafka:
    auth:
      sasl:
        username: "user"
        password: "secret"
        mechanism: "SCRAM-SHA-512"
      tls:
        insecure: false

Configuration example: Extract headers 🔗

This is an example of how to configure the receiver to extract headers:

receivers:
  kafka:
    topic: test
    header_extraction:
      extract_headers: true
      headers: ["header1", "header2"]

If you feed the receiver the following test:

{
  event: Hello,
  headers: {
    header1: value1,
    header2: value2,
  }
}

You’ll obtain the following log record:

{
  ...
  body: Hello,
  resource: {
    kafka.header.header1: value1,
    kafka.header.header2: value2,
  },
  ...
}

The following applies:

  • Kafka record headers header1 and header2 are added to the resource’s attributes.

  • Every matching Kafka header key is prefixed with the kafka.header string and attached to the resource’s attributes.

Settings 🔗

The following table shows the configuration options for the Kafka receiver:

Troubleshooting 🔗

If you are a Splunk Observability Cloud customer and are not able to see your data in Splunk Observability Cloud, you can get help in the following ways.

Available to Splunk Observability Cloud customers

Available to prospective customers and free trial users

  • Ask a question and get answers through community support at Splunk Answers .

  • Join the Splunk #observability user group Slack channel to communicate with customers, partners, and Splunk employees worldwide. To join, see Chat groups in the Get Started with Splunk Community manual.

This page was last updated on Dec 12, 2024.