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Debugging Kibana

For information about how to debug unit tests, refer to Debugging Unit Tests.

yarn debug will start the server with Node’s inspect flag. Kibana's development mode will start three processes on ports 9229, 9230, and 9231. Chrome’s developer tools need to be configured to connect to all three connections. Add localhost:<port> for each Kibana process in Chrome’s developer tools connection tab.

Kibana has built-in OpenTelemetry instrumentation for debugging and observability. The following sections cover tracing configuration.

To enable OTel traces, apply the following configuration:

telemetry.tracing:
  enabled: true
  sample_rate: 1
  exporters:
    - proto:
        url: <URL_TO_THE_OTLP_ENDPOINT>
        headers:
          authorization: 'ApiKey [REDACTED]'
		
  1. 1 by default

The OTLP endpoint can be any OTel/EDOT collector. It is recommended to use the mOTLP (Managed OTLP) endpoint that is provided by Elastic Cloud. The instructions to retrieve the OTLP endpoint and the API Key are available in Get started with traces and APM.

Kibana supports gRPC, protobuf and plain HTTP protocols to export the OTel Traces. The protocol to use is specified in the config via top property name in the exporter's declaration. The config syntax is the same for all.

telemetry.tracing:
  enabled: true
  sample_rate: 1
  exporters:
    - grpc:
        url: <URL_TO_THE_GRPC_OTLP_ENDPOINT>
        headers:
          authorization: 'ApiKey [REDACTED]'
    - proto:
        url: <URL_TO_THE_PROTO_OTLP_ENDPOINT>
        headers:
          authorization: 'ApiKey [REDACTED]'
    - http:
        url: <URL_TO_THE_HTTP_OTLP_ENDPOINT>
        headers:
          authorization: 'ApiKey [REDACTED]'
		
  1. 1 by default
Tip

gRPC typically operates on a different port to the protobuf and http protocols.

When using the mOTLP endpoint, the port is the same, but the endpoint changes:

  • gRPC uses the root path (https://my-ech-deployment.ingest.europe-west1.gcp.elastic-cloud.com:443)
  • Protobuf and HTTP use the path /v1/traces (https://my-ech-deployment.ingest.europe-west1.gcp.elastic-cloud.com:443/v1/traces)
Important

OTel instrumentation is only available on the server side. For RUM observability, Kibana uses Elastic RUM.

OTel instrumentation in the browser will be available in the future, once the OTel for RUM is ready for production.

When telemetry.tracing.enabled is true, server-side Elastic APM is disabled by default, but the kibana-frontend (RUM) service remains active. Elastic APM and OpenTelemetry tracing cannot be enabled simultaneously; setting elastic.apm.active: true while OTel tracing is enabled causes Kibana to fail on startup. You can still collect browser traces with Elastic RUM.

To enable Elastic RUM alongside OTel tracing, define the APM Server's URL in the Kibana config. Any settings accepted by the agent are also accepted:

elastic:
  apm:
    serverUrl: https://my-ech-deployment.apm.europe-west1.gcp.cloud.es.io:443
    # RUM is enabled by default when telemetry.tracing.enabled is true; serverUrl is required to send data to your deployment.
    # Below are optional
    environment: localhost
    transactionSampleRate: 1
		
Tip

RUM sends traces from the browser without embedded credentials. Prefer an Elastic Cloud Hosted (ECH) APM endpoint configured for RUM intake. Serverless APM endpoints often require authenticated intake and are usually not suitable for RUM unless your deployment explicitly supports unauthenticated browser intake.

Warning

This approach is deprecated. Use OTel Traces instead.

Kibana ships with the Elastic APM Node.js Agent built-in for debugging purposes.

With an application as varied and complex as Kibana has become, it’s not practical or scalable to craft all possible performance measurements by hand ahead of time. As such, we need to rely on tooling to help us catch things we might otherwise have missed.

For example, say you implement a brand new feature, plugin or service but do not know how it will impact Kibana’s performance as a whole. APM allows us to not only spot that something is slow, but also hints at why it might be performing slowly. For example, if a function is slow on specific types of inputs, we can see where the time is spent by viewing the trace for that function call in the APM UI.

apm example trace

The net of metrics captured by APM are both a wide and deep because the entire application is instrumented at runtime and we simply take a sample of these metrics. This means that we don’t have to know what we need to measure ahead of time, we’ll instead just get (most) of the data we’re likely going to need by default.

This type of data can help us identify unknown bottlenecks, spot when a performance regression may have been introduced, and inform how the performance of Kibana is changing between releases. Using APM allows us to be proactive in getting ahead of potential performance regressions before they are released.

The default APM configuration is meant to be used by core Kibana developers only, but it can easily be re-configured to your needs. In its default configuration it’s disabled and will, once enabled, send APM data to a centrally managed Elasticsearch cluster accessible only to Elastic employees.

To change the location where data is sent, use the serverUrl APM config option. To activate the APM agent, use the active APM config option.

All config options can be set by creating an appropriate config file under config/kibana.dev.yml.

Example config/kibana.dev.yml file:

elastic:
  apm:
    active: true
		

APM Real User Monitoring agent is not available in the Kibana distributables, however the agent can be enabled by setting ELASTIC_APM_ACTIVE to true. flags

ELASTIC_APM_ACTIVE=true yarn start
// activates both Node.js and RUM agent
		

Once the agent is active, it will trace all incoming HTTP requests to Kibana, monitor for errors, and collect process-level metrics. The collected data will be sent to the APM Server and is viewable in the APM UI in Kibana.

The easiest and recommended way of running Kibana with the APM agent locally is to use the solution provided by the apm-integration-testing repo. You’ll need Docker, Docker Compose and Python (version 3 preferred) to use the tool.

  1. Clone the elastic/apm-integration-testing repo.

  2. Change into the apm-integration-testing repo:

    cd apm-integration-testing
    		
  3. Run Elasticsearch and the APM servers without running Kibana:

    ./scripts/compose.py start master --no-kibana
    		
  4. Clone the elastic/kibana repo.

  5. Change into the Kibana repo:

    cd ../kibana
    		
  6. Change the elasticsearch credentials in your kibana.yml configuration file to match those needed by elasticsearch and the APM server (see the apm-integration-testing repo’s README for users provided to test different scenarios).

  7. Make sure that the APM agent is active and points to the local APM server by adding the following configuration settings to a config file under config/kibana.dev.yml:

    Example config/kibana.dev.yml file:

    elastic:
      apm:
        active: true
        serverUrl: http://localhost:8200
        secretToken: very_secret
        centralConfig: true
        breakdownMetrics: true
        transactionSampleRate: 0.1
    		
  8. Start Kibana with APM active using:

    yarn start
    		
  9. After Kibana starts up, navigate to the APM app, where you should see some transactions.

apm ui transactions

You can now continue doing what you want to in Kibana (e.g. install sample data sets, issue queries in dashboards, build new visualizations etc). Once you’re finished, you can stop Kibana normally, then stop the Elasticsearch and APM servers in the apm-integration-testing clone with the following script:

./scripts/compose.py stop