After you configure the integration, you can access these features:

• View metrics. You can create your own custom dashboards, and most monitors provide built-in dashboards as well. For information about dashboards, see View dashboards in Splunk Observability Cloud.

• View a data-driven visualization of the physical servers, virtual machines, AWS instances, and other resources in your environment that are visible to Infrastructure Monitoring. For information about navigators, see Use navigators in Splunk Infrastructure Monitoring.

• Access the Metric Finder and search for metrics sent by the monitor. For information, see Search the Metric Finder and Metadata Catalog.

Follow these steps to deploy this integration:

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

   • Install on Kubernetes

   • Install on Linux

   • Install on Windows

2. Configure the integration, as described in the Configuration section.

3. Restart the Splunk Distribution of the OpenTelemetry Collector.

To use this integration of a Smart Agent monitor with the Collector:

1. Include the Smart Agent receiver in your configuration file.

2. Add the monitor type to the Collector configuration, both in the receiver and pipelines sections.

   • See how to Use Smart Agent monitors with the Collector.

   • See how to set up the Smart Agent receiver.

   • For a list of common configuration options, refer to Common configuration settings for monitors.

   • Learn more about the Collector at Get started: Understand and use the Collector.

• To learn more about the available in Splunk Observability Cloud see Metric types.

• In host-based subscription plans, default metrics are those metrics included in host-based subscriptions in Splunk Observability Cloud, such as host, container, or bundled metrics. Custom metrics are not provided by default and might be subject to charges. See Metric categories for more information.

• In MTS-based subscription plans, all metrics are custom.

• To add additional metrics, see how to configure extraMetrics in Add additional metrics.

You’re getting a "bind: address already in use" error message

If you see an error message such as "bind: address already in use", another resource is already using the port that the current configuration requires. This resource could be another application, or a tracing tool such as Jaeger or Zipkin.

You can modify the configuration to use another port. You can modify any of these endpoints or ports:

• Receiver endpoint

• Extensions endpoint

• Metrics address (if port 8888)

If you see this error message on Kubernetes and you’re using Helm charts, modify the configuration by updating the chart values for both configuration and exposed ports.

You’re getting a "2021-10-19T20:18:40.556Z info builder/receivers_builder.go:112 Ignoring receiver as it is not used by any pipeline {"kind": "receiver", "name": "error message"

This error happens when a component (receiver, processor, or exporter) has been configured, but is not used in a receiver pipeline. For example, the following error message tells you that the smartagent/http receiver is configured, but that it is not used by any pipeline:

"2021-10-19T20:18:40.556Z info builder/receivers_builder.go:112 Ignoring receiver as it is not used by any pipeline {"kind": "receiver", "name": "smartagent/http"

Once configured, all components must be turned on by using pipelines in the service section. The service section is used to configure what components are activated based on the configuration found in the components sections of your configuration file. If a component is configured, but not defined within the service section, then it is not activated.

Here is a sample configuration:

service:
  pipelines:
  # Pipelines can contain multiple subsections, one per pipeline.
    traces:
    # Traces is the pipeline type.
      receivers: [otlp, jaeger, zipkin]
      processors: [memory_limiter, batch]
      exporters: [otlp, jaeger, zipkin]

See Process your data with pipelines for more information.

The Splunk Distribution of OpenTelemetry Collector is out of memory

If you receive high memory usage or out of memory warnings, do the following before opening a support case:

1. Verify that you have installed the latest version of the Splunk Distribution of OpenTelemetry Collector for Kubernetes.

2. Add or change the memory_limiter processor in your configuration file. For example:

   processors:
     memory_limiter:
        ballast_size_mib: 2000
        check_interval: 5s
           # Check_interval is the time between measurements of memory usage for the  purposes of avoiding goingover the limits.
           # The default is 0. Values below 1s are not recommended, as this can result in unnecessary CPU consumption.
        limit_mib: 4000
           # ​​Maximum amount of memory, in MiB, targeted to be allocated by the process heap.
           # The total memory usage of the process is typically about 50 MiB higher than this value.
        spike_limit_mib: 500
           # The maximum, in MiB, spike expected between the measurements of memory usage.
        ballast_size_mib: 2000
           # BallastSizeMiB is the size, in MiB, of the ballast size being used by the process.
           # This must match the value of the mem-ballast-size-mib command line option (if used).
           # Otherwise, the memory limiter does not work correctly.

3. Try to reproduce the error and collect a heap dump close to the point where the memory kill occurs:

   1. Add the pprof extension to the component configuration that is failing. Make sure you turned on this extension in a pipeline in the services section.

   2. Capture the output of the following commands against the problematic pod:

      curl http://127.0.0.1:1777/debug/pprof/goroutine?debug=2 (http://127.0.0.1:1777/debug/pprof/goroutine?debug=2)
      curl http://127.0.0.1:1777/debug/pprof/heap > heap.out

For example, if you discover that the pod lasts 5 minutes before it gets killed:

1. Bounce the pod and collect the first set of data after the startup.

2. Wait 3 minutes and collect another set of data. Make sure to label the data accordingly.

3. Collect another set of data before the crash, if possible.

How long does it take for the pod to be killed due to memory limit? Check the logs at the time of the issue to see if there are any obvious repeating errors.

Gather additional support information, including your end-to-end architecture information. See Gather information to open a support request

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

• Submit a case in the Splunk Support Portal.

• Contact Splunk Support.

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.