Skip to main content

Additional Configurations Reference

Sumo Logic Distribution for OpenTelemetry stores the configuration for the collector in the configuration directory. It can be found here.

WindowsC:\ProgramData\Sumo Logic\OpenTelemetry Collector\config\conf.d

Configuration location and structure

The Sumo Logic OpenTelemetry Collector configuration is comprised of two parts. Based on the platform, the configuration by default is stored at the following location:

  • Linux and macOS: /etc/otelcol-sumo/
  • Windows: C:\ProgramData\Sumo Logic\OpenTelemetry Collector\config

If you manually installed the collector, your configuration may be in a different location.

Sumo Logic-defined configuration

This is required by the collector to properly communicate with Sumo Logic SaaS service, and transmit data. All Sumo Logic preconfigured components are stored in sumologic.yaml file. This file is managed by the installation script and should never be changed manually. Depending upon your platform.

Data Source configuration

Here, you can define all the configuration that tells the collector what data to collect, how to process it (including adding metadata), and send it to Sumo Logic. All the user-defined configuration resides under the conf.d directory.

Any configuration for a Source (e.g., MySQL, Nginx, Application Logs) should be stored in a separate file with descriptive name under the conf.d directory. For example, a file named conf.d/mysql.yaml can contain configuration to collect MySQL data (logs and metrics), and will contain the necessary receiver, processors and the pipeline that together inform the collector on how to collect and send the MySQL data.


It is recommended to maintain the configuration of all reusable components in conf.d/common.yaml. For example, a file named conf.d/mysql.yaml can contain the MySQL receiver along with any processors that are intended to modify the collected data before sending it to Sumo Logic.

Our App Catalog provides a mechanism to create these configuration files using a simple UI form input. Learn More.

Default Collector Name

Each collector name must be unique. Collector by default uses hostname of the machine where collector is installed as the Collector's name. By default,if you are installing a collector that would have the same hostname as an existing collector, the system automatically appends a 13-digit unix timestamp to the collector name.

Forcing a Collector's Name with Clobber

Set the clobber flag to true if you want to delete the existing collector where a new collector is installed on a machine with same hostname. This is useful for scenarios where a VM is deleted and initiated again with the same hostname. To enable this property, create a file sumo-ot-clobber.yaml in otelcol-sumo/conf.d, add below configuration and restart your collector.

clobber: true

Setting the clobber flag to true deletes (clobbers) any existing collector with the same collector name/hostname, so make sure that is what you want to do. Clobber is effective only before the new collector has been registered (activated) with Sumo Logic.

Custom Configuration

Use Custom configuration to customize the collection of your logs, metrics and traces in Sumo Logic. Learn more about configuration here.

There are some processors provided in sumologic.yaml that are intended to be used in every pipeline.

  • Memory limiter processor. It is used to prevent out-of-memory situations on the collector. It should be always first on the processor's list. For more information, refer to the OpenTelemetry documentation.
  • Batch processor. It accepts spans, metrics, or logs and places them into batches. Batching helps better compress the data and reduce the number of outgoing connections required to transmit the data. See Using batch processor to batch data for more information.
  • ResourceDetection/System processor. It can be used to detect resource information from the host in a format that conforms to the OpenTelemetry resource semantic conventions, and append or override the resource value in telemetry data with this information. You can also tag labels like,, os.type.

We also expect the Sumo Logic exporter to be included in the exporters section.

See the following example:

- otlp
- memory_limiter
- batch
- sumologic

Using Batch processor to batch data

The Batch processor can be utilized to convert the processed data into batches that are larger than a specified size or time interval. This can aid in compressing the data more effectively and minimizing the number of requests sent by the exporters.

It is highly recommended to use this processor in every pipeline. It should be defined after memory limiter processor and any processors that drop the data, such as filter processor.

In addition to setting a lower batch size, it is also possible to set a maximal batch size.

We highly recommend setting that limit to avoid sudden increases in request sizes in case more data is temporarily received. The value we recommend to set is 2 * send_batch_size.

Overall, we recommend the following default configuration for this processor.

send_batch_size: 1_024
timeout: 1s
send_batch_max_size: 2_048 ## = 2 * 1024

If you are utilizing the Sumo Logic exporter to send data in a format other than OTLP, it is possible to explicitly restrict the size of the requests in bytes by utilizing the configuration option max_request_body_size.

Learn more about these processors:

Data Tagging Recommendations

We recommend reading the Metadata Naming Conventions document before continuing to become more familiar with the terms used below. The following terms are important for data tagging:

  • Source Category (_sourceCategory)
  • Source Host (_sourceHost)
  • Source Name (_sourceName)

The above attributes are taken from the Resource attributes. If they are not set, they are taken from the collector configuration.

See the following example which shows how to set them using the Resource attributes processor:

resource/static fields:
- key: _sourceName
value: my source name
## upsert will override existing _sourceName field
action: upsert

If you would like to add your own custom metadata fields to your logs, you can use the same attributes processor and use action: insert:

- key: collection_method
value: otel
action: insert

If you are adding custom attributes to your log metadata, then you need to ensure that these fields are also added in Sumo Logic under the Logs > Fields section.

For more advanced processing capabilities in your data pipeline, you can make use of the Transform processor. This processor enables you to perform more complex transformations on your data. For example, you can concatenate multiple Resource attributes into _sourceCategory field with a / character separating each attribute.

transform/custom fields:
- context: resource
- set(attributes["_sourceCategory"], Concat([attributes[""], attributes["http.method"]], "/"))

You now have the ability to create custom tags when processing data, beyond using special tags. All resource attributes are treated as tags, offering flexibility when categorizing and processing data.

You can set default tags in collector configuration using the collector_fields option:

cluster: staging

Tags are useful for building the queries and helps to correlate the different signals (metrics, logs and traces) with each other.


Refer to the Fields documentation for more information on fields and how to use them.

Privacy Statement
Terms of Use

Copyright © 2024 by Sumo Logic, Inc.