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.github/workflows/jekyll.yml

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- name: Checkout
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uses: actions/checkout@v4
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- name: Setup Ruby
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uses: ruby/setup-ruby@472790540115ce5bd69d399a020189a8c87d641f # v1.247.0
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uses: ruby/setup-ruby@bb6434c747fa7022e12fa1cae2a0951fcffcff26 # v1.253.0
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with:
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ruby-version: '3.4.1' # Not needed with a .ruby-version file
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bundler-cache: true # runs 'bundle install' and caches installed gems automatically

docs/reference/edot-collector/config/default-config-k8s.md

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Logs and metrics are batched for better performance ([`batch`] processor) and then enriched with meta information using the [`k8sattributes`], [`resourcedetection`] and [`resource`] processors.
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:::{note}
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The `from_context: client_metadata` option in the `resource` processor only applies to transport-level metadata. It cannot extract custom application attributes.
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To propagate such values into your telemetry, set them explicitly in your application code using EDOT SDK instrumentation. For more information, refer to [EDOT Collector doesn’t propagate client metadata](docs-content://troubleshoot/ingest/opentelemetry/edot-collector/metadata.md).
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:::
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### Application telemetry through OTLP from OTel SDKs
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The Daemonset collectors also receive the application telemetry from OTel SDKs that instrument services and pods running on corresponding Kubernetes nodes.

docs/reference/edot-collector/config/default-config-standalone.md

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For logs collection, the default configuration uses the [`filelog`] receiver to read log entries from files. In addition, the [`resourcedetection`] processor enriches the log entries with metadata about the corresponding host and operating system.
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:::{note}
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The `from_context: client_metadata` option in the `resource` processor only applies to transport-level metadata. It cannot extract custom application attributes.
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To propagate such values into your telemetry, set them explicitly in your application code using EDOT SDK instrumentation. For more information, refer to [EDOT Collector doesn’t propagate client metadata](docs-content://troubleshoot/ingest/opentelemetry/edot-collector/metadata.md).
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:::
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Data is exported directly to {{es}} using the [`elasticsearch`] exporter in `OTel-native` mode.
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#### Application and traces collection pipeline

docs/reference/edot-sdks/index.md

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products:
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- id: cloud-serverless
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- id: observability
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- id: edot-sdk
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---
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# EDOT SDKs feature overview
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# EDOT SDKs
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The {{edot}} (EDOT) SDKs are production-ready, customized distributions of [OpenTelemetry](https://opentelemetry.io/) language SDKs, specifically optimized for seamless integration with Elastic Observability. EDOT SDKs provide a comprehensive observability solution that automatically captures distributed traces, metrics, and logs from your applications with minimal configuration.
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While maintaining full compatibility with the OpenTelemetry specification, EDOT SDKs provide improvements and bug fixes from Elastic before they become available in upstream OpenTelemetry repositories.
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## Supported languages
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EDOT SDKs are available for the following programming languages and platforms:
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* [.NET](/reference/edot-sdks/dotnet/index.md)
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* [Java](/reference/edot-sdks/java/index.md)
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* [Node.js](/reference/edot-sdks/nodejs/index.md)
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* [PHP](/reference/edot-sdks/php/index.md)
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* [Python](/reference/edot-sdks/python/index.md)
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* [Android](/reference/edot-sdks/android/index.md)
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* [iOS](/reference/edot-sdks/ios/index.md)
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## Feature overview
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This table provides an overview of the features available in the {{edot}} (EDOT) SDKs across different programming languages.
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* ❌ Not available
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% end:edot-features
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## Elastic support for EDOT SDKs
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## Support for EDOT SDKs
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Elastic provides technical support for EDOT Language SDKs according to Elastic's [Support Policy](https://www.elastic.co/support_policy). EDOT SDKs are meant to be used in combination with the [EDOT Collector](/reference/edot-collector/index.md) or the [{{motlp}}](/reference/motlp.md) to ingest data into Elastic solutions from the EDOT SDKs. Other ingestion paths are not officially supported by Elastic.
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