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manage-data/data-store.md

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Then, learn how these documents and the fields they contain are stored and indexed in [Mapping](/manage-data/data-store/mapping.md), and how unstructured text is converted into a structured format that’s optimized for search in [Text analysis](/manage-data/data-store/text-analysis.md).
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You can also read more about working with {{es}} as a data store including how to use [index templates](/manage-data/data-store/templates.md) to tell {{es}} how to configure an index when it is created, how to use [aliases](/manage-data/data-store/aliases.md) to point to multiple indices, and how to use the [command line to manage data](/manage-data/data-store/manage-data-from-the-command-line.md) stored in {{es}}.
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You can also read more about working with {{es}} as a data store including how to use [index templates](/manage-data/data-store/templates.md) to tell {{es}} how to configure an index when it is created, how to use [aliases](/manage-data/data-store/aliases.md) to point to multiple indices, and how to use the [command line to manage data](/manage-data/data-store/manage-data-from-the-command-line.md) stored in {{es}}.
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If your use case involves working with continuous streams of time series data, you may consider using a [data stream](./data-store/data-streams.md). These are optimally suited for storing append-only data. The data can be accessed through a single, named resource, while it is stored in a series of hidden, auto-generated backing indices.

manage-data/data-store/index-types.md

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manage-data/toc.yml

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- file: data-store.md
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- file: data-store/index-basics.md
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- file: data-store/index-types.md
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- file: data-store/data-streams.md
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- file: data-store/data-streams/set-up-data-stream.md
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- file: data-store/data-streams/run-downsampling-manually.md
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- file: data-store/data-streams/run-downsampling-using-data-stream-lifecycle.md
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- file: data-store/data-streams/reindex-tsds.md
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- file: data-store/data-streams/logs-data-stream.md
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- file: data-store/data-streams/logs-data-stream.md
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- file: data-store/mapping.md
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- file: data-store/mapping/dynamic-mapping.md

raw-migrated-files/docs-content/serverless/observability-apm-agents-opentelemetry-opentelemetry-native-support.md

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Elastic natively supports the OpenTelemetry protocol (OTLP). This means trace data and metrics collected from your applications and infrastructure can be sent directly to Elastic.
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* Send data to Elastic from an upstream [OpenTelemetry Collector](../../../solutions/observability/apps/upstream-opentelemetry-collectors-language-sdks.md#observability-apm-agents-opentelemetry-opentelemetry-native-support-send-data-from-an-upstream-opentelemetry-collector)
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* Send data to Elastic from an upstream [OpenTelemetry language SDK](../../../solutions/observability/apps/upstream-opentelemetry-collectors-language-sdks.md#observability-apm-agents-opentelemetry-opentelemetry-native-support-send-data-from-an-upstream-opentelemetry-sdk)
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* Send data to Elastic from an upstream [OpenTelemetry Collector](../../../solutions/observability/apps/upstream-opentelemetry-collectors-language-sdks.md)
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* Send data to Elastic from an upstream [OpenTelemetry language SDK](../../../solutions/observability/apps/upstream-opentelemetry-collectors-language-sdks.md)
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## Send data from an upstream OpenTelemetry Collector [observability-apm-agents-opentelemetry-opentelemetry-native-support-send-data-from-an-upstream-opentelemetry-collector]
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`OTEL_EXPORTER_OTLP_HEADERS`
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: Authorization header that includes the Elastic APM API key: `"Authorization=ApiKey an_api_key"`. Note the required space between `ApiKey` and `an_api_key`.
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For information on how to format an API key, refer to [Secure communication with APM agents](../../../solutions/observability/apps/use-apm-securely.md#observability-apm-keep-data-secure-secure-communication-with-apm-agents).
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For information on how to format an API key, refer to [Secure communication with APM agents](../../../solutions/observability/apps/use-apm-securely.md).
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If you are using a version of the Python OpenTelemetry agent *before* 1.27.0, the content of the header *must* be URL-encoded. You can use the Python standard library’s `urllib.parse.quote` function to encode the content of the header.
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You are now ready to collect traces and [metrics](../../../solutions/observability/apps/collect-metrics.md) before [verifying metrics](../../../solutions/observability/apps/collect-metrics.md#open-telemetry-verify-metrics) and [visualizing metrics](../../../solutions/observability/apps/collect-metrics.md#open-telemetry-visualize).
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You are now ready to collect traces and [metrics](../../../solutions/observability/apps/collect-metrics.md) before [verifying metrics](../../../solutions/observability/apps/collect-metrics.md#apm-open-telemetry-verify-metrics) and [visualizing metrics](../../../solutions/observability/apps/collect-metrics.md#apm-open-telemetry-visualize).
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## Proxy requests to Elastic [observability-apm-agents-opentelemetry-opentelemetry-native-support-proxy-requests-to-elastic]

raw-migrated-files/docs-content/serverless/observability-apm-agents-opentelemetry.md

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Elastic integrates with OpenTelemetry, allowing you to reuse your existing instrumentation to easily send observability data to the Elastic Stack. There are several ways to integrate OpenTelemetry with the Elastic Stack:
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* [Elastic Distributions of OpenTelemetry language SDKs](../../../solutions/observability/apps/use-opentelemetry-with-apm.md#observability-apm-agents-opentelemetry-elastic-distributions-of-opentelemetry-language-sdks)
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* [Upstream OpenTelemetry API/SDK + Elastic APM agent](../../../solutions/observability/apps/use-opentelemetry-with-apm.md#observability-apm-agents-opentelemetry-upstream-opentelemetry-apisdk-elastic-apm-agent)
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* [Upstream OpenTelemetry Collector and language SDKs](../../../solutions/observability/apps/use-opentelemetry-with-apm.md#observability-apm-agents-opentelemetry-upstream-opentelemetry-collector-and-language-sdks)
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* [AWS Lambda collector exporter](../../../solutions/observability/apps/use-opentelemetry-with-apm.md#observability-apm-agents-opentelemetry-aws-lambda-collector-exporter)
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* [Elastic Distributions of OpenTelemetry language SDKs](../../../solutions/observability/apps/use-opentelemetry-with-apm.md)
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* [Upstream OpenTelemetry API/SDK + Elastic APM agent](../../../solutions/observability/apps/use-opentelemetry-with-apm.md)
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* [Upstream OpenTelemetry Collector and language SDKs](../../../solutions/observability/apps/use-opentelemetry-with-apm.md)
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* [AWS Lambda collector exporter](../../../solutions/observability/apps/use-opentelemetry-with-apm.md)
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## Elastic Distributions of OpenTelemetry language SDKs [observability-apm-agents-opentelemetry-elastic-distributions-of-opentelemetry-language-sdks]

raw-migrated-files/docs-content/serverless/observability-apm-create-custom-links.md

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Elastic’s custom link feature allows you to easily create up to 500 dynamic links based on your specific APM data. Custom links can be filtered to only appear for relevant services, environments, transaction types, or transaction names.
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Ready to dive in? Jump straight to the [examples](../../../solutions/observability/apps/create-custom-links.md#observability-apm-create-custom-links-custom-link-examples).
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Ready to dive in? Jump straight to the [examples](../../../solutions/observability/apps/create-custom-links.md).
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## Create a link [observability-apm-create-custom-links-create-a-link]

raw-migrated-files/docs-content/serverless/observability-apm-dependencies.md

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# Dependencies [observability-apm-dependencies]
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APM agents collect details about external calls made from instrumented services. Sometimes, these external calls resolve into a downstream service that’s instrumented — in these cases, you can utilize [distributed tracing](../../../solutions/observability/apps/trace-sample-timeline.md#observability-apm-trace-sample-timeline-distributed-tracing) to drill down into problematic downstream services. Other times, though, it’s not possible to instrument a downstream dependency — like with a database or third-party service. **Dependencies** gives you a window into these uninstrumented, downstream dependencies.
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APM agents collect details about external calls made from instrumented services. Sometimes, these external calls resolve into a downstream service that’s instrumented — in these cases, you can utilize [distributed tracing](../../../solutions/observability/apps/trace-sample-timeline.md) to drill down into problematic downstream services. Other times, though, it’s not possible to instrument a downstream dependency — like with a database or third-party service. **Dependencies** gives you a window into these uninstrumented, downstream dependencies.
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:alt: Dependencies view in the Applications UI

raw-migrated-files/docs-content/serverless/observability-apm-observe-lambda-functions.md

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### Latency distribution correlation [observability-apm-observe-lambda-functions-latency-distribution-correlation]
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The [latency correlations](../../../solutions/observability/apps/find-transaction-latency-failure-correlations.md#observability-apm-find-transaction-latency-and-failure-correlations-find-high-transaction-latency-correlations) feature can be used to visualize the impact of Lambda cold starts on latency—just select the `faas.coldstart` field.
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The [latency correlations](../../../solutions/observability/apps/find-transaction-latency-failure-correlations.md) feature can be used to visualize the impact of Lambda cold starts on latency—just select the `faas.coldstart` field.
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## AWS Lambda function grouping [observability-apm-observe-lambda-functions-aws-lambda-function-grouping]

raw-migrated-files/docs-content/serverless/observability-apm-service-overview.md

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The cold start rate chart is specific to serverless services, and displays the percentage of requests that trigger a cold start of a serverless function. A cold start occurs when a serverless function has not been used for a certain period of time. Analyzing the cold start rate can be useful for deciding how much memory to allocate to a function, or when to remove a large dependency.
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The cold start rate chart is currently supported for [AWS Lambda](../../../solutions/observability/apps/observe-lambda-functions.md#observability-apm-observe-lambda-functions-cold-starts) functions and Azure functions.
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The cold start rate chart is currently supported for [AWS Lambda](../../../solutions/observability/apps/observe-lambda-functions.md#apm-lambda-cold-start-info) functions and Azure functions.
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## Instances [observability-apm-service-overview-instances]

raw-migrated-files/docs-content/serverless/observability-apm-traces.md

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**Traces** displays your application’s entry (root) transactions. Transactions with the same name are grouped together and only shown once in this table. If you’re using [distributed tracing](../../../solutions/observability/apps/trace-sample-timeline.md#observability-apm-trace-sample-timeline-distributed-tracing), this view is key to finding the critical paths within your application.
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**Traces** displays your application’s entry (root) transactions. Transactions with the same name are grouped together and only shown once in this table. If you’re using [distributed tracing](../../../solutions/observability/apps/trace-sample-timeline.md), this view is key to finding the critical paths within your application.
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By default, transactions are sorted by *Impact*. Impact helps show the most used and slowest endpoints in your service — in other words, it’s the collective amount of pain a specific endpoint is causing your users. If there’s a particular endpoint you’re worried about, select it to view its [transaction details](../../../solutions/observability/apps/transactions-2.md#transaction-details).
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