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Copy file name to clipboardExpand all lines: docs/sources/tempo/configuration/_index.md
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-[Usage-report](#usage-report)
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-[Cache](#cache)
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Additionally, you can review [TLS]({{< relref "./network/tls" >}}) to configure the cluster components to communicate over TLS, or receive traces over TLS.
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Additionally, you can review [TLS](network/tls/) to configure the cluster components to communicate over TLS, or receive traces over TLS.
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## Use environment variables in the configuration
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For more information on configuration options, refer to [this file](https://github.com/grafana/tempo/blob/main/modules/generator/config.go).
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The metrics-generator processes spans and write metrics using the Prometheus remote write protocol.
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For more information on the metrics-generator, refer to the [Metrics-generator documentation]({{< relref "../metrics-generator" >}}).
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For more information on the metrics-generator, refer to the [Metrics-generator documentation](../metrics-generator/).
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Metrics-generator processors are disabled by default. To enable it for a specific tenant, set `metrics_generator.processors` in the [overrides](#overrides) section.
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The following example shows common options.
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For further platform-specific information, refer to the following:
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Automatic logging writes well formatted log lines to help with trace discovery.
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For a closer look into the feature, visit [Automatic logging]({{< relref "./automatic-logging" >}}).
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For a closer look into the feature, visit [Automatic logging](automatic-logging/).
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#### Tail-based sampling
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The Agent implements tail-based sampling for distributed tracing systems and multi-instance Agent deployments.
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With this feature, sampling decisions can be made based on data from a trace, rather than exclusively with probabilistic methods.
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For a detailed description, go to [Tail-based sampling]({{< relref "./tail-based-sampling" >}}).
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For a detailed description, go to [Tail-based sampling](tail-based-sampling/).
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For additional information, refer to the blog post, [An introduction to trace sampling with Grafana Tempo and Grafana Agent](/blog/2022/05/11/an-introduction-to-trace-sampling-with-grafana-tempo-and-grafana-agent).
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#### Generating metrics from spans
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The Agent can take advantage of the span data flowing through the pipeline to generate Prometheus metrics.
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Go to [Span metrics]({{< relref "./span-metrics" >}}) for a more detailed explanation of the feature.
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Go to [Span metrics](span-metrics/) for a more detailed explanation of the feature.
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#### Service graph metrics
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Edges are spans with a parent-child relationship, that represent a jump, such as a request, between two services.
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The amount of requests and their duration are recorded as metrics, which are used to represent the graph.
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To read more about this processor, go to its [section]({{< relref "./service-graphs" >}}).
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To read more about this processor, go to its [section](service-graphs/).
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The same service graph metrics can also be generated by Tempo.
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This is more efficient and recommended for larger installations.
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For a deep look into service graphs, visit [this section]({{< relref "../../metrics-generator/service_graphs" >}}).
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For a deep look into service graphs, visit [this section](../../../metrics-generator/service_graphs/).
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Service graphs are also used in the application performance management dashboard.
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For more information, refer to the [service graph view documentation]({{< relref "../../metrics-generator/service-graph-view" >}}).
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For more information, refer to the [service graph view documentation](../../../metrics-generator/service-graph-view/).
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## Before you begin
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The same service graph metrics can also be generated by Tempo.
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This is more efficient and recommended for larger installations.
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For additional information about viewing service graph metrics in Grafana and calculating cardinality, refer to the [server side documentation]({{< relref "../../metrics-generator/service_graphs/enable-service-graphs" >}}).
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For additional information about viewing service graph metrics in Grafana and calculating cardinality, refer to the [server side documentation](../../../metrics-generator/service_graphs/enable-service-graphs/).
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Tempo provides additional hosted storage configuration options discussed on the pages below. These options relate to providers such as Google Cloud, AWS S3, and Azure.
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For additional details about storage configuration, refer to [Storage configuration]({{< relref "../../configuration#storage" >}}).
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For additional details about storage configuration, refer to [Storage configuration](../#storage).
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# Apache Parquet block format
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Tempo has a default columnar block format based on Apache Parquet.
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This format is required for tags-based search as well as [TraceQL]({{< relref "../traceql" >}}), the query language for traces.
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This format is required for tags-based search as well as [TraceQL](../../traceql/), the query language for traces.
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The columnar block format improves search performance and enables an ecosystem of tools, including [Tempo CLI](https://grafana.com/docs/tempo/<TEMPO_VERSION>/operations/tempo_cli/#analyse-blocks), to access the underlying trace data.
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For more information, refer to the [Parquet design document](https://github.com/grafana/tempo/blob/main/docs/design-proposals/2022-04%20Parquet.md) and [Issue 1480](https://github.com/grafana/tempo/issues/1480).
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## Parquet configuration parameters
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Some parameters in the Tempo configuration are specific to Parquet.
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For more information, refer to the [storage configuration documentation]({{< relref "../configuration#storage" >}}).
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For more information, refer to the [storage configuration documentation](../#storage).
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