[DOC] Fix links for mounting OSS content to GET (#4388)

* Fix links for mounting OSS content to GET

* Fix ref to refs in frontmatter

* Apply suggestions from code review

Co-authored-by: Jack Baldry <jack.baldry@grafana.com>

* Update docs/sources/tempo/traceql/metrics-queries/functions.md

---------

Co-authored-by: Jack Baldry <jack.baldry@grafana.com>

docs/sources/tempo/introduction/solutions-with-traces/traces-app-insights.md

@@ -7,6 +7,17 @@ keywords:
 title: Identify bottlenecks and establish SLOs
 menuTitle: Identify bottlenecks and establish SLOs
 weight: 320
+refs:
+  metrics-generator:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/metrics-generator/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/metrics-generator/
+  span-metrics:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/metrics-generator/span_metrics/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/metrics-generator/span_metrics/
 ---
 
 # Identify bottlenecks and establish SLOs
@@ -19,34 +30,34 @@ Handy Site Corp, a fake website company, runs an ecommerce application that incl
 
 ### Define realistic SLOs
 
-Handy Site’s engineers start by establishing service level objectives (SLOs) around latency ensure that customers have a good experience when trying to complete the checkout process. 
+Handy Site’s engineers start by establishing service level objectives (SLOs) around latency ensure that customers have a good experience when trying to complete the checkout process.
 To do this, they use metrics generated from their span data.
 
 Their service level objective should be a realistic target based on previous history during times of normal operation.
-Once they've agreed upon their service level objective, they will set up alerts to warn them when they are at risk of failing to meet that objective. 
+Once they've agreed upon their service level objective, they will set up alerts to warn them when they are at risk of failing to meet that objective.
 
 ### Utilize span metrics to define your SLO and SLI
 
-After evaluating options, they decide to use [span metrics](https://grafana.com/docs/tempo/latest/metrics-generator/span_metrics/) as a service level indicator (SLI) to measure SLO compliance.
+After evaluating options, they decide to use [span metrics](ref:span-metrics) as a service level indicator (SLI) to measure SLO compliance.
 
 ![Metrics generator and exemplars](/media/docs/tempo/intro/traces-metrics-gen-exemplars.png)
 
-Tempo can generate metrics using the [metrics-generator component](https://grafana.com/docs/tempo/latest/metrics-generator/).
+Tempo can generate metrics using the [metrics-generator component](ref:metrics-generator).
 These metrics are created based on spans from incoming traces and demonstrate immediate usefulness with respect to application flow and overview.
 This includes rate, error, and duration (RED) metrics.
 
 
 Span metrics also make it easy to use exemplars.
-An [exemplar](https://grafana.com/docs/grafana/latest/basics/exemplars/) serves as a detailed example of one of the observations aggregated into a metric. An exemplar contains the observed value together with an optional timestamp and arbitrary trace IDs, which are typically used to reference a trace.
-Since traces and metrics co-exist in the metrics-generator, exemplars can be automatically added to those metrics, allowing you to quickly jump from a metric showing aggregate latency over time into an individual trace that represents a low, medium, or high latency request. Similarly, you can quickly jump from a metric showing error rate over time into an individual erroring trace. 
+An [exemplar](https://grafana.com/docs/grafana/<GRAFANA_VERSION>/basics/exemplars/) serves as a detailed example of one of the observations aggregated into a metric. An exemplar contains the observed value together with an optional timestamp and arbitrary trace IDs, which are typically used to reference a trace.
+Since traces and metrics co-exist in the metrics-generator, exemplars can be automatically added to those metrics, allowing you to quickly jump from a metric showing aggregate latency over time into an individual trace that represents a low, medium, or high latency request. Similarly, you can quickly jump from a metric showing error rate over time into an individual erroring trace.
 
 ### Monitor latency
 
 Handy Site decides they're most interested in monitoring the latency of requests processed by their checkout service and want to set an objective that 99.5% of requests in a given month should complete within 2 seconds.
 To define a service level indicator (SLI) that they can use to track their progress against their objective, they use the `traces_spanmetrics_latency` metric with the proper label selectors, such as `service name = checkoutservice`.
-The metrics-generator adds a default set of labels to the metrics it generates, including `span_kind` and `status_code`. However, if they were interested in calculating checkout service latency per endpoint or per version of the software, they could change the configuration of the Tempo metrics-generator to add these custom dimensions as labels to their spanmetrics. 
+The metrics-generator adds a default set of labels to the metrics it generates, including `span_kind` and `status_code`. However, if they were interested in calculating checkout service latency per endpoint or per version of the software, they could change the configuration of the Tempo metrics-generator to add these custom dimensions as labels to their spanmetrics.
 
-With all of this in place, Handy Site now opens the [Grafana SLO](https://grafana.com/docs/grafana-cloud/alerting-and-irm/slo/) application and follows the setup flow to establish an [SLI](https://grafana.com/docs/grafana-cloud/alerting-and-irm/slo/create/) for their checkout service around the `traces_spanmetrics_latency` metric..
+With all of this in place, Handy Site now opens the [Grafana SLO](https://grafana.com/docs/grafana-cloud/alerting-and-irm/slo/) application and follows the setup flow to establish an [SLI](https://grafana.com/docs/grafana-cloud/alerting-and-irm/slo/create/) for their checkout service around the `traces_spanmetrics_latency` metric.
 They can now be alerted to degradations in service quality that directly impact their end user experience. SLO-based alerting also ensures that they don't suffer from noisy alerts. Alerts are only triggered when the value of the SLI is such that the team is in danger of missing their SLO.
 
 ![Latency SLO dashboard](/media/docs/tempo/intro/traces-metrics-gen-SLO.png)

docs/sources/tempo/introduction/solutions-with-traces/traces-diagnose-errors.md

@@ -7,6 +7,12 @@ keywords:
 title: Diagnose errors with traces
 menuTitle: Diagnose errors with traces
 weight: 400
+refs:
+  traceql:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/traceql/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/traceql/
 ---
 
 # Diagnose errors with traces
@@ -27,7 +33,7 @@ It’s imperative for the operations team at Handy Site to quickly troubleshoot
 
 ## Use TraceQL to query data
 
-Tempo has a traces-first query language, [TraceQL](https://grafana.com/docs/tempo/latest/traceql/), that provides a unique toolset for selecting and searching tracing data. TraceQL can match traces based on span and resource attributes, duration, and ancestor<>descendant relationships. It also can compute aggregate statistics (e.g., `rate`) over a set of spans.
+Tempo has a traces-first query language, [TraceQL](ref:traceql), that provides a unique toolset for selecting and searching tracing data. TraceQL can match traces based on span and resource attributes, duration, and ancestor<>descendant relationships. It also can compute aggregate statistics (e.g., `rate`) over a set of spans.
 
 Handy Site’s services and applications are instrumented for tracing, so they can use TraceQL as a debugging tool. Using three TraceQL queries, the team identifies and validates the root cause of the issue.
 
@@ -50,7 +56,7 @@ Looking at the set of returned spans, the most concerning ones are those with th
 
 The team decides to use structural operators to follow an error chain from the top-level `mythical-requester` service to any descendant spans that also have an error status.
 Descendant spans can be any span that's descended from the parent span, such as a child or a further child at any depth.
-Using this query, the team can pinpoint the downstream service that might be causing the issue. The query below says "Find me spans where `status = error` that that are descendants of spans from the `mythical-requester` service that have status code `500`." 
+Using this query, the team can pinpoint the downstream service that might be causing the issue. The query below says "Find me spans where `status = error` that that are descendants of spans from the `mythical-requester` service that have status code `500`."
 
 ```traceql
 { resource.service.name = "mythical-requester" && span.http.status_code = 500 } >> { status = error }
@@ -68,14 +74,14 @@ Specifically, the service is passing a `null` value for a column in a database t
 After identifying the specific cause of this internal server error,
 the team wants to know if there are errors in any database operations other than the `null` `INSERT` error found above.
 Their updated query uses a negated regular expression to find any spans where the database statement either doesn’t exist, or doesn’t start with an `INSERT` clause.
-This should expose any other issues causing an internal server error and filter out the class of issues that they already diagnosed. 
+This should expose any other issues causing an internal server error and filter out the class of issues that they already diagnosed.
 
 ```traceql
 { resource.service.name = "mythical-requester" && span.http.status_code = 500 } >> { status = error && span.db.statement !~ "INSERT.*" }
 ```
 
 This query yields no results, suggesting that the root cause of the issues the operations team are seeing is exclusively due to the failing database `INSERT` statement.
 At this point, they can roll back to a known working version of the service, or deploy a fix to ensure that `null` data being passed to the service is rejected appropriately.
-Once that is complete, the issue can be marked resolved and the Handy team's error rate SLI should return back to acceptable levels. 
+Once that is complete, the issue can be marked resolved and the Handy team's error rate SLI should return back to acceptable levels.
 
 ![Empty query results](/media/docs/tempo/intro/traceql-no-results-handy-site.png)

docs/sources/tempo/metrics-generator/active-series.md

@@ -16,9 +16,9 @@ These capabilities rely on a set of generated span metrics and service metrics.
 
 Any spans that are ingested by Tempo can create many metric series. However, this doesn't mean that every time a span is ingested that a new active series is created.
 
-The number of active series generated depends on the label pairs generated from span data that are associated with the metrics, similar to other Prometheus-formated data.
+The number of active series generated depends on the label pairs generated from span data that are associated with the metrics, similar to other Prometheus-formatted data.
 
-For additional information, refer to the [Active series and DPM documentation](/docs/grafana-cloud/billing-and-usage/active-series-and-dpm/#active-series).
+For additional information, refer to the [Active series and DPM documentation](https://grafana.com/docs/grafana-cloud/billing-and-usage/active-series-and-dpm/).
 
 ## Active series calculation
 

docs/sources/tempo/metrics-generator/service-graph-view.md

@@ -5,6 +5,17 @@ description: Grafana's service graph view utilizes metrics generated by the metr
 aliases:
   - ./app-performance-mgmt # /docs/tempo/<TEMPO_VERSION>/metrics-generator/app-performance-mgmt
 weight: 400
+refs:
+  enable-service-graphs:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/metrics-generator/service_graphs/enable-service-graphs/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/metrics-generator/service_graphs/enable-service-graphs/
+  span-metrics:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/metrics-generator/span_metrics/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/metrics-generator/span_metrics/
 ---
 
 # Service graph view
@@ -27,13 +38,13 @@ You have to enable span metrics and service graph generation on the Grafana back
 
 To use the service graph view, you need:
 
-* Tempo or Grafana Cloud Traces with either 1) the metrics generator enabled and configured or 2)  Grafana Agent or Grafana Alloy enabled and configured to send data to a Prometheus-compatible metrics store
-* [Services graphs]({{< relref "../metrics-generator/service_graphs/enable-service-graphs" >}}), which are enabled by default in Grafana
-* [Span metrics]({{< relref "../metrics-generator/span_metrics#how-to-run" >}}) enabled in your Tempo data source configuration
+* Tempo or Grafana Cloud Traces with either the metrics generator enabled and configured or Grafana Agent or Grafana Alloy enabled and configured to send data to a Prometheus-compatible metrics store
+* [Services graphs](ref:enable-service-graphs), which are enabled by default in Grafana
+* [Span metrics](ref:span-metrics) enabled in your Tempo data source configuration
 
 The service graph view can be derived from metrics generated by either the metrics-generator or by Grafana Agent or Grafana Alloy.
 
-For information on how to configure these features, refer to the [Grafana Tempo data sources documentation](/docs/grafana/latest/datasources/tempo/).
+For information on how to configure these features, refer to the [Tempo data sources documentation](/docs/grafana/<GRAFANA_VERSION>/datasources/tempo/).
 
 ## What does the service graph view show?
 
@@ -46,7 +57,7 @@ The service graph view provides a span metrics visualization (table) and service
 You can select any information in the table that has an underline to show more detailed information.
 You can also select any node in the service graph to display additional information.
 
-![Service graph with extended informaiton](/media/docs/grafana/data-sources/tempo/query-editor/tempo-ds-query-service-graph-prom.png)
+![Service graph with extended information](/media/docs/grafana/data-sources/tempo/query-editor/tempo-ds-query-service-graph-prom.png)
 
 ### Error rate example
 

docs/sources/tempo/metrics-generator/service_graphs/enable-service-graphs.md

@@ -5,32 +5,38 @@ aliases:
 title: Enable service graphs
 description: Learn how to enable service graphs
 weight: 200
+refs:
+  cardinality:
+    - pattern: /docs/tempo/
+      destination: https://grafana.com/docs/tempo/<TEMPO_VERSION>/metrics-generator/cardinality/
+    - pattern: /docs/enterprise-traces/
+      destination: https://grafana.com/docs/enterprise-traces/<ENTERPRISE_TRACES_VERSION>/metrics-generator/cardinality/
 ---
 
 ## Enable service graphs
 
 Service graphs are generated in Tempo and pushed to a metrics storage.
 Then, they can be represented in Grafana as a graph.
-You will need those components to fully use service graphs.
+You need those components to fully use service graphs.
 
 {{< admonition type="note" >}}
 Cardinality can pose a problem when you have lots of services.
-To learn more about cardinality and how to perform a dry run of the metrics generator, see the [Cardinality documentation]({{< relref "../cardinality" >}}).
-{{% /admonition %}}
+To learn more about cardinality and how to perform a dry run of the metrics-generator, refer to the [Cardinality documentation](ref:cardinality).
+{{< /admonition >}}
 
 ### Enable service graphs in Tempo/GET
 
 To enable service graphs in Tempo/GET, enable the metrics generator and add an overrides section which enables the `service-graphs` generator.
-For more information, refer to the [configuration details]({{< relref "../../configuration#metrics-generator" >}}).
+For more information, refer to the [configuration details](https://grafana.com/docs/tempo/<TEMPO_VERSION>/configuration#metrics-generator).
 
-To enable service graphs when using Grafana Agent, refer to the [Grafana Agent and service graphs documentation]({{< relref "../../configuration/grafana-agent/service-graphs" >}}).
+To enable service graphs when using Grafana Alloy, refer to the [Grafana Alloy and service graphs documentation](https://grafana.com/docs/tempo/<TEMPO_VERSION>/configuration/grafana-alloy/service-graphs/).
 
 ### Enable service graphs in Grafana
 
 {{< admonition type="note" >}}
-Since Grafana 9.0.4, service graphs have been enabled by default. Prior to Grafana 9.0.4, service graphs were hidden
-under the [feature toggle](/docs/grafana/latest/setup-grafana/configure-grafana/#feature_toggles) `tempoServiceGraph`.
-{{% /admonition %}}
+Service graphs are enabled by default in Grafana. Prior to Grafana 9.0.4, service graphs were hidden
+under the [feature toggle](/docs/grafana/latest/setup-grafana/configure-grafana) `tempoServiceGraph`.
+{{< /admonition >}}
 
 Configure a Tempo data source's service graphs by linking to the Prometheus backend where metrics are being sent: