POC test for attribute dictionary in french. Please ignore

src/content/docs/apm/agents/go-agent/configuration/go-agent-logging.mdx

@@ -19,7 +19,7 @@ To use the Go agent methods for writing log and audit files, see [log.go on the
 
 ## Logrus integration example [#logrus]
 
-New Relic offers an [integration for the Logrus logging system](https://github.com/newrelic/go-agent/blob/master/_integrations/nrlogrus/nrlogrus.go). Here is an example of using the New Relic Logrus integration in an application:
+New Relic offers an [integration for the Logrus logging system.](https://github.com/newrelic/go-agent/blob/master/v3/integrations/nrlogrus/nrlogrus.go) Here is an example of using the New Relic Logrus integration in an application:
 
 1. Import both `github.com/sirupsen/logrus` and `github.com/newrelic/go-agent/v3/integrations/nrlogrus`.
 2. Set the log level and assign the Logger output to Logrus. For example:

src/content/docs/nrql/nrql-syntax-clauses-functions.mdx

@@ -2181,13 +2181,31 @@ SELECT histogram(duration, 10, 20) FROM PageView SINCE 1 week ago
   <Collapser
     className="freq-link"
     id="func-uniqueCount"
-    title={<InlineCode>uniqueCount(attribute)</InlineCode>}
+    title={<InlineCode>uniqueCount(attribute, [, attribute [, ...]] [, precision: number])</InlineCode>}
   >
-    Use the `uniqueCount()` function to return the number of unique values recorded for an attribute over the time range specified.
 
-    <Callout variant="tip">
-      To optimize query performance, this function returns approximate results for queries that inspect 256 or more unique values.
-    </Callout>
+    Use the `uniqueCount()` function to get the number of unique values recorded for an attribute over a specified time range. This function provides an exact result for up to 256 unique values when you call it without the `precision` argument. For more than 256 unique values, the result is approximate. You can specify a `precision` value within the range of 256 to 50,000 to increase the threshold for exact results. When unique values exceed the set threshold, the function uses the [HyperLogLog probabilistic data structure](https://algo.inria.fr/flajolet/Publications/FlFuGaMe07.pdf) to provide an approximate result.
+
+    Use the `uniqueCount()` function by specifying the attributes and optionally set the precision argument as follows:
+
+    ```sql
+    uniqueCount(attribute, [, attribute [, ...]] [, precision: number])
+    ```
+    * **Attribute(s)**: Attributes for which you want to count unique values.
+    * **Precision**: A numeric argument that sets the threshold for exact results. You can set a value up to 50,000.
+
+    Query example without a `precision` argument:
+
+    ```sql
+    SELECT uniqueCount(accountId) FROM Transaction SINCE 1 day ago
+    ```
+
+    Query example with a `precision` argument:
+
+    ```sql
+    SELECT uniqueCount(foo, bar, baz, precision: 1000) FROM Transaction SINCE 1 day ago
+    ```
+
   </Collapser>
 
   <Collapser

src/content/docs/opentelemetry/get-started/collector-infra-monitoring/opentelemetry-collector-infra-intro.mdx

@@ -62,4 +62,4 @@ The general pattern is to configure the Collector with a processor which detects
 
 While Collector requirements and configuration will vary, it comes with a variety of receivers and processors which make it popular for Kubernetes monitoring.
 Getting all the required telemetry requires scraping various Kubernetes APIs using multiple receivers with differing permission requirements, so to keep things simple for you, we built a helm chart that uses our custom distribution of the collector [nrdot-collector-k8s](https://github.com/newrelic/nrdot-collector-releases/tree/main/distributions/nrdot-collector-k8s) under the hood.
-For more details on how to get started, please refer to [OpenTelemetry for Kubernetes](/docs/kubernetes-pixie/kubernetes-integration/installation/k8s-otel/).
+For more details on how to get started, please refer to [OpenTelemetry for Kubernetes](/docs/kubernetes-pixie/k8s-otel/intro/).

src/content/docs/query-your-data/explore-query-data/dashboards/nested-variables.mdx

@@ -12,6 +12,8 @@ Nested variables let you create dynamic, dependent relationships between variabl
 ## Use case [#use-case]
 Imagine you've created an `Env` variable to select an environment (for example, production and staging). You want to update a `Machine` variable with a list of machines based on the selected environment. Directly embedding the Env variable in a `WHERE` condition for `Machine` isn't supported in a standard setup.
 
+<Callout variant="important">The nested variables feature is available only to <DNT>Pro</DNT>, <DNT>Enterprise</DNT>, and <DNT>Core Compute customers</DNT>. To learn more about our pricing model, editions, and buying programs, refer to the [pricing](/docs/accounts/accounts-billing/new-relic-one-pricing-billing/new-relic-one-pricing-billing/) documentation.</Callout>
+
 **Example:**
 - `Variable Env` = `production` or `staging`
 - `Variable Machine` = `SELECT uniques(machine) FROM Table WHERE env in ({{Env}})` 
@@ -44,4 +46,4 @@ When you use nested variables, be aware of the following limitations:
 - **Parent variable selection required for child definition:** Make sure your `env` variable has selected values when you define your `machine` variable. Otherwise, the `machine` query will return no results.
 - **Variable selection required for widget usage:** Ensure the variable has selected values when you use it inside widgets. Otherwise, the widget's query will return no results.
 - **Deletion impact:** If your `env` variable is deleted, your `machine` variable may show errors when loading.
-- **Cleared values:** If your `env` variable's values are cleared, your `machine` variable will continue to show values based on `env`'s previous selections.
+- **Cleared values:** If your `env` variable's values are cleared, your `machine` variable will continue to show values based on `env`'s previous selections.