Merge branch 'main' into boldfield/allow-prefixing-rollout-group

Author: trevorwhitney

.github/renovate.json5

@@ -48,6 +48,7 @@
       "matchManagers": ["helm-requirements", "helm-values", "helmv3"],
       "groupName": "helm-{{packageName}}",
       "matchUpdateTypes": ["major", "minor", "patch"],
+      "matchPackageNames": ["!grafana/loki"], // This is updated via a different job
       "autoApprove": false,
       "automerge": false
     },

docs/sources/query/metric_queries.md

@@ -153,3 +153,14 @@ Examples:
       or
     vector(0) # will return 0
     ```
+
+## Probabilistic aggregation
+
+The `topk` keyword lets you find the largest 1,000 elements in a data stream by sample size. When  `topk` hits the maximum series limit, LogQL also supports using a probable approximation; `approx_topk`  is a drop-in replacement when `topk` hits the maximum series limit.
+
+```logql
+approx_topk(k, <vector expression>)
+```
+
+It is only supported for instant queries and does not support grouping. It is useful when the cardinality of the inner
+vector is too high, for example, when it uses an aggregation by a structured metadata label.

docs/sources/send-data/alloy/examples/alloy-kafka-logs.md

@@ -1,20 +1,21 @@
 ---
 title: Sending Logs to Loki via Kafka using Alloy
 menuTitle: Sending Logs to Loki via Kafka using Alloy
-description: Configuring Grafana Alloy to recive logs via Kafka and send them to Loki.
+description: Configuring Grafana Alloy to receive logs via Kafka and send them to Loki.
 weight: 250
 killercoda:
   title: Sending Logs to Loki via Kafka using Alloy
-  description: Configuring Grafana Alloy to recive logs via Kafka and send them to Loki.
+  description: Configuring Grafana Alloy to receive logs via Kafka and send them to Loki.
   backend:
     imageid: ubuntu
 ---
-
+<!-- vale Grafana.We = NO -->
 <!-- INTERACTIVE page intro.md START -->
 
-#  Sending Logs to Loki via Kafka using Alloy
+# Sending Logs to Loki via Kafka using Alloy
 
 Alloy natively supports receiving logs via Kafka. In this example, we will configure Alloy to receive logs via Kafka using two different methods:
+
 - [loki.source.kafka](https://grafana.com/docs/alloy/latest/reference/components/loki.source.kafka): reads messages from Kafka using a consumer group and forwards them to other `loki.*` components.
 - [otelcol.receiver.kafka](https://grafana.com/docs/alloy/latest/reference/components/otelcol.receiver.kafka/): accepts telemetry data from a Kafka broker and forwards it to other `otelcol.*` components.
 
@@ -38,9 +39,10 @@ Provide feedback, report bugs, and raise issues in the [Grafana Killercoda repos
 {{< /admonition >}}
 <!-- INTERACTIVE ignore END -->
 
-
 ## Scenario
+
 In this scenario, we have a microservices application called the Carnivorous Greenhouse. This application consists of the following services:
+
 - **User Service:** Manages user data and authentication for the application. Such as creating users and logging in.
 - **Plant Service:** Manages the creation of new plants and updates other services when a new plant is created.
 - **Simulation Service:** Generates sensor data for each plant.
@@ -50,7 +52,8 @@ In this scenario, we have a microservices application called the Carnivorous Gre
 - **Database:** A database that stores user and plant data.
 
 Each service generates logs that are sent to Alloy via Kafka. In this example, they are sent on two different topics:
-- `loki`: This sends a structured log formatted message (json). 
+
+- `loki`: This sends a structured log formatted message (json).
 - `otlp`: This sends a serialized OpenTelemetry log message.
 
 You would not typically do this within your own application, but for the purposes of this example we wanted to show how Alloy can handle different types of log messages over Kafka.
@@ -69,7 +72,8 @@ In this step, we will set up our environment by cloning the repository that cont
     git clone -b microservice-kafka  https://github.com/grafana/loki-fundamentals.git
     ```
     <!-- INTERACTIVE exec END -->
-1.  Next we will spin up our observability stack using Docker Compose:
+
+1. Next we will spin up our observability stack using Docker Compose:
 
     <!-- INTERACTIVE ignore START -->
     ```bash
@@ -80,14 +84,15 @@ In this step, we will set up our environment by cloning the repository that cont
     {{< docs/ignore >}}
 
     <!-- INTERACTIVE exec START -->
-    ```bash 
+    ```bash
     docker-compose -f loki-fundamentals/docker-compose.yml up -d 
     ```
     <!-- INTERACTIVE exec END -->
 
     {{< /docs/ignore >}}
 
     This will spin up the following services:
+
     ```console
     ✔ Container loki-fundamentals-grafana-1      Started                                                        
     ✔ Container loki-fundamentals-loki-1         Started                        
@@ -97,6 +102,7 @@ In this step, we will set up our environment by cloning the repository that cont
     ```
 
 We will be access two UI interfaces:
+
 - Alloy at [http://localhost:12345](http://localhost:12345)
 - Grafana at [http://localhost:3000](http://localhost:3000)
 <!-- INTERACTIVE page step1.md END -->
@@ -107,12 +113,13 @@ We will be access two UI interfaces:
 
 In this first step, we will configure Alloy to ingest raw Kafka logs. To do this, we will update the `config.alloy` file to include the Kafka logs configuration.
 
-### Open your Code Editor and Locate the `config.alloy` file
+### Open your code editor and locate the `config.alloy` file
 
 Grafana Alloy requires a configuration file to define the components and their relationships. The configuration file is written using Alloy configuration syntax. We will build the entire observability pipeline within this configuration file. To start, we will open the `config.alloy` file in the code editor:
 
 {{< docs/ignore >}}
 **Note: Killercoda has an inbuilt Code editor which can be accessed via the `Editor` tab.**
+
 1. Expand the `loki-fundamentals` directory in the file explorer of the `Editor` tab.
 1. Locate the `config.alloy` file in the `loki-fundamentals` directory (Top level directory).
 1. Click on the `config.alloy` file to open it in the code editor.
@@ -126,13 +133,14 @@ Grafana Alloy requires a configuration file to define the components and their r
 
 You will copy all three of the following configuration snippets into the `config.alloy` file.  
 
-### Source logs from kafka
+### Source logs from Kafka
 
 First, we will configure the Loki Kafka source. `loki.source.kafka` reads messages from Kafka using a consumer group and forwards them to other `loki.*` components.
 
 The component starts a new Kafka consumer group for the given arguments and fans out incoming entries to the list of receivers in `forward_to`.
 
 Add the following configuration to the `config.alloy` file:
+
 ```alloy
 loki.source.kafka "raw" {
   brokers                = ["kafka:9092"]
@@ -145,6 +153,7 @@ loki.source.kafka "raw" {
 ```
 
 In this configuration:
+
 - `brokers`: The Kafka brokers to connect to.
 - `topics`: The Kafka topics to consume. In this case, we are consuming the `loki` topic.
 - `forward_to`: The list of receivers to forward the logs to. In this case, we are forwarding the logs to the `loki.write.http.receiver`.
@@ -159,6 +168,7 @@ For more information on the `loki.source.kafka` configuration, see the [Loki Kaf
 Next, we will configure the Loki relabel rules. The `loki.relabel` component rewrites the label set of each log entry passed to its receiver by applying one or more relabeling rules and forwards the results to the list of receivers in the component’s arguments. In our case we are directly calling the rule from the `loki.source.kafka` component.
 
 Now add the following configuration to the `config.alloy` file:
+
 ```alloy
 loki.relabel "kafka" {
   forward_to      = [loki.write.http.receiver]
@@ -170,6 +180,7 @@ loki.relabel "kafka" {
 ```
 
 In this configuration:
+
 - `forward_to`: The list of receivers to forward the logs to. In this case, we are forwarding the logs to the `loki.write.http.receiver`. Though in this case, we are directly calling the rule from the `loki.source.kafka` component. So `forward_to` is being used as a placeholder as it is required by the `loki.relabel` component.
 - `rule`: The relabeling rule to apply to the incoming logs. In this case, we are renaming the `__meta_kafka_topic` label to `topic`.
 
@@ -180,6 +191,7 @@ For more information on the `loki.relabel` configuration, see the [Loki Relabel
 Lastly, we will configure the Loki write component. `loki.write` receives log entries from other loki components and sends them over the network using the Loki logproto format.
 
 And finally, add the following configuration to the `config.alloy` file:
+
 ```alloy
 loki.write "http" {
   endpoint {
@@ -189,6 +201,7 @@ loki.write "http" {
 ```
 
 In this configuration:
+
 - `endpoint`: The endpoint to send the logs to. In this case, we are sending the logs to the Loki HTTP endpoint.
 
 For more information on the `loki.write` configuration, see the [Loki Write documentation](https://grafana.com/docs/alloy/latest/reference/components/loki.write/).
@@ -209,7 +222,6 @@ The new configuration will be loaded.  You can verify this by checking the Alloy
 
 If you get stuck or need help creating the configuration, you can copy and replace the entire `config.alloy` using the completed configuration file:
 
-
 <!-- INTERACTIVE exec START -->
 ```bash
 cp loki-fundamentals/completed/config-raw.alloy loki-fundamentals/config.alloy
@@ -225,16 +237,16 @@ curl -X POST http://localhost:12345/-/reload
 
 Next we will configure Alloy to also ingest OpenTelemetry logs via Kafka, we need to update the Alloy configuration file once again. We will add the new components to the `config.alloy` file along with the existing components.
 
-### Open your Code Editor and Locate the `config.alloy` file
+### Open your code editor and locate the `config.alloy` file
 
 Like before, we generate our next pipeline configuration within the same `config.alloy` file. You will add the following configuration snippets to the file **in addition** to the existing configuration. Essentially, we are configuring two pipelines within the same Alloy configuration file.
 
-
 ### Source OpenTelemetry logs from Kafka
 
-First, we will configure the OpenTelemetry Kafaka receiver. `otelcol.receiver.kafka` accepts telemetry data from a Kafka broker and forwards it to other `otelcol.*` components.
+First, we will configure the OpenTelemetry Kafka receiver. `otelcol.receiver.kafka` accepts telemetry data from a Kafka broker and forwards it to other `otelcol.*` components.
 
 Now add the following configuration to the `config.alloy` file:
+
 ```alloy
 otelcol.receiver.kafka "default" {
   brokers          = ["kafka:9092"]
@@ -249,6 +261,7 @@ otelcol.receiver.kafka "default" {
 ```
 
 In this configuration:
+
 - `brokers`: The Kafka brokers to connect to.
 - `protocol_version`: The Kafka protocol version to use.
 - `topic`: The Kafka topic to consume. In this case, we are consuming the `otlp` topic.
@@ -257,12 +270,12 @@ In this configuration:
 
 For more information on the `otelcol.receiver.kafka` configuration, see the [OpenTelemetry Receiver Kafka documentation](https://grafana.com/docs/alloy/latest/reference/components/otelcol.receiver.kafka/).
 
-
 ### Batch OpenTelemetry logs before sending
 
 Next, we will configure a OpenTelemetry processor. `otelcol.processor.batch` accepts telemetry data from other otelcol components and places them into batches. Batching improves the compression of data and reduces the number of outgoing network requests required to transmit data. This processor supports both size and time based batching.
 
 Now add the following configuration to the `config.alloy` file:
+
 ```alloy
 otelcol.processor.batch "default" {
     output {
@@ -272,6 +285,7 @@ otelcol.processor.batch "default" {
 ```
 
 In this configuration:
+
 - `output`: The list of receivers to forward the logs to. In this case, we are forwarding the logs to the `otelcol.exporter.otlphttp.default.input`.
 
 For more information on the `otelcol.processor.batch` configuration, see the [OpenTelemetry Processor Batch documentation](https://grafana.com/docs/alloy/latest/reference/components/otelcol.processor.batch/).
@@ -281,6 +295,7 @@ For more information on the `otelcol.processor.batch` configuration, see the [Op
 Lastly, we will configure the OpenTelemetry exporter. `otelcol.exporter.otlphttp` accepts telemetry data from other otelcol components and writes them over the network using the OTLP HTTP protocol. We will use this exporter to send the logs to the Loki native OTLP endpoint.
 
 Finally, add the following configuration to the `config.alloy` file:
+
 ```alloy
 otelcol.exporter.otlphttp "default" {
   client {
@@ -290,6 +305,7 @@ otelcol.exporter.otlphttp "default" {
 ```
 
 In this configuration:
+
 - `client`: The client configuration for the exporter. In this case, we are sending the logs to the Loki OTLP endpoint.
 
 For more information on the `otelcol.exporter.otlphttp` configuration, see the [OpenTelemetry Exporter OTLP HTTP documentation](https://grafana.com/docs/alloy/latest/reference/components/otelcol.exporter.otlphttp/).
@@ -341,7 +357,6 @@ docker compose -f loki-fundamentals/greenhouse/docker-compose-micro.yml up -d --
 ```
 <!-- INTERACTIVE ignore END -->
 
-
 {{< docs/ignore >}}
 
 <!-- INTERACTIVE exec START -->
@@ -353,6 +368,7 @@ docker-compose -f loki-fundamentals/greenhouse/docker-compose-micro.yml up -d --
 {{< /docs/ignore >}}
 
 This will start the following services:
+
 ```console
  ✔ Container greenhouse-db-1                 Started                                                         
  ✔ Container greenhouse-websocket_service-1  Started 
@@ -372,7 +388,6 @@ Once started, you can access the Carnivorous Greenhouse application at [http://l
 
 Finally to view the logs in Loki, navigate to the Loki Logs Explore view in Grafana at [http://localhost:3000/a/grafana-lokiexplore-app/explore](http://localhost:3000/a/grafana-lokiexplore-app/explore).
 
-
 <!-- INTERACTIVE page step4.md END -->
 
 <!-- INTERACTIVE page finish.md START -->
@@ -383,14 +398,16 @@ In this example, we configured Alloy to ingest logs via Kafka. We configured All
 
 {{< docs/ignore >}}
 
-### Back to Docs
+### Back to docs
+
 Head back to where you started from to continue with the Loki documentation: [Loki documentation](https://grafana.com/docs/loki/latest/send-data/alloy)
 
 {{< /docs/ignore >}}
 
 ## Further reading
 
 For more information on Grafana Alloy, refer to the following resources:
+
 - [Grafana Alloy getting started examples](https://grafana.com/docs/alloy/latest/tutorials/)
 - [Grafana Alloy component reference](https://grafana.com/docs/alloy/latest/reference/components/)
 
@@ -400,5 +417,5 @@ If you would like to use a demo that includes Mimir, Loki, Tempo, and Grafana, y
 
 The project includes detailed explanations of each component and annotated configurations for a single-instance deployment. Data from `intro-to-mltp` can also be pushed to Grafana Cloud.
 
-
-<!-- INTERACTIVE page finish.md END -->
+<!-- INTERACTIVE page finish.md END -->
+<!-- vale Grafana.We = YES -->