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This allows a tool to parse this source file and regenerate the Killercoda Interactive Learning Environment from its contents.

As I was in the file, I linted it for Writers' Toolkit style.

Signed-off-by: Jack Baldry <[email protected]>
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282 changes: 197 additions & 85 deletions docs/sources/get-started/quick-start.md
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title: Quickstart to run Loki locally
menuTitle: Loki quickstart
weight: 200
description: How to create and use a simple local Loki cluster for testing and evaluation purposes.
description: How to create and use a local Loki cluster for testing and evaluation purposes.
killercoda:
title: Loki Quickstart Demo
description: This sandbox provides an online enviroment for testing the Loki quickstart demo.
details:
finish:
text: finished.md
backend:
imageid: ubuntu
---

<!-- Killercoda intro.md START -->

# Quickstart to run Loki locally

If you want to experiment with Loki, you can run Loki locally using the Docker Compose file that ships with Loki. It runs Loki in a [monolithic deployment](https://grafana.com/docs/loki/<LOKI_VERSION>/get-started/deployment-modes/#monolithic-mode) mode and includes a sample application to generate logs.

The Docker Compose configuration instantiates the following components, each in its own container:

- **flog** a sample application which generates log lines. [flog](https://github.com/mingrammer/flog) is a log generator for common log formats.
- **flog** a sample application which generates log lines.
[flog](https://github.com/mingrammer/flog) is a log generator for common log formats.
- **Grafana Alloy** which scrapes the log lines from flog, and pushes them to Loki through the gateway.
- **Gateway** (NGINX) which receives requests and redirects them to the appropriate container based on the request's URL.
- **Gateway** (nginx) which receives requests and redirects them to the appropriate container based on the request's URL.
- One Loki **read** component (Query Frontend, Querier).
- One Loki **write** component (Distributor, Ingester).
- One Loki **backend** component (Index Gateway, Compactor, Ruler, Bloom Compactor (Experimental), Bloom Gateway (Experimental)).
Expand All @@ -22,140 +33,217 @@ The Docker Compose configuration instantiates the following components, each in

{{< figure max-width="75%" src="/media/docs/loki/get-started-flog-v3.png" caption="Getting started sample application" alt="Getting started sample application">}}

<!-- Killercoda intro.md END -->

## Before you begin

Use the [Interactive Learning Environment](#interactive-learning-environment) to skip installing Docker and Docker Compose.

- Install [Docker](https://docs.docker.com/install)
- Install [Docker Compose](https://docs.docker.com/compose/install)

## Interactive Learning Environment

{{< admonition type="note" >}}
The Interactive Learning Environment is currently in trial. Please provide feedback, report bugs, and raise issues in the [Grafana Killercoda Repository](https://github.com/grafana/killercoda).
The Interactive Learning Environment is in trial.

Provide feedback, report bugs, and raise issues in the [Grafana Killercoda repository](https://github.com/grafana/killercoda).
{{< /admonition >}}

Try out this demo within our interactive learning environment: [Loki Quickstart Sandbox](https://killercoda.com/grafana-labs/course/loki/loki-quickstart)
Try out this demo within our interactive learning environment: [Loki Quickstart Sandbox](https://killercoda.com/grafana-labs/course/loki/loki-quickstart)

- A free Killercoda account is required to verify you are not a bot.
- Tutorial instructions are located on the left-hand side of the screen. Click to move on to the next section.
- All commands run inside the interactive terminal. Grafana can also be accessed via the URL links provided within the sandbox.
- You must have a free Killercoda account to verify you aren't a bot.
- Tutorial instructions are located on the left-side of the screen.
Click to move on to the next section.
- All commands run inside the interactive terminal.
- You can access Grafana with the URL links provided within the sandbox.

## Installing Loki and collecting sample logs
<!-- Killercoda step1.md START -->

Prerequisites
## Install Loki and collecting sample logs

- [Docker](https://docs.docker.com/install)
- [Docker Compose](https://docs.docker.com/compose/install)
<!-- Killercoda ignore START -->

{{% admonition type="note" %}}
{{< admonition type="note" >}}
This quickstart assumes you are running Linux.
{{% /admonition %}}
{{< /admonition >}}

<!-- Killercoda ignore END -->

**To install Loki locally, follow these steps:**

1. Create a directory called `evaluate-loki` for the demo environment. Make `evaluate-loki` your current working directory:
1. Create a directory called `evaluate-loki` for the demo environment.
Make `evaluate-loki` your current working directory:

<!-- Killercoda execute START -->

```bash
mkdir evaluate-loki
cd evaluate-loki
```
```bash
mkdir evaluate-loki
cd evaluate-loki
```

<!-- Killercoda execute END -->

1. Download `loki-config.yaml`, `alloy-local-config.yaml`, and `docker-compose.yaml`:

```bash
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/loki-config.yaml -O loki-config.yaml
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/alloy-local-config.yaml -O alloy-local-config.yaml
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/docker-compose.yaml -O docker-compose.yaml
```
<!-- Killercoda execute START -->

```bash
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/loki-config.yaml -O loki-config.yaml
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/alloy-local-config.yaml -O alloy-local-config.yaml
wget https://raw.githubusercontent.com/grafana/loki/main/examples/getting-started/docker-compose.yaml -O docker-compose.yaml
```

<!-- Killercoda execute END -->

1. Deploy the sample Docker image.

With `evaluate-loki` as the current working directory, start the demo environment using `docker compose`:
With `evaluate-loki` as the current working directory, start the demo environment using `docker compose`:

```bash
docker compose up -d
```
<!-- Killercoda execute START -->

You should see something similar to the following:
```bash
docker compose up -d
```

```bash
✔ Network evaluate-loki_loki Created 0.1s
✔ Container evaluate-loki-minio-1 Started 0.6s
✔ Container evaluate-loki-flog-1 Started 0.6s
✔ Container evaluate-loki-backend-1 Started 0.8s
✔ Container evaluate-loki-write-1 Started 0.8s
✔ Container evaluate-loki-read-1 Started 0.8s
✔ Container evaluate-loki-gateway-1 Started 1.1s
✔ Container evaluate-loki-grafana-1 Started 1.4s
✔ Container evaluate-loki-alloy-1 Started 1.4s
```
<!-- Killercoda execute END -->

You should see something similar to the following:

```bash
✔ Network evaluate-loki_loki Created 0.1s
✔ Container evaluate-loki-minio-1 Started 0.6s
✔ Container evaluate-loki-flog-1 Started 0.6s
✔ Container evaluate-loki-backend-1 Started 0.8s
✔ Container evaluate-loki-write-1 Started 0.8s
✔ Container evaluate-loki-read-1 Started 0.8s
✔ Container evaluate-loki-gateway-1 Started 1.1s
✔ Container evaluate-loki-grafana-1 Started 1.4s
✔ Container evaluate-loki-alloy-1 Started 1.4s
```

1. (Optional) Verify that the Loki cluster is up and running.
- The read component returns `ready` when you point a web browser at [http://localhost:3101/ready](http://localhost:3101/ready). The message `Query Frontend not ready: not ready: number of schedulers this worker is connected to is 0` will show prior to the read component being ready.
- The write component returns `ready` when you point a web browser at [http://localhost:3102/ready](http://localhost:3102/ready). The message `Ingester not ready: waiting for 15s after being ready` will show prior to the write component being ready.


- The read component returns `ready` when you browse to [http://localhost:3101/ready](http://localhost:3101/ready).
The message `Query Frontend not ready: not ready: number of schedulers this worker is connected to is 0` shows until the read component is ready.
- The write component returns `ready` when you browse to [http://localhost:3102/ready](http://localhost:3102/ready).
The message `Ingester not ready: waiting for 15s after being ready` shows until the write component is ready.

1. (Optional) Verify that Grafana Alloy is running.
- Grafana Alloy's UI can be accessed at [http://localhost:12345](http://localhost:12345).
- You can access the Grafana Alloy UI at [http://localhost:12345](http://localhost:12345).

<!-- Killercoda step1.md END -->

<!-- Killercoda step2.md START -->

## View your logs in Grafana

## Viewing your logs in Grafana
After you have collected logs, you will want to view them.
You can view your logs using the command line interface, [LogCLI](/docs/loki/<LOKI_VERSION>/query/logcli/), but the easiest way to view your logs is with Grafana.

Once you have collected logs, you will want to view them. You can view your logs using the command line interface, [LogCLI](/docs/loki/<LOKI_VERSION>/query/logcli/), but the easiest way to view your logs is with Grafana.
1. Use Grafana to query the Loki data source.

1. Use Grafana to query the Loki data source.
The test environment includes [Grafana](https://grafana.com/docs/grafana/latest/), which you can use to query and observe the sample logs generated by the flog application.

The test environment includes [Grafana](https://grafana.com/docs/grafana/latest/), which you can use to query and observe the sample logs generated by the flog application. You can access the Grafana cluster by navigating to [http://localhost:3000](http://localhost:3000). The Grafana instance provided with this demo has a Loki [datasource](https://grafana.com/docs/grafana/latest/datasources/loki/) already configured.
You can access the Grafana cluster by browsing to [http://localhost:3000](http://localhost:3000).

The Grafana instance in this demonstration has a Loki [data source](https://grafana.com/docs/grafana/latest/datasources/loki/) already configured.

{{< figure src="/media/docs/loki/grafana-query-builder-v2.png" caption="Grafana Explore" alt="Grafana Explore">}}

1. From the Grafana main menu, click the **Explore** icon (1) to launch the Explore tab. To learn more about Explore, refer the [Explore](https://grafana.com/docs/grafana/latest/explore/) documentation.
1. From the Grafana main menu, click the **Explore** icon (1) to open the Explore tab.

To learn more about Explore, refer to the [Explore](https://grafana.com/docs/grafana/latest/explore/) documentation.

1. From the menu in the dashboard header, select the Loki data source (2).

1. From the menu in the dashboard header, select the Loki data source (2). This displays the Loki query editor. In the query editor you use the Loki query language, [LogQL](https://grafana.com/docs/loki/<LOKI_VERSION>/query/), to query your logs.
To learn more about the query editor, refer to the [query editor documentation](https://grafana.com/docs/grafana/latest/datasources/loki/query-editor/).
This displays the Loki query editor.

In the query editor you use the Loki query language, [LogQL](https://grafana.com/docs/loki/<LOKI_VERSION>/query/), to query your logs.
To learn more about the query editor, refer to the [query editor documentation](https://grafana.com/docs/grafana/latest/datasources/loki/query-editor/).

1. The Loki query editor has two modes (3):

- [Builder mode](https://grafana.com/docs/grafana/latest/datasources/loki/query-editor/#builder-mode), which provides a visual query designer.
- [Code mode](https://grafana.com/docs/grafana/latest/datasources/loki/query-editor/#code-mode), which provides a feature-rich editor for writing LogQL queries.

Next we’ll walk through a few simple queries using both the builder and code views.
1. Click **Code** (3) to work in Code mode in the query editor.

Here are some basic sample queries to get you started using LogQL. Note that these queries assume that you followed the instructions to create a directory called `evaluate-loki`. If you installed in a different directory, you’ll need to modify these queries to match your installation directory. After copying any of these queries into the query editor, click **Run Query** (4) to execute the query.
Here are some sample queries to get you started using LogQL.
These queries assume that you followed the instructions to create a directory called `evaluate-loki`.

If you installed in a different directory, you’ll need to modify these queries to match your installation directory.

1. View all the log lines which have the container label "flog":
After copying any of these queries into the query editor, click **Run Query** (4) to execute the query.

```bash
{container="evaluate-loki-flog-1"}
```
1. View all the log lines which have the container label `evaluate-loki-flog-1`:

In Loki, this is called a log stream. Loki uses [labels](https://grafana.com/docs/loki/<LOKI_VERSION>/get-started/labels/) as metadata to describe log streams. Loki queries always start with a label selector. In the query above, the label selector is `container`.
<!-- Killercoda copy START -->

1. To view all the log lines which have the container label "grafana":
```bash
{container="evaluate-loki-flog-1"}
```

```bash
{container="evaluate-loki-grafana-1"}
```
<!-- Killercoda copy END -->

1. Find all the log lines in the container=flog stream that contain the string "status":
In Loki, this is a log stream.

```bash
{container="evaluate-loki-flog-1"} |= `status`
```
Loki uses [labels](https://grafana.com/docs/loki/<LOKI_VERSION>/get-started/labels/) as metadata to describe log streams.

1. Find all the log lines in the container=flog stream where the JSON field "status" is "404":
Loki queries always start with a label selector.
In the previous query, the label selector is `{container="evaluate-loki-flog-1"}`.

```bash
{container="evaluate-loki-flog-1"} | json | status=`404`
```
1. To view all the log lines which have the container label `evaluate-loki-grafana-1`:

1. Calculate the number of logs per second where the JSON field "status" is "404":
<!-- Killercoda copy START -->

```bash
sum by(container) (rate({container="evaluate-loki-flog-1"} | json | status=`404` [$__auto]))
```
```bash
{container="evaluate-loki-grafana-1"}
```

The final query above is a metric query which returns a time series. This will trigger Grafana to draw a graph of the results. You can change the type of graph for a different view of the data. Click **Bars** to view a bar graph of the data.
<!-- Killercoda copy END -->

1. Click the **Builder** tab (3) to return to Builder mode in the query editor.
1. In Builder view, click **Kick start your query**(5).
1. Expand the **Log query starters** section.
1. Select the first choice, **Parse log lines with logfmt parser**, by clicking **Use this query**.
1. On the Explore tab, click **Label browser**, in the dialog select a container and click **Show logs**.
1. Find all the log lines in the `{container="evaluate-loki-flog-1}` stream that contain the string `status`:
<!-- Killercoda copy START -->
```bash
{container="evaluate-loki-flog-1"} |= `status`
```
<!-- Killercoda copy END -->
1. Find all the log lines in the `{container="evaluate-loki-flog-1}` stream where the JSON field `status` has the value `404`:

<!-- Killercoda copy START -->

```bash
{container="evaluate-loki-flog-1"} | json | status=`404`
```

<!-- Killercoda copy END -->

1. Calculate the number of logs per second where the JSON field `status` has the value `404`:

<!-- Killercoda copy START -->

```bash
sum by(container) (rate({container="evaluate-loki-flog-1"} | json | status=`404` [$__auto]))
```

<!-- Killercoda copy END -->

The final query is a metric query which returns a time series.
This makes Grafana draw a graph of the results.

You can change the type of graph for a different view of the data.
Click **Bars** to view a bar graph of the data.

1. Click the **Builder** tab (3) to return to builder mode in the query editor.
1. In builder mode, click **Kick start your query** (5).
1. Expand the **Log query starters** section.
1. Select the first choice, **Parse log lines with logfmt parser**, by clicking **Use this query**.
1. On the Explore tab, click **Label browser**, in the dialog select a container and click **Show logs**.

For a thorough introduction to LogQL, refer to the [LogQL reference](https://grafana.com/docs/loki/<LOKI_VERSION>/query/).

Expand All @@ -165,40 +253,64 @@ Here are some more sample queries that you can run using the Flog sample data.

To see all the log lines that flog has generated, enter the LogQL query:

<!-- Killercoda copy START -->

```bash
{container="evaluate-loki-flog-1"}|= ``
{container="evaluate-loki-flog-1"}
```

<!-- Killercoda copy END -->

The flog app generates log lines for simulated HTTP requests.

To see all `GET` log lines, enter the LogQL query:

<!-- Killercoda copy START -->

```bash
{container="evaluate-loki-flog-1"} |= "GET"
```

<!-- Killercoda copy END -->

To see all `POST` methods, enter the LogQL query:

<!-- Killercoda copy START -->

```bash
{container="evaluate-loki-flog-1"} |= "POST"
```

<!-- Killercoda copy END -->

To see every log line with a 401 status (unauthorized error), enter the LogQL query:

<!-- Killercoda copy START -->

```bash
{container="evaluate-loki-flog-1"} | json | status="401"
```

To see every log line that does not contain the value 401:
<!-- Killercoda copy END -->

To see every log line that doesn't contain the text `401`:
<!-- Killercoda copy START -->
```bash
{container="evaluate-loki-flog-1"} != "401"
```
<!-- Killercoda copy END -->
For more examples, refer to the [query documentation](https://grafana.com/docs/loki/<LOKI_VERSION>/query/query_examples/).
<!-- Killercoda step2.md END -->
## Complete metrics, logs, traces, and profiling example
If you would like to use a demo that includes Mimir, Loki, Tempo, and Grafana, you can use [Introduction to Metrics, Logs, Traces, and Profiling in Grafana](https://github.com/grafana/intro-to-mlt). `Intro-to-mltp` provides a self-contained environment for learning about Mimir, Loki, Tempo, and Grafana.
If you would like to run a demonstration environment that includes Mimir, Loki, Tempo, and Grafana, you can use [Introduction to Metrics, Logs, Traces, and Profiling in Grafana](https://github.com/grafana/intro-to-mlt).
It's a self-contained environment for learning about Mimir, Loki, Tempo, and Grafana.

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.
The project includes detailed explanations of each component and annotated configurations for a single-instance deployment.
You can also push the data from the environment to [Grafana Cloud](https://grafana.com/cloud/.

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