---
title: Build a logs data source plugin
---

# Build a logs data source plugin

Grafana data source plugins support metrics, logs, and other data types. The steps to build a logs data source plugin are largely the same as for a metrics data source, but there are a few differences which we will explain in this guide.

## Before you begin

This guide assumes that you're already familiar with how to [Build a data source plugin](/tutorials/build-a-data-source-plugin/) for metrics. We recommend that you review this material before continuing.

## Add logs support to your data source

To add logs support to an existing data source, you need to:

1. Enable logs support
1. Construct the log data

When these steps are done, then you can improve the user experience with one or more [optional features](#enhance-your-logs-data-source-plugin-with-optional-features).

### Step 1: Enable logs support

Tell Grafana that your data source plugin can return log data, by adding `"logs": true` to the [plugin.json]({{< relref "metadata/" >}}) file.

```json
{
  "logs": true
}
```

### Step 2: Construct the log data

As it does with metrics data, Grafana expects your plugin to return log data as a [data frame]({{< relref "data-frames/" >}}).

To return log data, return a data frame with at least one time field and one text field from the data source's `query` method.

**Example:**

```ts
const frame = new MutableDataFrame({
  refId: query.refId,
  fields: [
    { name: 'time', type: FieldType.time },
    { name: 'content', type: FieldType.string },
  ],
});

frame.add({ time: 1589189388597, content: 'user registered' });
frame.add({ time: 1589189406480, content: 'user logged in' });
```

That's all you need to start returning log data from your data source. Go ahead and try it out in [Explore]({{< relref "../../explore/" >}}) or by adding a [Logs panel]({{< relref "../../panels-visualizations/visualizations/logs/" >}}).

Congratulations, you just wrote your first logs data source plugin! Next, let's look at a couple of features that can further improve the experience for the user.

## Enhance your logs data source plugin with optional features

Add visualization type hints, labels, and other optional features to logs.

### Add a preferred visualization type hint to the data frame

To make sure Grafana recognizes data as logs and shows logs visualization automatically in Explore, set `meta.preferredVisualisationType` to `'logs'` in the returned data frame. See [Selecting preferred visualisation section]({{< relref "add-support-for-explore-queries/#selecting-preferred-visualisation" >}})

**Example:**

```ts
const frame = new MutableDataFrame({
  refId: query.refId,
  meta: {
    preferredVisualisationType: 'logs',
  },
  fields: [
    { name: 'time', type: FieldType.time },
    { name: 'content', type: FieldType.string },
  ],
});
```

### Add labels to your logs

Many log systems let you query logs based on metadata, or _labels_, to help filter log lines.

Add labels to a stream of logs by setting the `labels` property on the Field.

**Example**:

```ts
const frame = new MutableDataFrame({
  refId: query.refId,
  fields: [
    { name: 'time', type: FieldType.time },
    { name: 'content', type: FieldType.string, labels: { filename: 'file.txt' } },
  ],
});

frame.add({ time: 1589189388597, content: 'user registered' });
frame.add({ time: 1589189406480, content: 'user logged in' });
```

### Extract detected fields from your logs

Add additional information about each log line by supplying more data frame fields.

If a data frame has more than one text field, then Grafana assumes the first field in the data frame to be the actual log line. Grafana treats subsequent text fields as [detected fields]({{< relref "../../explore/#labels-and-detected-fields" >}}).

Any number of custom fields can be added to your data frame; Grafana comes with two dedicated fields: `levels` and `id`.

#### Levels

To set the level for each log line, add a `level` field.

**Example:**

```ts
const frame = new MutableDataFrame({
  refId: query.refId,
  fields: [
    { name: 'time', type: FieldType.time },
    { name: 'content', type: FieldType.string, labels: { filename: 'file.txt' } },
    { name: 'level', type: FieldType.string },
  ],
});

frame.add({ time: 1589189388597, content: 'user registered', level: 'info' });
frame.add({ time: 1589189406480, content: 'unknown error', level: 'error' });
```

#### 'id' for assigning unique identifiers to log lines

By default, Grafana offers basic support for deduplicating log lines. You can improve the support by adding an `id` field to explicitly assign identifiers to each log line.

**Example:**

```ts
const frame = new MutableDataFrame({
  refId: query.refId,
  fields: [
    { name: 'time', type: FieldType.time },
    { name: 'content', type: FieldType.string, labels: { filename: 'file.txt' } },
    { name: 'level', type: FieldType.string },
    { name: 'id', type: FieldType.string },
  ],
});

frame.add({ time: 1589189388597, content: 'user registered', level: 'info', id: 'd3b07384d113edec49eaa6238ad5ff00' });
frame.add({ time: 1589189406480, content: 'unknown error', level: 'error', id: 'c157a79031e1c40f85931829bc5fc552' });
```