--- title: "TestData query editor | Grafana documentation" description: "Reference for the TestData query editor and all available scenarios." --- > For a curated documentation index, see [llms.txt](/llms.txt). For the complete documentation index, see [llms-full.txt](/llms-full.txt). # TestData query editor Instead of a traditional query language, the TestData data source uses **scenarios** to generate simulated data. Each scenario produces a different type of data suited for testing specific visualizations, behaviors, or edge cases. TestData includes 30 scenarios covering time series, logs, traces, graphs, streaming, and error simulation. Use scenarios to: - **Prototype dashboards** without connecting to a real data source. - **Reproduce bugs** with controlled, deterministic data that other developers can replicate. - **Test panel behavior** with edge cases like empty results, timestamps outside the visible range, or mixed data and errors. - **Validate alerting pipelines** using predictable patterns that fire and resolve on a known schedule. - **Simulate streaming** to verify how panels handle real-time data updates. To build a query, select a scenario from the **Scenario** drop-down. The query editor updates to show fields specific to that scenario. Click **Run queries** or use the keyboard shortcut to execute. > Note > > Some scenarios run entirely in the browser (Streaming Client, Grafana Live, Grafana API, Steps, No Data Points). These scenarios don’t send queries to the backend, which means they can’t be used with [Grafana Alerting](/docs/grafana/latest/datasources/testdata/alerting/) or in any context that requires server-side evaluation. ## Scenario reference The scenarios are organized into the following categories. Use the table below to find the right scenario for your use case. Expand table | Scenario | Category | Purpose | |---------------------------------------------------------------------|-----------------------|----------------------------------------------------| | [Random Walk](#random-walk) | Data generation | Random walk time series (default scenario). | | [Random Walk Table](#random-walk-table) | Data generation | Random walk in table format with `Enum` state. | | [Random Walk (with error)](#random-walk-with-error) | Data generation | Random walk that also returns an error. | | [Predictable Pulse](#predictable-pulse) | Data generation | Repeating on/off wave based on absolute time. | | [Predictable CSV Wave](#predictable-csv-wave) | Data generation | Custom repeating waveforms from CSV values. | | [Simulation](#simulation) | Data generation | Continuous simulation engine (flight, sine, tank). | | [USA generated data](#usa-generated-data) | Data generation | Multi-dimensional data with US state dimensions. | | [CSV Content](#csv-content) | Manual input | Paste or type CSV data directly. | | [Steps](#steps) | Manual input | Step-function data from CSV input. | | [CSV File](#csv-file) | Manual input | Select from built-in CSV data files. | | [CSV Metric Values](#csv-metric-values) | Manual input | Time series from comma-separated values. | | [Raw Frames](#raw-frames) | Manual input | Define data frames in JSON format. | | [Load Apache Arrow Data](#load-apache-arrow-data) | Manual input | Render base64-encoded Arrow payloads. | | [Table Static](#table-static) | Manual input | Static table with predefined columns. | | [Logs](#logs) | Visualization testing | Simulated log data with random levels. | | [Node Graph](#node-graph) | Visualization testing | Data for node graph visualizations. | | [Flame Graph](#flame-graph) | Visualization testing | Data for flame graph visualizations. | | [Trace](#trace) | Visualization testing | Simulated distributed trace data. | | [Annotations](#annotations) | Visualization testing | Annotation data points. | | [Exponential heatmap bucket data](#exponential-heatmap-bucket-data) | Visualization testing | Heatmap data with exponential buckets. | | [Linear heatmap bucket data](#linear-heatmap-bucket-data) | Visualization testing | Heatmap data with linear buckets. | | [Streaming Client](#streaming-client) | Streaming | Browser-side streaming (signal, logs, traces). | | [Grafana Live](#grafana-live) | Streaming | Server-side streaming via live channels. | | [Grafana API](#grafana-api) | Data retrieval | Fetch data from internal Grafana endpoints. | | [Conditional Error](#conditional-error) | Error testing | Configurable error or CSV data. | | [Error with source](#error-with-source) | Error testing | Error with plugin or downstream classification. | | [No Data Points](#no-data-points) | Error testing | Empty result with no data. | | [Data Points Outside Range](#datapoints-outside-range) | Error testing | Data point outside the visible time range. | | [Slow Query](#slow-query) | Error testing | Configurable delay before returning data. | | [Query Metadata](#query-metadata) | Metadata | Returns query context metadata. | ## Shared query options Every scenario displays the **Scenario** drop-down. Most scenarios also show an **Alias** field and, when the scenario defines a default, a **String Input** field. Some scenarios expose additional shared controls. Scenario-specific options appear below these fields. Expand table | Field | Description | |------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | **Scenario** | Drop-down to select the data generation type. Scenarios are listed alphabetically. | | **Alias** | Optional display name for the series. Hidden for the Simulation and Annotations scenarios. Supports the special values `__server_names` and `__house_locations` to use built-in name sets. | | **String Input** | Text field shown when the selected scenario provides a default string value. Used differently by each scenario. | | **Labels** | Available for Random Walk and Predictable Pulse. Set labels using key=value syntax, for example `key="value", key2="value2"`. Use `$seriesIndex` in a value to insert the series index. | | **Drop percent** | Available for CSV Content and CSV File. Drops a random percentage (0-100) of data points from the result. | ## Data generation scenarios These scenarios produce time-series data with configurable parameters. ### Random Walk Generates random walk time-series data. This is the default scenario. Expand table | Field | Description | |------------------|---------------------------------------------------------| | **Series count** | Number of series to generate. Default: `1`. | | **Start value** | Initial value for the walk. Default: auto (random). | | **Min** | Minimum value the walk can reach. Default: none. | | **Max** | Maximum value the walk can reach. Default: none. | | **Spread** | Controls how far each step can deviate. Default: `1`. | | **Noise** | Adds noise to each data point. Default: `0`. | | **Drop (%)** | Percentage of points to randomly exclude. Default: `0`. | ### Random Walk Table Generates random walk data in table format with columns for Time, Value, Min, Max, Info, and State. The State column uses an `enum` field with values Unknown, Up, and Down. Optionally includes null values when **withNil** is enabled. ### Random Walk (with error) Generates random walk time-series data and also returns an error in the response. Use this to test how panels handle data responses that contain both data and errors. ### Predictable Pulse Generates a predictable pulse wave based on absolute time from the epoch, making it reproducible across runs. Expand table | Field | Description | |---------------|---------------------------------------------------------------------------------------| | **Step** | Seconds between data points. Default: `60`. | | **On Count** | Number of data points at the start of each cycle that use the on value. Default: `3`. | | **Off Count** | Number of data points in each cycle that use the off value. Default: `3`. | | **On Value** | The value for “on” data points. Can be a number, `null`, or `nan`. Default: `2`. | | **Off Value** | The value for “off” data points. Can be a number, `null`, or `nan`. Default: `1`. | The wave cycles at `Step * (On Count + Off Count)` seconds. Timestamps align evenly on the step interval. With the defaults (Step=60, On Count=3, Off Count=3), the wave completes a full cycle every 6 minutes. The on value (`2`) holds for the first 3 data points, then the off value (`1`) holds for the next 3. ### Predictable CSV Wave Generates one or more predictable waves from CSV-defined values. Each wave cycles through its comma-separated values at a fixed time step. Expand table | Field | Description | |------------|-------------------------------------------------------------------------------------------------| | **Values** | Comma-separated numeric values for the wave. Supports `null` and `nan`. Default: `0,0,2,2,1,1`. | | **Step** | Seconds between data points. Default: `60`. | | **Name** | Optional name for the series. | | **Labels** | Optional labels in key=value format. | Click the **+** button on the last wave row to add another wave. Click the **-** button on any other row to remove it. For example, to create two overlapping waves for comparison: - Wave 1: Values `0,1,2,3,4,5`, Step `60`, Name `rising` - Wave 2: Values `5,4,3,2,1,0`, Step `60`, Name `falling` ### Simulation Runs a simulation engine that generates data continuously. Simulation supports streaming data through Grafana Live. Expand table | Field | Description | |----------------|----------------------------------------------------------------------------------------------------------------| | **Simulation** | Simulation type: `Flight` (circling flight path), `Sine` (sine wave), or `Tank` (fill and drain a water tank). | | **Stream** | Toggle to stream data through Grafana Live instead of returning a static result. | | **Interval** | Tick frequency in Hz. Default: `10`. | | **Last** | Toggle to return only the most recent value instead of the full time range. | | **UID** | Optional unique identifier. Allows multiple instances of the same simulation type to run concurrently. | ### USA generated data Generates data with US state dimensions. Useful for testing geo-map visualizations and multi-dimensional data. Expand table | Field | Description | |------------|--------------------------------------------------------------------------------------------------------------------| | **Mode** | Data format: `values-as-rows`, `values-as-fields`, `values-as-labeled-fields`, `timeseries`, or `timeseries-wide`. | | **Period** | Time period for data generation. Default: `30m`. | | **Fields** | Fields to include: `foo`, `bar`, `baz`. Default: all. | | **States** | US state codes to include (for example, `CA`, `NY`, `TX`). Default: all 50 states plus DC. | ## Manual input scenarios These scenarios let you provide your own data directly instead of generating it. ### CSV Content Provides a text editor where you paste or type CSV data directly. The first row is treated as headers. Use the **Drop percent** field to randomly exclude a percentage of data points. For example, enter the following to create a time series with two value columns: ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy ```none Time,Temperature,Humidity 2024-01-01 00:00:00,22.5,45 2024-01-01 01:00:00,21.8,48 2024-01-01 02:00:00,20.1,52 ``` ### Steps Provides a CSV text area (the same editor as CSV Content) for defining step-function data. The default content is `a`, `b`, `c`. This scenario is handled entirely in the browser. ### CSV File Selects from a set of built-in CSV data files. Use the **Drop percent** field to randomly exclude a percentage of data points. Available files: - `flight_info_by_state.csv` - `population_by_state.csv` - `gdp_per_capita.csv` - `js_libraries.csv` - `ohlc_dogecoin.csv` - `weight_height.csv` - `browser_marketshare.csv` - `automobiles.csv` ### CSV Metric Values Generates time-series data from comma-separated values entered in the **String Input** field. Values are evenly distributed across the selected time range. Default: `1,20,90,30,5,0`. For example, with the default values and a 6-hour time range, the six values (`1`, `20`, `90`, `30`, `5`, `0`) are spread across the range at equal intervals. ### Raw Frames Provides a JSON editor for defining data frames directly. The editor accepts the Grafana data frame JSON format and includes paste helpers for panel JSON and raw query results. ### Load Apache Arrow Data Loads data from a base64-encoded Apache Arrow payload entered in the **String Input** text area. Use this to test Arrow format rendering. ### Table Static Generates a static table with predefined columns: Time, Message, Description, and Value. ## Visualization test scenarios These scenarios generate data for testing specific visualization types. ### Logs Generates simulated log data with random log levels, container IDs, and hostnames. Expand table | Field | Description | |-----------|--------------------------------------------------------------------------------------------| | **Lines** | Number of log lines to generate. Default: `10`. Maximum: `10000`. | | **Level** | Toggle to include a separate level column in the data instead of embedding it in messages. | ### Node Graph Generates data for the [Node Graph visualization](/docs/grafana/latest/panels-visualizations/visualizations/node-graph/). Expand table | Field | Description | |---------------|-----------------------------------------------------------------------------------------------------------| | **Data type** | Type of graph data: `random`, `response_small`, `response_medium`, `random edges`, or `feature_showcase`. | | **Count** | Number of nodes to generate. Available for `random` and `random edges` types. | | **Seed** | Seed value for reproducible random generation. Available for `random` and `random edges` types. | ### Flame Graph Generates data for the [Flame Graph visualization](/docs/grafana/latest/panels-visualizations/visualizations/flame-graph/). Expand table | Field | Description | |------------------|-----------------------------------------------------------------------| | **Diff profile** | Toggle to generate a differential flame graph comparing two profiles. | ### Trace Generates simulated distributed trace data. Expand table | Field | Description | |----------------|-----------------------------------------| | **Span count** | Number of spans in the generated trace. | ### Annotations Generates synthetic annotation data points. These annotations are created entirely in the browser and are useful for testing how panels display annotation markers and overlays. They don’t query an external source or persist data. For more information about annotations in Grafana, refer to [Annotate visualizations](/docs/grafana/latest/dashboards/build-dashboards/annotate-visualizations/). Expand table | Field | Description | |-----------|---------------------------------------------------| | **Count** | Number of annotations to generate. Default: `10`. | ### Exponential heatmap bucket data Generates heatmap data with exponentially distributed bucket boundaries (1, 2, 4, 8, 16, …). Use this to test heatmap panels with exponential distributions. ### Linear heatmap bucket data Generates heatmap data with linearly distributed bucket boundaries (0, 10, 20, 30, …). Use this to test heatmap panels with linear distributions. ## Streaming scenarios These scenarios produce real-time streaming data. Data updates continuously in the browser without requiring manual query execution. ### Streaming Client Generates streaming data directly from the browser client. Expand table | Field | Description | |----------|---------------------------------------------------------------| | **Type** | Stream type: `Signal`, `Logs`, `Fetch`, `Traces`, or `Watch`. | Additional fields depend on the selected type: - **Signal:** Speed (ms), Spread, Noise, Bands. - **Logs, Traces, Watch:** Speed (ms) only. - **Fetch:** URL of a remote CSV endpoint to stream incrementally. ### Grafana Live Connects to a Grafana Live channel that streams random data from the server. Expand table | Field | Description | |-------------|--------------------------------------------| | **Channel** | The live channel to subscribe to. Options: | Expand table | Channel | Description | |-------------------------|-----------------------------------------------| | `random-2s-stream` | Random stream with points every 2s. | | `random-flakey-stream` | Stream that returns data at random intervals. | | `random-labeled-stream` | Value with moving labels. | | `random-20Hz-stream` | Random stream with points at 20 Hz. | ## Data retrieval scenarios These scenarios fetch data from internal Grafana endpoints. ### Grafana API Fetches data from internal Grafana API endpoints and returns the result as a data frame. This scenario runs in the browser. Expand table | Field | Description | |--------------|-------------------------------------| | **Endpoint** | The API endpoint to query. Options: | Expand table | Endpoint | Description | |------------------|-----------------------------------| | **Data Sources** | Lists configured data sources. | | **Search** | Returns dashboard search results. | | **Annotations** | Returns annotations. | ## Error and edge-case testing scenarios These scenarios help test how Grafana handles errors, empty data, and slow responses. ### Conditional Error Produces an error or data depending on the **String Input** and **Error type** fields. When the **String Input** field is empty, the scenario triggers the selected error type. When the field contains CSV values (default: `1,20,90,30,5,0`), it returns time-series data like the CSV Metric Values scenario, regardless of the error type. Expand table | Field | Description | |----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | **Error type** | Type of error to simulate: `Server panic` (backend panic), `Frontend exception` (uncaught error in the browser), or `Frontend observable` (error emitted through the query observable). | To trigger an error, clear the **String Input** field and select the error type you want to test. ### Error with source Returns an error with a configurable source classification. Expand table | Field | Description | |------------------|------------------------------------------------------------------------------------------| | **Error source** | Source of the error: `Plugin` (plugin error) or `Downstream` (downstream service error). | Use this to test how Grafana differentiates between plugin errors and downstream errors in alerting and error handling. ### No Data Points Returns an empty result with no data points. Use this to test how panels display when there’s no data. ### Data points Outside Range Returns a single data point with a timestamp one hour before the query time range. Use this to test how panels handle data outside the visible range. ### Slow Query Introduces a configurable delay before returning random walk data. Set the delay duration in the **String Input** field using Go duration syntax (for example, `5s`, `1m`, `500ms`). Default: `5s`. ## Metadata scenarios These scenarios return metadata rather than time-series data. ### Query Metadata Returns a table with query metadata including the current user’s username. Use this to verify that query context information is available.