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# Custom Dashboard Feature
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# Custom Dashboards as Code
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Welcome to the Custom Dashboard! This feature allows you to create and manage personalized dashboards to monitor and visualize your data effectively.
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Build custom dashboards to track workflow `executions`, `logs` and `metrics` filtered by specific namespaces or labels and showing data you care about.
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## Create a new Dashboard as code
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The declarative syntax allows you to manage dashboards as code — you can version control that dashboard definition alongside your flows.
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Below is an example of a dashboard definition that displays executions over time, a table that uses metrics to display the sum of sales per namespace, and a table that shows the log count by level per namespace:
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## Example
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Below is an example dashboard definition that displays:
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-**time series** of **executions** over time
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-**table** with specific **metrics** aggregated per namespace
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-**table** with **logs** aggregated per log level and namespace.
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```yaml
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title: Getting Started
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- prod_graph
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```
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To see all available properties to configure a custom dashboard as code, see examples provided in the [Enterprise Edition Examples](https://github.com/kestra-io/enterprise-edition-examples) repository.
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For more examples, check our [GitHub repository](https://github.com/kestra-io/enterprise-edition-examples) and explore Dashboard Blueprints.
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## Querying data
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The `data` property of a chart defines the type of data that is queried and displayed. The `type` determines which columns are displayed.
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The `data` property of a chart defines the type of data that is queried. The `type` determines which columns are displayed.
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Dashboards can query data from these source `types`:
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- `type: io.kestra.plugin.core.dashboard.data.Executions`: data related to your workflow executions
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- `type: io.kestra.plugin.core.dashboard.data.Logs`: logs produced by your workflows
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- `type: io.kestra.plugin.core.dashboard.data.Metrics`: metrics emitted by your plugins
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After defining the data source, specify the columns to display in the chart. Each column is defined by the `field` and may include additional optional properties.
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- `type: io.kestra.plugin.core.dashboard.data.Logs`: logs produced by your executions
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- `type: io.kestra.plugin.core.dashboard.data.Metrics`: metrics emitted during executions.
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After defining the data source, specify the **columns** to display in the chart. Each column is defined by the `field` and may include additional optional properties.
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| `columnAlignment` | Specifies the alignment of the column in the table: supported alignments include `LEFT`, `RIGHT`, `CENTER` |
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You can also use the `where` property to set conditions that filter the result set before displaying it in the chart. Filters can apply to any column in the data source. For shared logic, use the `AND` operator in the `where` property to combine several conditions. If multiple conditions are needed with different logic, use the `type: OR` property.
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You can also use the `where` property to set conditions that filter the result set before displaying it in the chart. Filters can apply to any column in the data source. For shared logic, use the `AND` operator in the `where` property to combine several conditions. If multiple conditions are needed with a different logic, use the `type: OR` property.
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