How to use AWS IoT TwinMaker knowledge graph with Grafana - AWS IoT TwinMaker

How to use AWS IoT TwinMaker knowledge graph with Grafana

This section shows you how to add a query editor panel to your AWS IoT TwinMaker Grafana dashboard to run and display queries.

AWS IoT TwinMaker query editor prerequisites

Before you use the AWS IoT TwinMaker knowledge graph in Grafana, complete the following prerequisites:

Note

To use the AWS IoT TwinMaker knowledge graph, you need to be in either the standard or tiered bundle pricing modes. For more information, see Switch AWS IoT TwinMaker pricing modes.

AWS IoT TwinMaker query editor permissions

To use the AWS IoT TwinMaker query editor in Grafana, you must have an IAM role with permission for the action iottwinmaker:ExecuteQuery. Add that permission to your workspace dashboard role, as shown in this example:

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:GetObject" ], "Resource": [ "{s3Arn}", "{s3Arn}/" ] }, { "Effect": "Allow", "Action": [ "iottwinmaker:Get", "iottwinmaker:List", "iottwinmaker:ExecuteQuery" ], "Resource": [ "{workspaceArn}", "{workspaceArn}/*" ] }, { "Effect": "Allow", "Action": "iottwinmaker:ListWorkspaces", "Resource": "*" } ] }
Note

When you configure your AWS IoT TwinMaker Grafana data source, make sure to use the role with this permission for the Assume role ARN field. After you add it, you can select your workspace from the dropdown next to Workspace.

For more information, see Creating a dashboard IAM role.

Set up the AWS IoT TwinMaker query editor panel

To set up a new Grafana dashboard panel for knowledge graph
  1. Open your AWS IoT TwinMaker Grafana dashboard.

  2. Create a new dashboard panel. For detailed steps on how to create a panel, see Create a dashboard in the Grafana documentation.

  3. From the list of visualizations, select AWS IoT TwinMaker Query Editor.

    The dropdown list in the AWS IoT TwinMaker dashboard contains the option for the 
                            AWS IoT TwinMaker Query Editor.
  4. Select the data source to run queries against.

  5. (Optional) Add a name for the new panel in the provided field.

  6. Select Apply to save and confirm your new panel.

The knowledge graph panel works in a similar way as the query editor provided in the AWS IoT TwinMaker console. You can run, write, and clear queries you make in the panel. For more information on how to write queries, see AWS IoT TwinMaker knowledge graph additional resources.

How to use the AWS IoT TwinMaker query editor

The results of your queries are displayed in three ways, as shown in the following images: visualized in a graph, listed in a table, or presented as a run summary.

  • Graph visualization:

    AWS IoT TwinMaker query editor results displayed as a Visual graph.

    The visual graph only displays data for queries that have at least one relation in the result. The graph displays entities as nodes and relationships as directed edges in the graph.

  • Tabular data:

    AWS IoT TwinMaker query editor results displayed as tabular data.

    The tabular data format displays the data for all queries. You can search the table for specific results or subsets of the results. The data can be exported in JSON or CSV format.

  • Run summary

    AWS IoT TwinMaker query editor results displayed as a run summary.

    The run summary displays the query and metadata about the status of the query.