Manage Datasets

Datasets are created programmatically when you send data to Honeycomb. Once you create a dataset, you can manage it using the Honeycomb UI.

Create Dataset 

To send data to Honeycomb, you must instrument your service and then make requests to it. Making requests to your service will generate telemetry data and send it to Honeycomb where it will appear in the Honeycomb UI within seconds.

When you send data to Honeycomb, Honeycomb creates a Dataset in which to store your data, using the service name in your instrumentation as the Dataset’s name. Once created, Dataset names are permanent. Honeycomb determines which Environment to should house your Dataset based on the API Key with which you send the data.

You cannot create a Dataset through the Honeycomb UI.

Add Description 

To add your Dataset’s description:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset for which you want to add a description.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset for which you want to add a description, and select its name to view the available settings.

  6. Locate the Description section, and select Add a description for this dataset.

  7. Enter a description, and select Save Changes.

Change Description 

To change your Dataset’s description:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset for which you want to change the description.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset for which you want to change the description, and select its name to view the available settings.

  6. Locate the Description section, and select Edit.

  7. Enter a new description, and select Save Changes.

Set Default Granularity 

For periodic data captured at regular, known intervals, such as metric data, you can set a minimum default granularity, or interval, to ensure that queries within the Dataset do not drop below it (unless you choose to override it manually when building an individual query).

Default Granularity affects the display of visualizations seen:

  • after running a query
  • on Honeycomb Home
  • as suggested queries on a blank query page

To set your Dataset’s default granularity:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset for which you want to set the default granularity.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset for which you want to set the default granularity, and select its name to view the available settings.

  6. Locate the Default Granularity section, and select the desired interval from the dropdown.

    Tip
    To prevent a spiky appearance in your graphs, we recommend that you set the default granularity with the interval at which data enters Honeycomb. For example, if your data enters the dataset at regular 30-second intervals, we recommend setting a default granularity of 30 seconds.

We save your changes automatically.

Set Suggested Queries 

For each Dataset, you can select a Board to provide suggested queries, which will appear any time you land on a blank query page.

To set your Dataset’s suggested queries:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset for which you want to set suggested queries.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset for which you want to set suggested queries, and select its name to view the available settings.

  6. Locate the Suggested Queries section, and select the desired Board from the dropdown. You must select a public Board that contains named queries. Multiple datasets can use the same board.

We save your changes automatically.

Set Default Correlations Board 

For each Dataset, you can select a Board to appear in the Correlations view of your query results. The order of the charts in the Correlations view matches the order of the charts on the Board.

To set your Dataset’s default Correlations Board:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset for which you want to set a default Correlations Board.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset for which you want to set a default Correlations Board, and select its name to view the available settings.

  6. Select the Correlations view.

  7. Locate the Default Correlations Board section, and select the desired Board from the dropdown. You must select a public Board. Multiple datasets can use the same board.

We save your changes automatically.

Delete Dataset 

Warning

Dataset deletion is permanent, so make sure you really want to delete your Dataset before doing so.

To delete a Dataset, you must be a Team Owner, and Deletion Protection must be disabled.

To delete your Dataset:

  1. Log in to the Honeycomb UI.

  2. Select the Environments label on the top-left, then select the Environment that contains the Dataset you want to delete.

  3. In the left navigation menu, select Manage Data.

  4. In the list, locate and select Datasets.

  5. In the list, locate the Dataset that you want to delete, and select its name to view the available settings.

  6. Select the Delete view.

  7. If Deletion Protection is enabled for the Dataset, toggle it ‘off’ to enable the Delete Dataset button.

  8. Select Delete Dataset.

  9. In the Delete Dataset? modal, enter the unique identifier of the Dataset (listed in parentheses).

  10. Select I understand the consequences. Delete this dataset.

Your Dataset will be deleted, but it may take several minutes for the process to complete.