Queries

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Queries populate your app with data from Datadog APIs or supported integrations. They take inputs from other queries or from UI components and return outputs for use in other queries or in UI components.

The Action Catalog within the Datadog App provides actions that can be performed as queries against your infrastructure and integrations using App Builder. You can orchestrate and automate your end-to-end processes by linking together actions that perform tasks in your cloud providers, SaaS tools, and Datadog accounts.

To add a query, click the plus (+) icon in the Queries section and search for an action to add to your app. After you’ve added the query action, it appears in the query list above the query editor. Click and drag queries to reorder them. Select a query to configure it.

Queries rely on Connections for authentication. App Builder shares connections with Workflow Automation.

Run settings

Run Settings determine when a query is executed. There are two options:

  • Auto: The query runs when the app loads and whenever any query arguments change.
  • Manual: The query runs when another portion of the app triggers it. For example, use a manual trigger if you want a query to execute only when a user clicks a UI button component. For more information on event triggers, see Events.

Advanced query options

Debounce

Configuring debounce ensures that your query is only triggered once per user input. By default, debounce is set to 0 milliseconds (ms). To prevent a query from being called too frequently, increase the debounce. Configure debounce in the Advanced section of a query.

Conditional queries

You can set a condition that must be met before a query can run. To set the condition for a query, enter an expression in the Condition field in the Advanced section of the query. This condition must evaluate to true before the query can run. For example, if you want a given query to run only if a UI component named select0 exists and is not empty, use the following expression:

${select0.value && select0.value.length > 0}

Post-query transformation

Perform a post-query transformation to simplify or transform the output of a query. Add a post-query transformation in the Advanced section of a query.

For example, the Slack List Channels action returns an array of dictionaries containing the ID and name for each channel. To discard the IDs and return only an array of names, add the following query transformation:

// Use `outputs` to reference the query's unformatted output.
// TODO: Apply transformations to the raw query output
arr = []
object = outputs.channels
for (var item in object) {
    arr.push(object[item].name);
}

return arr

Post-query hooks

Similar to UI component events, you can configure a reaction to trigger after a query executes. A post-query hook can set a UI component state, open or close a modal, trigger another query, or even run custom JavaScript. For example, the ECS Task Manager blueprint’s scaleService query uses a post-query hook to rerun the describeService query after it executes.

You can use state functions in post-query hooks.

Error notifications

To display a toast (a brief notification message) to the user when the system returns an error, toggle Show Toast on Errors in the Advanced section of a query.

Confirmation prompts

To prompt a user for confirmation before the query runs, toggle the Requires Confirmation option in the Advanced section of a query.

Polling intervals

To run a query repeatedly at a set interval while the app is open on someone’s screen, enter the interval in milliseconds (ms) as the Polling interval in the Advanced section of a query.

Note: The query does not run in the background; it only runs when someone has the app open.

Mocked outputs

Sometimes when you are building or testing an app in the editor, you might want to avoid executing a real query, or avoid executing the same query repeatedly. When you enable Mocked outputs and run your query, App Builder populates outputs with mocked data instead of running the query action.

You can generate mocked outputs from a previous query run or provide them manually.

Generate outputs from previous run

To generate mocked output data from a previous query run, perform the following steps:

  1. Add a query and fill out the rest of your query’s parameters.
  2. Click Run to execute your query once.
  3. In the Mocked outputs section of the query, click the Generate tab.
  4. Click Generate from outputs. This automatically toggles Use Mocked Outputs on.
    The Run button changes to say Run (Mocked), and the next time you run your query, the output populates with the mocked data.

Provide outputs manually

To provide mocked outputs manually, perform the following steps:

  1. Add a query and fill out the rest of your query’s parameters.
  2. In the Mocked outputs section of the query, click the GUI tab.
  3. Fill in all required fields, which the GUI view automatically displays.
  4. Optionally, to add additional fields, click + (plus). Choose a key from the dropdown and fill in a value. If you want to enter a value that is an object or an array, click the {} or [], respectively, after the Enter value field.
  1. Add a query and fill out the rest of your query’s parameters.
  2. In the Mocked outputs section of the query, click the JSON tab.
  3. Paste in JSON that matches the expected output format of the query.
    If you do not know the expected output format, you can run the query once and then reference outputs in the Inspect Data section of the query.

Order of operations

When executing a query, App Builder performs the following steps in the order listed:

  1. Checks if there is a Condition expression for the query, and if so, checks that the condition is met. If it is not, execution stops.
  2. Evaluates any expressions in Inputs to determine the input data for the query.
  3. If the Debounce property is set, delays execution for the interval defined by the debounce value. If query inputs or their dependencies update during this time, the current query execution is stopped, and a new one starts from the beginning using the updated inputs.
    Note: If more than one query request occurs within the debounce interval, all requests except the last execution request are canceled.
  4. Executes the query.
  5. Stores the raw query response in query.rawOutputs.
  6. Runs any post query transformation and sets query.outputs equal to the result. This process takes a snapshot of app data and passes it to the post query transformation.
    Note: Post query transformations should be pure functions without side effects. For example, do not update a state variable in your post query transformation.
  7. Computes any expressions in the app that depend on data from the query output.
  8. Runs all Reactions from the app’s Events, in the order in which they are defined in the UI. This involves taking a snapshot of the app which is used throughout the reaction’s run. A new snapshot is taken before each reaction runs, and changes made by a previous reaction are visible to a subsequent reaction.
  9. If there is a Polling interval set, schedules the query to re-run the defined number of milliseconds in the future.

Example apps

Return workflow results to an app

App Builder queries can trigger Workflow Automation workflows. Apps can then use the results of those workflows.

This app provides a button to trigger a workflow. The workflow sends a poll to a Slack channel asking the user to pick from one of two options. Based on the option the user chooses, the workflow issues one of two different HTTP GET requests, which then returns data that is displayed in the app.

Create workflow
  1. In a new workflow canvas, under Datadog Triggers, click App.
  2. Under the App trigger step, click the plus (+) icon, then search for “Make a decision” and select the Make a decision Slack action.
  3. Select your workspace and choose a channel to poll.
  4. Fill in the prompt text “Cat fact or dog fact?” and change the button choices to “Cat fact” and “Dog fact”.
  5. Under the Make a decision step in the canvas, click the plus (+) icon above Cat fact and add the Make request HTTP action.
  6. Name the step “Get cat fact”. Under Inputs, for the URL, keep GET selected and enter the URL https://catfact.ninja/fact.
  7. Under the Make a decision step in the canvas, click the plus (+) icon above Dog fact. Follow the same steps to add the Make request HTTP action, but this time name the step “Get dog fact” and use the following parameters:
    • URL: https://dogapi.dog/api/v2/facts.
    • Request Headers: Content-Type of application/json
  8. Click the plus (+) icon under the cat fact step. Search for “Function” and choose the Function data transformation step.
  9. Connect the plus (+) icon under the dog fact step to this JS Function step by clicking and dragging from the plus to the dot that appears above the JS Function step.
  10. In the JS Function, under Configure, for Script, use the following code snippet:
    const catFact = $.Steps.Get_cat_fact?.body?.fact;
const dogFactRaw = $.Steps.Get_dog_fact?.body;

let dogFact;

try {
    const parsedDogFact = JSON.parse(dogFactRaw);
    dogFact = parsedDogFact.data?.[0]?.attributes?.body;
} catch {
    // Do nothing
}

return catFact != null ? catFact : dogFact;
  11. In the workflow overview, under Output Parameters, add a parameter named output with the value {{ Steps.Function.data }} and the Data Type string.
  12. Name your workflow “My AB Workflow”, then save and publish the workflow.
Create app

To connect App Builder to the workflow, perform the following steps:

  1. In your app, under Queries, click + New Query.
  2. Search for “Trigger Workflow” and select the Trigger Workflow Datadog Workflow Automation item.
  3. Set Run Settings to Manual and name the query triggerWorkflow0.
  4. Under Inputs, for App Workflow, select My AB Workflow.
  5. Click Run to run the workflow, then go to your Slack channel and answer the poll question. This gives App Builder example data to display.
  6. Add a text component. Under Content, enter the expression ${triggerWorkflow0?.outputs?.workflowOutputs?.output}.
  7. Add a button component. Use the following values:
    • Label: “Trigger Workflow”
    • Is Loading: ${triggerWorkflow0.isLoading} (click </> to enter an expression)
  8. Under the button’s Events, click the plus (+) to add an event. Use the following values:
    • Event: click
    • Reaction: Trigger Query
    • Query: triggerWorkflow0
  9. Save your app.
Test app
  1. In your app, click Preview.
  2. Click the Trigger Workflow button.
  3. In the Slack channel you selected, answer the poll question.
    Your app displays a result related to the option you chose.

Combine and transform query output data

After you get data from a query in App Builder, you can use data transformers to combine and transform that data.

This app provides buttons to fetch facts about two numbers from an API. It then uses a data transformer to calculate and display the sum of the two numbers.

Create queries
  1. In a new app, click + New Query. Search for “Make request” and choose the HTTP Make request action.
  2. Use the following values:
    • Name: mathFact1
    • Under Inputs, for URL: GET http://numbersapi.com/random/trivia
  3. Click the + (plus) to add another HTTP Make request query. Use the following values:
    • Name: mathFact2
    • Under Inputs, for URL: GET http://numbersapi.com/random/trivia
Add data transformer
  1. Click the Σ (sigma) to open the Transformers panel.
  2. Click + Create Transformer.
  3. Name the transformer numberTransformer. Under Inputs, under function () {, enter the following:
    // get both random facts
const fact1 = mathFact1.outputs.body;
const fact2 = mathFact2.outputs.body;

// parse the facts to get the first number that appears in them
const num1 = fact1.match(/\d+/)[0];
const num2 = fact2.match(/\d+/)[0];

// complete arithmetic on the numbers to find the sum
const numSum = Number(num1) + Number(num2)

return numSum
Create app canvas components
  1. In the app canvas, add a button and fill in the label “Generate fact 1”.
  2. Under the button’s Events, use the following values:
    • Event: click
    • Reaction: Trigger Query
    • Query: mathFact1
  3. Add another button and fill in the label “Generate fact 2”.
  4. Under the button’s Events, use the following values:
    • Event: click
    • Reaction: Trigger Query
    • Query: mathFact2
  5. Add a text element under the first button. For its Content property, click the </> and enter the expression ${mathFact1.outputs.body}.
  6. Add a text element under the second button. For its Content property, click the </> and enter the expression ${mathFact2.outputs.body}.
  7. Add a text element with the Content value “Sum of numbers”.
  8. Add a text element next to it. For its Content property, click the </> and use the expression ${numberTransformer.outputs}.
Test app
  1. In your app, click Preview.
  2. Click Generate fact 1, then click Generate fact 2.
    Your app updates the number facts and the sum of the numbers as you click each button.

Further reading

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