Web API On-Prem plugin

The Web API plugin allows you to query data from any HTTP API that returns JSON and visualize that data. This is particularly useful if there isn't a SquaredUp plugin available for your data source.

Configuring and deploying an agent

If you have already created an agent in SquaredUp that you can use for this data source, you can skip this step and choose the agent group you want to use while Configuring the data source.

See one of the following, depending on your platform type:

• Configuring an agent (Windows platforms)
• Configuring an agent (Linux platforms)

Configuring the data source

To add a data source click on the + next to Data Sources on the left-hand menu in SquaredUp. Search for the data source and click on it to open the Configure data source page.

1. Display Name:
   Enter a name for your data source. This helps you to identify this data source in the list of your data sources.

   You may find it useful to put the API URL in the display name.

2. Agent Group:
   Select the Agent Group that contains the agent(s) you want to use.

3. Base URL:
   Enter the base URL of the API to be used for requests, for example https://www.googleapis.com/
4. Query arguments:
   Add any parameters that should be added to the Base URL.
5. Authentication:
   • None: No authentication required.
   • Basic: You must enter a Username and Password.
   • OAuth 2: Token-based authentication according to the OAuth 2.0 standard. Many APIs use OAuth 2.0 for authorization, and will require an OAuth provider to include the additional information about how to authorize against the service. If this option is selected, follow the steps in Configure OAuth 2.0 below.
     Configure OAuth 2.0

     Specify the details for your required OAuth 2.0 flow. For more detailed information see OAuth 2.0 Configuration.

     1. Token URL:
        Enter the URL of the third-party authentication server you are using. For example, https://oauth2.googleapis.com/token.
     2. Client ID:
        Enter the ID provided by your client application.
     3. Client Secret:
        Enter the secret provided by your client application.
     4. Authorization Scope:
        Enter your required access scopes for the third-party application server you are using. For example, if you are using the Web API plugin to access the https://www.googleapis.com/ API and you wish to use the drive/v3/files endpoint, you can use the authorization scope https://www.googleapis.com/auth/drive.readonly.
        If you require more than one scope, you add them all here separated by spaces.
        Offline access

        The Web API plugin requires offline access to be requested, which requires the correct scope to be entered, dependent on the authentication server being used:

        • Atlassian: Request the offline_access scope.
        • Google APIs: Offline access isn't requested via a scope at all. Instead, you must add the access_type = offline and include_granted_scopes = true query arguments to the Authorization URL.

     5. How to send credentials to the Token URL:
        Select where you want the client credentials you entered above to be included in the OAuth 2.0 request.
     6. Grant Type:
        Select the OAuth 2.0 flow you need to use. Choose from:
        • Authorization Code: Enter the Authorization URL of the authorization server you are using (for example, https://www.googleapis.com/) and then click the Sign In button below. You are redirected to the authorization sign in page.
          Upon returning to SquaredUp , if the request was successful, the Sign In button shows you as logged in.
        • Client Credentials: No additional details are required.
        • Password: You must enter a Username and Password.
     7. If you need to send the authorization token in the query URL, select Send authorization with query.
6. Headers can be added if required.

7. Ignore Certificate errors:

   If you activate this checkbox the data source will ignore certificate errors when accessing the server. This is useful if you have self-signed certificates.

8. Test endpoint:
   Optionally, you can tick Test endpoint to run a test request and see an example payload.
   Test endpoint

   Enter the details of an endpoint you'd like to run a test against to see what is returned. The information entered here is only used for the test.

   1. Endpoint path to test:
      Enter an endpoint path.
   2. Additional headers for the test:
      Enter any additional header names and values to be used for the test.
   3. HTTP method for the test:
      GET or POST
   4. Query arguments for the test GET:
      If you chose GET you can optionally add any query arguments to be used for the test.
   5. Body for test POST:
      If you chose POST you can optionally enter a JSON string representing the body of the POST request.
   6. Click Send.
   7. The Result box will show the resulting payload.

9. Restrict access to this data source:
   You can enable this option if you only want certain users or groups to have access to the data source, or the permission to link it to new workspaces. See data source access control for more information.

   Restrict access to this data source

   The term data source here really means data source instance. For example, a user may configure two instances of the AWS data source, one for their development environment and one for production. In that case, each data source instance has its own access control settings.

   By default, Restrict access to this data source is set to off. The data source can be viewed, edited and administered by anyone. If you would like to control who has access to this data source, switch Restrict access to this data source to on.

   Use the Restrict access to this data source dropdown to control who has access to the workspace:

   • By default, the user setting the permissions for the data source will be given Full Control and the Everyone group will be given Link to workspace permissions.
   • Tailor access to the data source, as required, by selecting individual users or user groups from the dropdown and giving them Link to workspace or Full Control permissions.
   • If the user is not available from the dropdown, you are able to invite them to the data source by typing in their email address and then clicking Add. The new user will then receive an email inviting them to create an account on SquaredUp. Once the account has been created, they will gain access to the organization.
   • At least one user or group must be given Full Control.
   • Admin users can edit the configuration, modify the Access Control List (ACL) and delete the data source, regardless of the ACL chosen.

   Access level	Permissions
   Link to workspace	User can link the data source to any workspace they have at least Editor permissions for. Data from the data source can then be viewed by anyone with any access to the workspace. User can share the data source data with anyone they want. User cannot configure the data source in any way, or delete it.
   Full Control	User can change the data source configuration, ACL, and delete the data source.

   See Access control for more information.

10. Click Add.
    

Next steps

Show data on a tile

1. On a dashboard click + and then Data to add a new data tile.
2. Data Stream tab:
   Click on HTTP Request.
   If HTTP Request isn't listed then perhaps the data source was added for the organization but not this workspace. Click the Data Source menu > Add new data source and look through the data sources listed.
   If you still can't see the data source perhaps it doesn't exist at the organization level, so click the link at the bottom of the page to add a new data source.
   Click on the Objects tab (or click Next).
3. Objects tab:
   Click on the name you gave your Data Source to tick it.
   Click on the Parameters tab (or click Next).
4. Parameters tab:
   You will see the Base URL which you configured in the Data Source setup. Depending on your API, you may see data at this point, or you may need to carry out some further configuration.
   Endpoint path:
   Optionally, enter an endpoint path.
   Supports timeframe mustache parameters

   A mustache parameter is a dynamic value, the actual value will be inserted to replace the field in curly braces. For example, {{timeframe.start}} will insert the start time based on the timeframe configured within the tile, or {{name}} will insert the name of the object(s) in scope.

   This data stream supports timeframe parameters:

   Parameter	Replacement value	Type
   {{timeframe.start}}	2022-03-13T19:45:00.000Z	string
   {{timeframe.unixStart}}	1647200700	number
   {{timeframe.end}}	2022-03-14T19:45:00.000Z	string
   {{timeframe.unixEnd}}	1647287100	number
   {{timeframe.enum}}	last24hours	string
   {{timeframe.interval}}	PT15M	string
   {{timeframe.durationSeconds}}	86400	number
   {{timeframe.durationMinutes}}	1440	number
   {{timeframe.durationHours}}	24	number

   
   Additional headers for this request:
   Optionally, enter any additional header names and values to be used. You can choose to encrypt a Header Value by clicking the encrypt icon
   . This turns the field into a password field, so that the value is hidden and the data is stored as encrypted.
   
   Supports timeframe mustache parameters (in values field)

   A mustache parameter is a dynamic value, the actual value will be inserted to replace the field in curly braces. For example, {{timeframe.start}} will insert the start time based on the timeframe configured within the tile, or {{name}} will insert the name of the object(s) in scope.

   This data stream supports timeframe parameters:

   Parameter	Replacement value	Type
   {{timeframe.start}}	2022-03-13T19:45:00.000Z	string
   {{timeframe.unixStart}}	1647200700	number
   {{timeframe.end}}	2022-03-14T19:45:00.000Z	string
   {{timeframe.unixEnd}}	1647287100	number
   {{timeframe.enum}}	last24hours	string
   {{timeframe.interval}}	PT15M	string
   {{timeframe.durationSeconds}}	86400	number
   {{timeframe.durationMinutes}}	1440	number
   {{timeframe.durationHours}}	24	number

   
   HTTP method:
   Select GET or POST
   Query arguments for GET:
   If you chose GET you can optionally add any query arguments to be used.
   
   

   

   Supports timeframe mustache parameters (in values field)

   A mustache parameter is a dynamic value, the actual value will be inserted to replace the field in curly braces. For example, {{timeframe.start}} will insert the start time based on the timeframe configured within the tile, or {{name}} will insert the name of the object(s) in scope.

   This data stream supports timeframe parameters:

   Parameter	Replacement value	Type
   {{timeframe.start}}	2022-03-13T19:45:00.000Z	string
   {{timeframe.unixStart}}	1647200700	number
   {{timeframe.end}}	2022-03-14T19:45:00.000Z	string
   {{timeframe.unixEnd}}	1647287100	number
   {{timeframe.enum}}	last24hours	string
   {{timeframe.interval}}	PT15M	string
   {{timeframe.durationSeconds}}	86400	number
   {{timeframe.durationMinutes}}	1440	number
   {{timeframe.durationHours}}	24	number

   Body for POST:
   If you chose POST you can optionally enter a JSON string representing the body of the POST request.
   Supports timeframe mustache parameters

   A mustache parameter is a dynamic value, the actual value will be inserted to replace the field in curly braces. For example, {{timeframe.start}} will insert the start time based on the timeframe configured within the tile, or {{name}} will insert the name of the object(s) in scope.

   This data stream supports timeframe parameters:

   Parameter	Replacement value	Type
   {{timeframe.start}}	2022-03-13T19:45:00.000Z	string
   {{timeframe.unixStart}}	1647200700	number
   {{timeframe.end}}	2022-03-14T19:45:00.000Z	string
   {{timeframe.unixEnd}}	1647287100	number
   {{timeframe.enum}}	last24hours	string
   {{timeframe.interval}}	PT15M	string
   {{timeframe.durationSeconds}}	86400	number
   {{timeframe.durationMinutes}}	1440	number
   {{timeframe.durationHours}}	24	number

5. Click Send. The Result box will show an example of the resulting payload (you may need to scroll down).
6. The Result box shows you a preview of the data returned.
   Path to data:
   This is where you enter the location of the results set that is returned. Check the Result box for the location of the data returned, and use that in the Path to data.
   

   

   Expand inner objects:
   Objects inside the requested data path will be used to make extra columns of data, for example if you have columns that show [object Object].
   
   What exactly does Expand inner objects do?

   Let's keep this example payload in mind:

   Copy

   const payload = {
       a1: 'a1',
       a2: 111,
       a3: true,
       arr: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
       obj: {
           b1: 'b1',
           b2: 222,
           b3: true,
           sub1Arr: [
               { x1: 'x1', x2: 6661, x3: { y1: 'y11', y2: 'y21' } },
               { x1: 'x2', x2: 6662, x3: { y1: 'y12', y2: 'y22' } }
           ],
           subObj: {
               c1: 'c1',
               c2: 333,
               c3: false
           }
       }
   };

   If Expand inner objects is unchecked (off)

   If Path to data points to an array, so values like arr, obj.sub1Arr, the data stream is going to return one row for each element (with no limit of 10 involved here).

   arr will return rows with a single column called value with all the integers from 1 to 12 (incl.)

   Copy

   value
      1
      2
   ...
     11
     12

   obj.sub1Arr will return two rows and three columns, like:

   Copy

   x1     x2           x3
   "x1"  6661    "[object Object]"
   "x2"  6662    "[object Object]"

   If Path to data points to a scalar, the data stream will return a single row with a single column called result and the value will be the scalar, for example, obj.b2 will return:

   Copy

   result
   222

   If Path to data points to an object, the data stream will return a single row with columns for each of the properties, for example, obj will return:

   Copy

   b1   b2   b3        sub1Arr           subObj
   "b1" 222 true   "[object Array]"  "[object Object]"

   If Expand inner objects is checked (on)

   Behavior differs wherever one of the [object XXX] placeholders appeared before.

   For example,

   obj.sub1Arr will return two rows and four columns, like:

   Copy

   x1     x2    x3.y1    x3.y2
   "x1"  6661    "y11"    "y21"
   "x2"  6662    "y12"    "y22"

   Also, nested arrays will be expanded (but only to a maximum of ten elements.

   
   Click Next or click on the Timeframe tab.
7. Timeframe tab:
   Optionally, you can specify a timeframe here, but you may have specified a set timeframe in the query or endpoint path, or used mustache parameters to use the dashboard timeframe.
8. At this point you might like to change the visualization, see Visualization Settings.
   The Shaping and Columns sections can help you configure the visualization as you need.
9. Shaping tab:
   Shaping allows you to perform filtering, grouping and sorting operations on the data you retrieve, although you may also do this using your query.
   
   Filtering

   Data can be filtered according to whether data in a column meets or does not meet specified text or numerical value conditions. Depending on the data you are filtering, available options include: Equals, Not equals, Contains, Doesn't contain, Less than, Greater than, Before now, After now, Is empty, Is not empty.

   Dates can be filtered by Before now or After now (e.g. to show overdue orders). Text matching is case sensitive.

   You are able to add multiple filter conditions. Available options are:

   • AND: All conditions must be satisfied (e.g. Status-Equals-Closed ANDType-Equals-Question).
   • OR: Any condition can be satisfied (e.g. Status-Equals-Pending ORStatus-Equals-Closed).
   Grouping

   You can group and aggregate data by column.

   For example, for AWS cost data you might configure the following settings to display a table or bar chart of cost per label:

   • Group by:label
   • Aggregation type: Total
   • Aggregation column: Amount

   Which columns are available depends on the data stream you chose.

   Configuring grouping enables different visualizations to be displayed, such as bar chart and donut. For example, grouping tickets by channel allows you to show a donut of how many tickets were logged by email vs web form.

   Bucket by

   If you group by a time column, and further grouping is possible, the Bucket by dropdown appears. Use this field to control how the time data is grouped, for example by hour, day, month etc.

   Aggregation type and column

   Use this dropdown to choose how to summarize your data, for example as a count, average or total.
   For example, you could do the following:

   • When creating a Bar Chart of ticket data you might configure the following settings to show a graph of tickets per day:
     • Group by:Date created
     • Bucketby:Day
     • Aggregation type: Count
   • When creating Bar Chart of Azure Resource Group cost you could configure the following settings:
     • Group by:Timestamp
     • Bucketby:Day
     • Aggregation type:Total
     • Aggregate column: Cost
   Sorting

   The Sort section allows you to select a column to be displayed in Ascending or Descending order. While this sets the default sort order, but you can always click on a column heading to sort data in a table on the fly.

   Enabling the Top toggle allows you to additionally specify the top n rows of data to display.

10. Columns tab:
    Column configuration

    Use the Columns tab of the tile editor to format the columns of the table on the Data tab.

    

    SquaredUp automatically defines the metadata retrieved from data streams so the data is assigned the correct data type, however in some circumstances you may want to override this.

    For example, when retrieving data using the Web API plugin, scripting, or custom query data streams (such as Splunk Enterprise plugin), the assigned data type may not be quite correct or as you expect.

    Formatting columns

    Use the following options to format your columns.

    Option	Description
    Name	To rename a column, click the current Name value and enter a new one. Columns that can be renamed display the Rename column icon when hovered over.
    Type	Select an option from the Type dropdown to change the data type of the column. If any additional options are available to configure, the dropdown is expanded below.
    Value	Displays the original value of the column.
    Formatted	Displays the formatted value of the column.
    Add a copy of this column	Click to duplicate a column. The copied field displays Copy of [field name] above its Name.
    Remove this column	Click to delete a cloned column.

    Additional options

    Some data types have advanced settings that can be configured in the options section, which is displayed whenever you change the data Type or by clicking expand

    next to the column Name.

    Option	Description
    Output Format	Enter a custom format to display date values as a string. Any specified output format is supported. For example, dd/mm/yy, dd/mm/yyyy or d/M/Y. By default, dates and times are displayed in your local timezone to ensure the data makes sense to you.
    Input Format	Enter the format that corresponds to the inputted date. For example, if your data has values such as 05/27/24 01:44 PM, then the Input Format should be set to dd/mm/yy hh:mm aa. Any input format is supported, however if you have a custom input format that is missing any time zone information, the input is always assumed to be UTC. This field is required if the data string for the column are not ISO-8601 formatted. For example, 2024-09-09T13:52:25.281Z.
    Currency	Select the currency to display the value in. This does not convert the currency value.
    Decimal Places	Formats the number of decimal places for a supported data type. Enter a value between 0 and 20.
    Link Text	Specify the text of the URL links in the column.
    Format as duration	Toggle between displaying the time value in minutes and seconds or seconds.
    Map Values to States	Define the values that trigger states. Select a value for each of the corresponding dropdowns: Success Warning Error Unknown

11. Optionally, configure Monitoring and KPIs.
12. When you have finished click Save.

Advanced users

{
	"name": "scope example",
	"matches": "all",
	"dataSourceConfig": {
		"endpointPath": "post",
		"httpMethod": "post",
		"idSeparator": "], [",
		"headers": [
			{
			"key": "header1",
			"value": "header1Val"
			},
			{
			"key": "sourceIds",
			"value": "[{{sourceIds}}]"
			}
		],
		"expandInnerObjects": true
	},
	"rowPath": []
}

//If you want to specify only one value of an object property//
"matches": {
	"ObjectProperty": {
		"type": "equals",
		"value": "ValueOfTheObjectProperty"
	}
},
 
//If you want to specify multiple values for an object property//
"matches": {
	"ObjectProperty": {
 		"type": "oneOf",
		"values": ["ValueOfTheObjectProperty1", "ValueOfTheObjectProperty2", "ValueOfTheObjectProperty3"]
	}
},

"matches": {
    "sourceName": {
      "type": "equals",
      "value": "AppDynamics"
    },
    "type": {
      "type": "equals",
      "value": "app"
    }
  },

"matches": [
    {
        "sourceName": {
            "type": "equals",
            "value": "AppDynamics"
        }
    },
    {
        "type": {
            "type": "equals",
            "value": "app"
        }
    }
]

{
    "generalInfo": "some info",
    "results": [
        {
            "name": "object 1",
            "tags": [
                "tag 1",
                "tag 2",
                "tag 3"
            ]
        },
        {
            "name": "object 2",
            "tags": [
                "tag 1",
                "tag 4"
            ]
        }
    ]
}

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