ODBC on-prem plugin

For more information about what this plugin does and the data streams it retrieves, see:

Connects to any on-prem ODBC data resource.

An on-prem data source connects a service running in your internal network to SquaredUp. They require an agent installed on a machine that has access to your internal network.

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.

The ODBC data source requires that you have already installed the ODBC driver you wish to use on the same machine as the SquaredUp agent.

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 the data source

Display Name:
Enter a name for your data source. This helps you to identify this data source in the list of your data sources.
Agent Group:
Select the Agent Group that contains the agent(s) you want to use.
Connection String:
Each ODBC Data Source will require a different Connection String, with the format varying based on the ODBC driver type. See ODBC Connection String: Connecting to Your Database
Object Query (optional):
The ODBC Connection can create objects in the Knowledge Graph index and these can be used to create context sensitive objects and drill-downs.
These plugins support the creation of objects from a database query. The resulting table must contain sourceId, name, and type fields. Additional fields are allowed, and any non-null fields will be included with the object when imported into the Knowledge Graph.
A sample query result is below:
sourceId
name
type
initials
operating_system
abeLincoln
Abraham Lincoln
user
AL
server_1
Infra-SQL01.local
server
windows
In the above sample table two objects will be created in the Knowledge Graph. The first will be of type user and have a sourceId of abeLincoln and a single property for initials. The operating_system attribute will not be added to this object as it has a null property. The second object created will be a server with sourceId server_1 and a single property of operating_system.
Relationship Query (optional):
If you are creating objects with the Object Query set in the previous step, you can relate those objects in the Knowledge Graph.
Along with an Object Query an additional Relationship Query can also be used. The result of this query must contain the fields inV, outV, and label. The rows of this result will be converted to relationships in the Knowledge Graph.
A sample query result is below:
outV
label
inV
abeLincoln
own
server_1
After the import is complete the two objects created from the Object Query will now be linked, with Abraham Lincoln owning Infra-SQL01.local

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.

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.

Click Add.
You can also add a data source from Settings > Data Sources > Add data source, but sample dashboards are not added when using this method.

Importing Microsoft Excel document data

The ODBC plugin's flexibility allows you to import Microsoft Excel document data via the ODBC data source. To do so, you must simply create a document containing the mandatory sourceId, name and type columns, then pass a Connection String and Object Query for the Excel document when you Add an ODBC data source in SquaredUp. The following information details this process.

Prerequisites

When connecting to Excel, ensure that:

The proper drivers are installed (see Microsoft Access Database Engine 2016 Redistributable).
The bit architecture of the application and driver is correct (i.e. use 64-bit Excel with the 64-bit driver).
That the Relay agent is set up with a security principle that has access to the file (i.e. notNetwork Service, otherwise the Error: Cannot find module error occurs).

How to import excel document data via the ODBC plugin

Create the Excel (64-bit) spreadsheet you'll be extracting data from and add the sourceId, name, type columns.
The sourceId, name, and type columns must exist in your Excel spreadsheet, otherwise the data source will not function.
You must also ensure that column headers do not contain spaces.
1. Make a note of the Excel file name. In the following example, the worksheet name is Usage_v2.
2. Make a note of the file location of the Excel document you created. In the following example, the file is called ServerUsage1.xlsx.
On the machine hosting the Relay agent and the Excel data source, open ODBC Data Source Administrator (64-bit).
1. Make a note of the Microsoft Excel driver full name on the Drivers tab. For example, Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb).
Combine the values you previously noted to create the data source connection string.

The Connection String is created as:
Driver={driver name};DBQ=File location;For example:
Driver={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=C:\SqupAgent\ExcelFile\ServerUsage1.xlsx;The Object Query is crafted as:
Select Excel column names from Excel document nameFor example:
Select sourceId, name, type, ip, ServerName from [Usage_v2$]
It is recommended that you wrap the Excel document name in square brackets, just in case there are any unsupported characters, such as spaces.
Additionally, the query is not case sensitive. However, if it contains any spelling or formatting errors you will not receive any results.
Follow the steps in Add an ODBC data source in SquaredUp, entering the Connection String and Object Query you previously created for the Excel document in the corresponding setup fields.

Next steps

Add a dashboard and go into the configuration of a tile.
Filter to the ODBC data source.
Create a data stream by clicking on one of the customizable data streams.

Data streams standardize data from all the different shapes and formats your tools use into a straightforward tabular format.

While creating a tile you can tweak data streams by grouping or aggregating specific columns.

Depending on the kind of data, SquaredUp will automatically suggest how to visualize the result, for example as a table or line graph.

Data streams can be either global or scoped:

Global data streams are unscoped and return information of a general nature (e.g. "Get the current number of unused hosts").
A scoped data stream gets information relevant to the specific set objects supplied in the tile scope (e.g. "Get the current session count for these hosts").

Data streams

The following data streams are installed with this plugin.

Data streams standardize data from all the different shapes and formats your tools use into a straightforward tabular format.

While creating a tile you can tweak data streams by grouping or aggregating specific columns.

Depending on the kind of data, SquaredUp will automatically suggest how to visualize the result, for example as a table or line graph.

Data streams can be either global or scoped:

Global data streams are unscoped and return information of a general nature (e.g. "Get the current number of unused hosts").
A scoped data stream gets information relevant to the specific set objects supplied in the tile scope (e.g. "Get the current session count for these hosts").

See Data Streams for more information.

When using the data source to create data streams you have the option to create three different query types, as detailed below. The use of dynamic {{mustache}} properties is supported and is detailed following the types.

This allows for any tabular data to be pulled into to SquaredUp and be displayed in a standard table.

This configurable data stream type allows for data to be displayed in a visual format, such as a line graph. When writing a query for use as a Metrics query, the below three columns are mandatory and all others will be ignored.

Column Name (case sensitive)	Content
label	The label for the value passed in, for example ‘Percent Utilization’. Each distinct ‘label’ value will get its own line color which includes only values for that label.
timestamp	A DateTime value of when this reading occurred
value	A numerical non-null value to be visualized

This configurable data stream allows for data to be displayed as a state tile (Red, Yellow, or Green blocks). When writing a query for use in a State query the below three columns are mandatory and all others will be ignored.

Column Name (case sensitive)	Content
label	The label for the state passed in, for example ‘Deliveries’. These ‘label’ values must be distinct and will each produce their own status block
id	If this state will be tied to an object, then that object’s sourceId should be used, otherwise passing the ‘label’ value a second time will work effectively.
state	The state of the labeled object, options are ‘Success’, ‘Warning’, ‘Error’, and ‘Unknown’

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.

Check the relevant data source documentation to see which fields accept mustache parameters. See Data Sources

Only scoped data streams are able to insert properties from objects in scope, such as sourceIds, sourceId and targetNodes. They will also be able to use other properties such as timeframe.
Global data streams are able to use other properties, such as timeframe.

timeframe

All of the properties in the calling event payload are passed through to the template builder with the addition of below three properties.

durationSeconds
durationMinutes
durationHours

For example:

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

Select CustomerName, Order from dbo.Orders where orderDT > DateADD(mi, -{{timeframe.durationMinutes}},GetDate())

sourceIds

This is a unique property as some pre-processing occurs within the data source to modify the values. sourceIds will return a list of all the targeted nodes sourceId elements, concatenated with commas and string delimiters for TSQL friendly systems.

For example:

Parameter	Replacement value	Type
{{sourceIds}}	'idOne','idTwo','idThree'	string

Select CustomerName, Order from dbo.Orders where customerId IN ({{sourceIds}})

sourceId

This will return the sourceId of the first target node in the query. While not as powerful as the sourceIds value, it works for systems that don't support TSQL syntax and will still allow drill-down behavior. For Example:

Parameter	Replacement value	Type
{{sourceId}}	idOne	string

Select CustomerName, Order from dbo.Orders where customerId = '{{sourceId}}'

targetNodes:

This property represents the targetNodes on the calling event with the small addition of a first and last property on the respective nodes. This allows for Mustache templates to do a couple tricks, for example:

Parameter	Replacement value	Type
{{targetNodes.0.sourceId}}	idOne	string
{{#targetNodes}}'{{sourceId}}'{{^last}},{{/last}}{{/targetNodes}}	'idOne','idTwo','idThree'	string

Select CustomerName, Order from dbo.Orders where customerId = '{{targetNodes.0.sourceId}}'

Select CustomerName, Order from dbo.Orders where customerId IN ({{#targetNodes}}'{{sourceId}}'{{^last}},{{/last}}{{/targetNodes}})

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sourceId	name	type	initials	operating_system
abeLincoln	Abraham Lincoln	user	AL
server_1	Infra-SQL01.local	server		windows