Apono Query Language
Learn the key concepts of the Apono Query Language
Last updated
Was this helpful?
Learn the key concepts of the Apono Query Language
Last updated
Was this helpful?
The Apono Query Language (AQL) provides a simple, intuitive syntax for filtering cloud resources, integrations, and permissions.
This reference documents query construction, available components, and common filtering examples.
When you are first starting to build queries, you can quickly learn how to build them by following these steps:
On the page, click Basic.
.
Click AQL. The AQL syntax will appear in the code box.
The following is a basic AQL query.
AQL uses a simple field-operator-value pattern.
Attribute or tag to query
Comparative logic
value
Expected value for the field
The field
component specifies the attribute of your cloud resources to query.
resource_type
Resource type
resource_type = "aws-rds-mysql"
resource_name
Resource name
resource_name contains "prod"
resource_path
Resource Path
resource_path contains "us-east-1"
resource
Resource identifier
resource = "res_12345"
resource_status
Current status
resource_status = "active"
resource_risk_level
Associated risk level
resource_risk_level = "high"
The operator
component defines how to evaluate the field
against the specified value
.
Basic operators that test for equality and inequality between values
=
Checks if values are the same
resource_type = "aws-account-dynamodb-table"
!=
Checks if values are different
integration != "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
The following AQL queries demonstrate how to efficiently locate, audit, and manage cloud resources and permissions. They cover common use cases such as identifying high-risk assets, tracking access levels, and enforcing security policies.
Use these queries as a foundation and customize them to fit your specific environment and compliance requirements.
Queries focused on locating and filtering cloud infrastructure resources
Queries that manage and audit access control settings
Advanced patterns that merge resource and permission conditions for precise access control
Follow these best practices to write AQL queries that are clear, efficient, and easy to modify. These guidelines improve readability, execution speed, and adaptability.
AQL processes conditions from left to right. Starting with a specific filter improves efficiency.
When checking multiple values, in (...)
is more concise and performs better than chaining multiple or
conditions.
Without parentheses, complex conditions can be misinterpreted and return unexpected results. Grouping conditions explicitly ensures the query evaluates as intended.