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  • Tonic Structural User Guide
  • About Tonic Structural
    • Structural data generation workflow
    • Structural deployment types
    • Structural implementation roles
    • Structural license plans
  • Logging into Structural for the first time
  • Getting started with the Structural free trial
  • Managing your user account
  • Frequently Asked Questions
  • Tutorial videos
  • Creating and managing workspaces
    • Managing workspaces
      • Viewing your list of workspaces
      • Creating, editing, or deleting a workspace
      • Workspace configuration settings
        • Workspace identification and connection type
        • Data connection settings
        • Configuring secrets managers for database connections
        • Data generation settings
        • Enabling and configuring upsert
        • Writing output to Tonic Ephemeral
        • Writing output to a container repository
        • Advanced workspace overrides
      • About the workspace management view
      • About workspace inheritance
      • Assigning tags to a workspace
      • Exporting and importing the workspace configuration
    • Managing access to workspaces
      • Sharing workspace access
      • Transferring ownership of a workspace
    • Viewing workspace jobs and job details
  • Configuring data generation
    • Privacy Hub
    • Database View
      • Viewing and configuring tables
      • Viewing the column list
      • Displaying sample data for a column
      • Configuring an individual column
      • Configuring multiple columns
      • Identifying similar columns
      • Commenting on columns
    • Table View
    • Working with document-based data
      • Performing scans on collections
      • Using Collection View
    • Identifying sensitive data
      • Running the Structural sensitivity scan
      • Manually indicating whether a column is sensitive
      • Built-in sensitivity types that Structural detects
      • Creating and managing custom sensitivity rules
    • Table modes
    • Generator information
      • Generator summary
      • Generator reference
        • Address
        • Algebraic
        • Alphanumeric String Key
        • Array Character Scramble
        • Array JSON Mask
        • Array Regex Mask
        • ASCII Key
        • Business Name
        • Categorical
        • Character Scramble
        • Character Substitution
        • Company Name
        • Conditional
        • Constant
        • Continuous
        • Cross Table Sum
        • CSV Mask
        • Custom Categorical
        • Date Truncation
        • Email
        • Event Timestamps
        • File Name
        • Find and Replace
        • FNR
        • Geo
        • HIPAA Address
        • Hostname
        • HStore Mask
        • HTML Mask
        • Integer Key
        • International Address
        • IP Address
        • JSON Mask
        • MAC Address
        • Mongo ObjectId Key
        • Name
        • Noise Generator
        • Null
        • Numeric String Key
        • Passthrough
        • Phone
        • Random Boolean
        • Random Double
        • Random Hash
        • Random Integer
        • Random Timestamp
        • Random UUID
        • Regex Mask
        • Sequential Integer
        • Shipping Container
        • SIN
        • SSN
        • Struct Mask
        • Timestamp Shift Generator
        • Unique Email
        • URL
        • UUID Key
        • XML Mask
      • Generator characteristics
        • Enabling consistency
        • Linking generators
        • Differential privacy
        • Partitioning a column
        • Data-free generators
        • Supporting uniqueness constraints
        • Format-preserving encryption (FPE)
      • Generator types
        • Composite generators
        • Primary key generators
    • Generator assignment and configuration
      • Reviewing and applying recommended generators
      • Assigning and configuring generators
      • Document View for file connector JSON columns
      • Generator hints and tips
      • Managing generator presets
      • Configuring and using Structural data encryption
      • Custom value processors
    • Subsetting data
      • About subsetting
      • Using table filtering for data warehouses and Spark-based data connectors
      • Viewing the current subsetting configuration
      • Subsetting and foreign keys
      • Configuring subsetting
      • Viewing and managing configuration inheritance
      • Viewing the subset creation steps
      • Viewing previous subsetting data generation runs
      • Generating cohesive subset data from related databases
      • Other subsetting hints and tips
    • Viewing and adding foreign keys
    • Viewing and resolving schema changes
    • Tracking changes to workspaces, generator presets, and sensitivity rules
    • Using the Privacy Report to verify data protection
  • Running data generation
    • Running data generation jobs
      • Types of data generation
      • Data generation process
      • Running data generation manually
      • Scheduling data generation
      • Issues that prevent data generation
    • Managing data generation performance
    • Viewing and downloading container artifacts
    • Post-job scripts
    • Webhooks
  • Installing and Administering Structural
    • Structural architecture
    • Using Structural securely
    • Deploying a self-hosted Structural instance
      • Deployment checklist
      • System requirements
      • Deploying with Docker Compose
      • Deploying on Kubernetes with Helm
      • Enabling the option to write output data to a container repository
        • Setting up a Kubernetes cluster to use to write output data to a container repository
        • Required access to write destination data to a container repository
      • Entering and updating your license key
      • Setting up host integration
      • Working with the application database
      • Setting up a secret
      • Setting a custom certificate
    • Using Structural Cloud
      • Structural Cloud notes
      • Setting up and managing a Structural Cloud pay-as-you-go subscription
      • Structural Cloud onboarding
    • Managing user access to Structural
      • Structural organizations
      • Determining whether users can create accounts
      • Creating a new account in an existing organization
      • Single sign-on (SSO)
        • Structural user authentication with SSO
        • Enabling and configuring SSO on Structural Cloud
        • Synchronizing SSO groups with Structural
        • Viewing the list of SSO groups in Tonic Structural
        • AWS IAM Identity Center
        • Duo
        • GitHub
        • Google
        • Keycloak
        • Microsoft Entra ID (previously Azure Active Directory)
        • Okta
        • OpenID Connect (OIDC)
        • SAML
      • Managing Structural users
      • Managing permissions
        • About permission sets
        • Built-in permission sets
        • Available permissions
        • Viewing the lists of global and workspace permission sets
        • Configuring custom permission sets
        • Selecting default permission sets
        • Configuring access to global permission sets
        • Setting initial access to all global permissions
        • Granting Account Admin access for a Structural Cloud organization
    • Structural monitoring and logging
      • Monitoring Structural services
      • Performing health checks
      • Downloading the usage report
      • Tracking user access and permissions
      • Redacted and diagnostic (unredacted) logs
      • Data that Tonic.ai collects
      • Verifying and enabling telemetry sharing
    • Configuring environment settings
    • Updating Structural
  • Connecting to your data
    • About data connectors
    • Overview for database administrators
    • Data connector summary
    • Amazon DynamoDB
      • System requirements and limitations for DynamoDB
      • Structural differences and limitations with DynamoDB
      • Before you create a DynamoDB workspace
      • Configuring DynamoDB workspace data connections
    • Amazon EMR
      • Structural process overview for Amazon EMR
      • System requirements for Amazon EMR
      • Structural differences and limitations with Amazon EMR
      • Before you create an Amazon EMR workspace
        • Creating IAM roles for Structural and Amazon EMR
        • Creating Athena workgroups
        • Configuration for cross-account setups
      • Configuring Amazon EMR workspace data connections
    • Amazon Redshift
      • Structural process overview for Amazon Redshift
      • Structural differences and limitations with Amazon Redshift
      • Before you create an Amazon Redshift workspace
        • Required AWS instance profile permissions for Amazon Redshift
        • Setting up the AWS Lambda role for Amazon Redshift
        • AWS KMS permissions for Amazon SQS message encryption
        • Amazon Redshift-specific Structural environment settings
        • Source and destination database permissions for Amazon Redshift
      • Configuring Amazon Redshift workspace data connections
    • Databricks
      • Structural process overview for Databricks
      • System requirements for Databricks
      • Structural differences and limitations with Databricks
      • Before you create a Databricks workspace
        • Granting access to storage
        • Setting up your Databricks cluster
        • Configuring the destination database schema creation
      • Configuring Databricks workspace data connections
    • Db2 for LUW
      • System requirements for Db2 for LUW
      • Structural differences and limitations with Db2 for LUW
      • Before you create a Db2 for LUW workspace
      • Configuring Db2 for LUW workspace data connections
    • File connector
      • Overview of the file connector process
      • Supported file and content types
      • Structural differences and limitations with the file connector
      • Before you create a file connector workspace
      • Configuring the file connector storage type and output options
      • Managing file groups in a file connector workspace
      • Downloading generated file connector files
    • Google BigQuery
      • Structural differences and limitations with Google BigQuery
      • Before you create a Google BigQuery workspace
      • Configuring Google BigQuery workspace data connections
      • Resolving schema changes for de-identified views
    • MongoDB
      • System requirements for MongoDB
      • Structural differences and limitations with MongoDB
      • Configuring MongoDB workspace data connections
      • Other MongoDB hints and tips
    • MySQL
      • System requirements for MySQL
      • Before you create a MySQL workspace
      • Configuring MySQL workspace data connections
    • Oracle
      • Known limitations for Oracle schema objects
      • System requirements for Oracle
      • Structural differences and limitations with Oracle
      • Before you create an Oracle workspace
      • Configuring Oracle workspace data connections
    • PostgreSQL
      • System requirements for PostgreSQL
      • Before you create a PostgreSQL workspace
      • Configuring PostgreSQL workspace data connections
    • Salesforce
      • System requirements for Salesforce
      • Structural differences and limitations with Salesforce
      • Before you create a Salesforce workspace
      • Configuring Salesforce workspace data connections
    • Snowflake on AWS
      • Structural process overviews for Snowflake on AWS
      • Structural differences and limitations with Snowflake on AWS
      • Before you create a Snowflake on AWS workspace
        • Required AWS instance profile permissions for Snowflake on AWS
        • Other configuration for Lambda processing
        • Source and destination database permissions for Snowflake on AWS
        • Configuring whether Structural creates the Snowflake on AWS destination database schema
      • Configuring Snowflake on AWS workspace data connections
    • Snowflake on Azure
      • Structural process overview for Snowflake on Azure
      • Structural differences and limitations with Snowflake on Azure
      • Before you create a Snowflake on Azure workspace
      • Configuring Snowflake on Azure workspace data connections
    • Spark SDK
      • Structural process overview for the Spark SDK
      • Structural differences and limitations with the Spark SDK
      • Configuring Spark SDK workspace data connections
      • Using Spark to run de-identification of the data
    • SQL Server
      • System requirements for SQL Server
      • Before you create a SQL Server workspace
      • Configuring SQL Server workspace data connections
    • Yugabyte
      • System requirements for Yugabyte
      • Structural differences and limitations with Yugabyte
      • Before you create a Yugabyte workspace
      • Configuring Yugabyte workspace data connections
      • Troubleshooting Yugabyte data generation issues
  • Using the Structural API
    • About the Structural API
    • Getting an API token
    • Getting the workspace ID
    • Using the Structural API to perform tasks
      • Configure environment settings
      • Manage generator presets
        • Retrieving the list of generator presets
        • Structure of a generator preset
        • Creating a custom generator preset
        • Updating an existing generator preset
        • Deleting a generator preset
      • Manage custom sensitivity rules
      • Create a workspace
      • Connect to source and destination data
      • Manage file groups in a file connector workspace
      • Assign table modes and filters to source database tables
      • Set column sensitivity
      • Assign generators to columns
        • Getting the generator IDs and available metadata
        • Updating generator configurations
        • Structure of a generator assignment
        • Generator API reference
          • Address (AddressGenerator)
          • Algebraic (AlgebraicGenerator)
          • Alphanumeric String Key (AlphaNumericPkGenerator)
          • Array Character Scramble (ArrayTextMaskGenerator)
          • Array JSON Mask (ArrayJsonMaskGenerator)
          • Array Regex Mask (ArrayRegexMaskGenerator)
          • ASCII Key (AsciiPkGenerator)
          • Business Name (BusinessNameGenerator)
          • Categorical (CategoricalGenerator)
          • Character Scramble (TextMaskGenerator)
          • Character Substitution (StringMaskGenerator)
          • Company Name (CompanyNameGenerator)
          • Conditional (ConditionalGenerator)
          • Constant (ConstantGenerator)
          • Continuous (GaussianGenerator)
          • Cross Table Sum (CrossTableAggregateGenerator)
          • CSV Mask (CsvMaskGenerator)
          • Custom Categorical (CustomCategoricalGenerator)
          • Date Truncation (DateTruncationGenerator)
          • Email (EmailGenerator)
          • Event Timestamps (EventGenerator)
          • File Name (FileNameGenerator)
          • Find and Replace (FindAndReplaceGenerator)
          • FNR (FnrGenerator)
          • Geo (GeoGenerator)
          • HIPAA Address (HipaaAddressGenerator)
          • Hostname (HostnameGenerator)
          • HStore Mask (HStoreMaskGenerator)
          • HTML Mask (HtmlMaskGenerator)
          • Integer Key (IntegerPkGenerator)
          • International Address (InternationalAddressGenerator)
          • IP Address (IPAddressGenerator)
          • JSON Mask (JsonMaskGenerator)
          • MAC Address (MACAddressGenerator)
          • Mongo ObjectId Key (ObjectIdPkGenerator)
          • Name (NameGenerator)
          • Noise Generator (NoiseGenerator)
          • Null (NullGenerator)
          • Numeric String Key (NumericStringPkGenerator)
          • Passthrough (PassthroughGenerator)
          • Phone (USPhoneNumberGenerator)
          • Random Boolean (RandomBooleanGenerator)
          • Random Double (RandomDoubleGenerator)
          • Random Hash (RandomStringGenerator)
          • Random Integer (RandomIntegerGenerator)
          • Random Timestamp (RandomTimestampGenerator)
          • Random UUID (UUIDGenerator)
          • Regex Mask (RegexMaskGenerator)
          • Sequential Integer (UniqueIntegerGenerator)
          • Shipping Container (ShippingContainerGenerator)
          • SIN (SINGenerator)
          • SSN (SsnGenerator)
          • Struct Mask (StructMaskGenerator)
          • Timestamp Shift (TimestampShiftGenerator)
          • Unique Email (UniqueEmailGenerator)
          • URL (UrlGenerator)
          • UUID Key (UuidPkGenerator)
          • XML Mask (XmlMaskGenerator)
      • Configure subsetting
      • Check for and resolve schema changes
      • Run data generation jobs
      • Schedule data generation jobs
    • Example script: Starting a data generation job
    • Example script: Polling for a job status and creating a Docker package
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On this page
  • About configuring environment settings
  • Options for configuring an environment setting
  • Configuring an environment setting in the correct service
  • Restarting after a configuration change
  • Configuring environment settings from Structural Settings
  • Information in the Environment Settings list
  • Filtering and sorting the Environment Settings list
  • Adding a setting manually
  • Setting a new value
  • Restoring the default value
  • Configuring environment settings from a .yaml file
  • Updating in Kubernetes
  • Updating in Docker

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  1. Installing and Administering Structural

Configuring environment settings

Last updated 3 months ago

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Environment settings were previously referred to as environment variables.

Tonic Structural uses environment settings for many of its configuration options. For example, the ENABLE_LOG_COLLECTION environment setting determines whether you share logs with Tonic.ai.

Structural also uses environment settings to enable custom generators and pre-release features for customers.

About configuring environment settings

Options for configuring an environment setting

You can configure selected environment settings from the Environment Settings tab of Structural Settings. For these selected settings, you can also .

You configure other environment settings in a .yaml file.

  • For Kubernetes deployments, the file is values.yaml.

  • For Docker deployments, the file is docker-compose.yaml.

Configuring an environment setting in the correct service

Each environment setting is tied to a specific service. Most environment settings are used by either the Structural web server or the worker.

The .yaml files contain a section for each service. Within each section is a subsection for the environment settings for that service.

You add each environment setting to the environment settings for the appropriate service.

When you configure an environment setting from Structural Settings or using the Structural API, Structural automatically uses the new value. You do not need to specify a service.

Restarting after a configuration change

When you change an environment setting, the change does not take effect until the services are restarted.

When you configure an environment setting from Structural Settings or using the Structural API, Structural automatically uses the new value. You do not need to restart any services.

Configuring environment settings from Structural Settings

Required global permission: Manage environment settings

The Environment Settings tab on Structural Settings allows you to configure some of the more commonly used environment settings. Some settings are always displayed in the list. Others you can add to the list manually when you need to set them.

When you configure a setting value from Structural Settings, it overrides any configuration of that setting in the .yaml file.

Information in the Environment Settings list

For each setting, the Environment Settings list includes:

  • The name of the environment setting. The name is the setting identifier updated to use title case instead of all caps, and to replace underscores with spaces.

  • The identifier used in the .yaml file for that setting.

  • A description of the setting and how it is used.

  • The default value.

    • If you configured a value for the setting in the .yaml file, then this is that value.

    • If you did not configure a value in the .yaml file, then this is the Structural default value.

Filtering and sorting the Environment Settings list

To filter the list, in the filter field, begin to type the setting identifier or value. As you type, the list is filtered to only display matching settings.

You can use the Name column to sort the list. To sort the list, click the column heading. To reverse the sort order, click the column heading again.

Adding a setting manually

In addition to the settings that are always displayed, there are settings that you can add to the list manually if you need to configure them.

From the Environment Settings tab, to add a setting manually:

  1. Click Add New Setting.

  2. On the Add Environment Setting panel, in the Setting Name field, enter the name of the setting.

  1. After you specify the setting name, under Setting Value, Structural displays the appropriate field to provide the setting value. For example, for a boolean value, a toggle displays. For a text value, a field displays.

  2. After you provide the value, to save the setting to the list, click Save.

After you add the setting to the list, you can update the value in the same way as settings that are permanently in the list.

Setting a new value

To provide a new value for a setting:

  1. Click the edit icon for the setting.

  2. Provide the new value: For a numeric or text value, in the field, type the new value. For a boolean value, use the toggle. When the toggle is in the on position, the value is true.

  3. Click Save.

Restoring the default value

The value displayed in the Default Value column is either:

  • If a value is configured in the .yaml file, then it is that value.

  • If a value is not configured in the .yaml file, then it is the Structural default value.

To reset the setting to the value in Default Value:

  1. Click the edit icon for the setting.

  2. Click the restore icon that is next to the default value.

Configuring environment settings from a .yaml file

Updating in Kubernetes

For Kubernetes, in values.yaml, the service sections (web_server and worker) are under tonicai. Within those sections, the environment settings are under env.

tonicai:
  web_server:
    env: {
      "ENVIRONMENT_SETTING_NAME": "Setting value"
    }

You add the environment setting to the appropriate env section, based on the service that that variable is associated with. For example:

env: {
    "TONIC_SSO_AUTHORIZATION_SERVER_ID": "12345",
    "TONIC_SSO_PROVIDER": "google"
}

After you update the .yaml file, to restart the service and complete the update, run:

$ helm upgrade <name_of_release> -n <namespace_name> <path-to-helm-chart>

The above helm upgrade command is always safe to use when you provide specific version numbers. However, if you use the latest tag, it might result in Structural containers that have different versions.

Alternatively, you can:

  • Delete each deployment (kubectl delete pod …), or scale the deployment replicas to 0 and then back to 1. This ensures that all pods restart with the latest version.

  • Use helm to uninstall and re-install Structural.

Remember that if an environment setting is configured on Structural Settings or using the Structural API, then that configuration takes precedence over any configuration in the .yaml file.

Updating in Docker

For Docker, in docker-compose.yaml, the service sections (tonic_web_server and tonic_worker) are under services. Within those sections, the environment settings are under environment.

tonic_web_server:
  environment:
    ENVIRONMENT_SETTING_NAME: Setting value

If your Structural instance is deployed using Docker, then you can either:

  • Set the value directly in docker-compose.yaml.

  • Set the value in your .env file, and add a reference to the variable in docker-compose.yaml.

To set the value directly in docker-compose.yaml, add the setting and value to the appropriate environment section, based on the service that the setting is associated with. For example:

environment:
  TONIC_SSO_AUTHORIZATION_SERVER_ID: 12345
  TONIC_SSO_PROVIDER: google

If you set the value in .env, then to add the reference in docker-compose.yaml:

environment:
  TONIC_SSO_AUTHORIZATION_SERVER_ID: ${TONIC_SSO_AUTHORIZATION_SERVER_ID}
  TONIC_SSO_PROVIDER: ${TONIC_SSO_PROVIDER}

After you update the yaml file, to restart the service and complete the update:

$ docker-compose down
$ docker-compose pull && docker-compose up -d

Remember that if an environment setting is configured on Structural Settings or using the Structural API, then that configuration takes precedence over any configuration in the .yaml file.

If this occurs, you can run the to ensure that all of the containers are updated and synchronized on the latest Structural version.

use the Structural API to configure them
Structural update process
Environment Settings tab on Structural Settings
Add Environment Setting panel with a setting name specified
Restore icon to restore the default value for an environment setting