TDM Installation and Initial Configuration

This document outlines installation guidelines and initial configuration procedures required for a new TDM installation. The upgrade to TDM V9.4 is described in the TDM upgrade document.

Table of Contents

• TDM Development Environment Installation

  • TDM On-Prem Installation — Desktop Studio
  • TDM On-Prem Installation — Web Studio
  • TDM K2view Cloud Installation

• TDM Non-Development Environment Installation

  • On-Prem VM Installation
  • K2view Cloud Installation

• TDM Initial Setup

• Optional — TDM AI Installation

TDM Development Environment Installation

TDM On-Prem Installation — Desktop Studio

Prerequisites

• Download and install Fabric V8.3.X Studio.
• Create a project in the Fabric Studio for TDM. It is recommended to maintain this project in a pre-configured GitHub repository.
• Create a PostgreSQL DB — a PostgreSQL DB is required for Fabric System (operational) DB and TDM operational DB (TDM V9.4 was certified based on PG V17). Note that you can download a PG image from the K2view download page. For more details, read here.

TDM Library Installation

• Download the TDM Library export files from the links provided by your K2view representative.

• Download Links for K2view Representatives

• Once downloaded, import the TDM Library export file using the Import All option: Right-click on the root of the Project Tree, click on Import, and select Import All, then in the File Browser, choose the export file to be imported. The following LUs would then be imported into your project: TDM, TDM_LIBRARY, and the TDM_TableLevel.

Click here for more information about the TDM Library.

Click here for more information about Import options.

TDM Deployment

• If you use Cassandra as Fabric’s system DB, you must edit the SEQ_CACHE_INTERFACE Global and update its value to DB_CASSANDRA.

• Perform the following step in order to use the PostgreSQL DB as the Fabric system DB:

  • Open Fabric’s config.ini file and edit the [system_db] section’s attributes, including the SYSTEM_DB_DATABASE attribute, to be aligned with the POSTGRESQL_ADMIN DB interface.

• Set the POSTGRESQL_ADMIN interface to active.

• Edit the TDM and POSTGRESQL_ADMIN interfaces with the installed PostgreSQL connection details.

• Set the CREATE_TDMDB Global in the TDM LU to true.

• Optional: Edit the TDMDB_SCHEMA shared Global if you wish to change the schema name for the TDM DB (the default schema name contains the cluster ID). Restart Fabric after updating this Global.

• Deploy the TDM LU. This deployment creates the TDM DB and the k2masking schema. Note that the k2masking schema can also be created by running the masking-create-cache-table.flow from the Broadway Examples (found in the Broadway Flow window, Main Menu > Actions > Examples and select this flow).

• After the TDM DB is created, set the CREATE_TDMDB Global in the TDM LU back to false.

TDM On-Prem Installation — Web Studio

Prerequisites

• Install Docker Compose container to host the Web Studio.

  Install Fabric V8.3.X Web Studio. Use the studio_pg profile, which is a Web Studio with PostgreSQL for use with its System DB and TDM.

TDM Library Installation

If internet access is available:

• Open the Fabric Web Studio.
• Click the Extensions icon.
• Select TDM to install the TDM library.

If internet access is unavailable:

• Download the VSIX file from the download page.
• Upload the file to the TDM project:
  • Right-click on project-resources from the Project Tree.
  • Select Upload Files… and choose the downloaded TDM VSIX file.
• Click the Extensions icon.
• Click the three-horizontal-dots menu (top-right of the pane).
• Select Install from VSIX….
• In the pop-up window, select the uploaded TDM VSIX file.
• Click Install from VSIX.

TDM Deployment

• Set the POSTGRESQL_ADMIN interface to active.
• Edit the TDM and POSTGRESQL_ADMIN interfaces with the installed PostgreSQL connection details.
• Perform the following step in order to use the PostgreSQL DB as the Fabric system DB:
  • Open Fabric’s config.ini file and edit the [system_db] section’s attributes, including the SYSTEM_DB_DATABASE attribute, to be aligned with the POSTGRESQL_ADMIN DB interface.
• Set the CREATE_TDMDB Global in the TDM LU to true.
• Optional: Edit the TDMDB_SCHEMA shared Global if you wish to change the schema name for the TDM DB (the default schema name contains the cluster ID). Restart Fabric after updating this Global.
• Deploy the TDM LU. This deployment creates the TDM DB and the k2masking schema. Note that the k2masking schema can also be created by running the masking-create-cache-table.flow from the Broadway examples.
• After the TDM DB is created, set the CREATE_TDMDB Global in the TDM LU back to false.

K2view Cloud Development Environment Installation

• Create a new Space on K2cloud. Select the TDM Dev Project and TDM-9.4 Profile.
• Set the CREATE_TDMDB Global in the TDM LU to true.
• Optional: Edit the TDMDB_SCHEMA shared Global if you wish to change the schema name for the TDM DB (the default schema name contains the cluster ID). Restart Fabric after updating this Global.
• Deploy the TDM LU. This deployment creates the TDM DB and the k2masking schema. Note that the k2masking schema can also be created by running the masking-create-cache-table.flow from the Broadway examples.
• After the TDM DB is created, set the CREATE_TDMDB Global in the TDM LU back to false.

TDM Non-Development Environment Installation

On-Prem VM Installation

Prerequisites

• Install VMs (virtual machines) for the Fabric server and the PostgreSQL DB. The PostgreSQL DB is required for Fabric System (operational) DB and TDM operational DB.

• Install Fabric V8.3.X and PostgreSQL DB (TDM V9.4 was certified based on PG V17).

• Note that Kafka installation is not required for a TDM project.

• For more information, see the following articles:

  Fabric 8 Setup Guide

  Kubernetes System Requirements

  Linux / Docker Requirements

  PostgreSQL Setup

Git Clone

• It is recommended to use separate Git branches for development, testing (SIT), and production environments. Changes from the development branch are merged into the testing branch, and tested changes from the testing branch are merged into the production branch.
• Edit the following Globals in the relevant branch before cloning in order to create the TDM DB and k2masking schema during the first TDM LU deployment:
  • The CREATE_TDMDB Global in the TDM LU must be set to true.
  • Optional: Edit the TDMDB_SCHEMA shared Global if you wish to change the schema name for the TDM DB (the default schema name contains the cluster ID).
• Clone the relevant GitHub branch.

Build and Deploy the Environments to Fabric

• Build and deploy the Environments to Fabric. The Environments must be deployed before deploying the TDM project to Fabric. Use the deploy-environment.sh script to deploy the Environments file.
• Note that the POSTGRESQL_ADMIN interface must be active.

Build and Deploy the TDM Project to Fabric

• Deploy the TDM LU. This deployment creates the TDM DB and the k2masking schema. After the TDM DB is created, set the CREATE_TDMDB Global in the TDM LU back to false.

• Build and deploy the remaining TDM project components to Fabric.

• Click here for more information about offline deployment.

K2view Cloud Installation

• Create a Project with Fabric V8.3.X and PostgreSQL DB.
• Attach the relevant GitHub branch to this project.
• Edit the following Globals in the relevant branch before cloning in order to create the TDM DB and k2masking schema during the first TDM LU deployment:
  • The CREATE_TDMDB Global in the TDM LU must be set to true
  • Optional: Edit the TDMDB_SCHEMA shared Global if you wish to change the schema name for the TDM DB (the default schema name contains the cluster ID).
• Create a Space based on this Project. Deploy the project to Fabric.

TDM Initial Setup

The following activities must be performed after deploying the TDM project to Fabric:

• Define Fabric roles — one for each user group as defined in the external IDP, and grant permissions to each role.

• TDM DB — General Parameters setup.

• TDM self-service application setup:

  • Permission group mapping — map the Fabric roles related to the corresponding TDM users to the TDM permission group (admin/owner/user).

  • Creating Business Entities. Note that all LUs must be deployed to Fabric before creating Business Entities (BEs).

  • Creating Systems.

  • Environment creation and setup — create all environments in the TDM self-service application.

    • Optional: Add permission sets to the environments to assign testers to these environments and define their TDM permissions.
    • Note that the environments must be deployed to Fabric before creating the environments in the TDM self-service application.

Optional — TDM AI Installation

TDM equips your QA and development teams with cutting-edge AI-driven synthetic data generation, transforming test data creation from manual rule-based scripts into intelligent automation:

• SDG (Synthetic Data Generation) based on AI: TDM seamlessly integrates with AI models to train on the existing data schema and generate realistic, production-grade synthetic entities — all within the platform.
• AI Workflows with One Click: Select a Business Entity, choose your training model, specify the data volume, and launch a 'generate new data' task. The system handles model selection, data ingestion into Fabric, and optionally loads the data directly into test environments.
• Robust Implementation Controls: Easily configure AI endpoints using global settings — such as AI_DB_INTERFACE, AI_ENVIRONMENT and AI_EXECUTION — allowing teams to customize connectivity, environments, and cleanup protocols.
• Hybrid, Business-Ready Approach: Choose between rule-based or AI-based generation for each scenario, which is an ideal approach for use cases ranging from edge-case testing to large-scale synthetic data population.
• Seamless Integration & Compliance: Generated entities include built-in support for sequence IDs, LUI mapping, and referential integrity. All data is cataloged in Fabric and masked as required.

The TDM AI installation guide outlines the essential infrastructure and application setup steps needed to integrate K2view's TDM with AI-powered capabilities. It covers everything from provisioning GPU-enabled environments to project configuration, cleanup processes, and performance testing.