Table of Contents

Skyline EPM Platform VSAT WM CMDB

About

The Skyline EPM Platform VSAT WM CMDB connector is a workflow manager that handles file-based provisioning for the CMDB (Customer Management Database) data management within the system. This connector reads device inventory data from JSON files, processes mapping configurations, and generates provisioning output files for connectors.

Key Features

  • Automated file provisioning: Automatically imports, transforms, and exports inventory data on a configurable interval, reducing manual data management overhead.

  • Flexible JSON mapping engine: Uses a JSON-based mapping configuration that allows field renaming, constant values, nested object creation, array transformation, and default value handling without code changes.

  • Multi-format configuration file support: Reads configuration (CC) files in both XML and CSV format, extracting device names to filter relevant inventory records.

  • Remote file access: Supports accessing files from network shares using configurable Windows credentials with impersonation.

  • Dual import sources: Processes both connector-specific and global inventory files, enabling hierarchical data provisioning across different system levels.

Use Cases

Synchronizing Inventory Data to Collectors

Challenge: Managing large networks requires synchronizing inventory data from a central CMDB to multiple distributed collectors, each handling a subset of devices.

Solution: The connector imports a global circuit inventory JSON file and multiple configuration files (one per collector). It filters inventory records based on device names present in each configuration file and generates collector-specific provisioning (CP) files.

Benefit: Automated, targeted provisioning ensures each collector receives only the relevant data, reducing network overhead and processing time while maintaining data consistency across the system.

Handling Differences in Data Structure for CMDB and Collectors

Challenge: The source CMDB exports data in a different structure than what the downstream collectors expect, requiring field transformations, renaming, and restructuring.

Solution: The JSON mapping file allows operators to define transformations declaratively: copying fields with from, setting constants with const, creating nested objects using dot notation, transforming arrays with itemFields, and providing fallback values with default.

Benefit: Data structure changes can be accommodated by updating the mapping file without modifying connector code, reducing deployment time and testing effort for schema changes.

Dealing with Different Network Topologies

Challenge: Inventory files are stored on remote network shares that require authentication, and different environments may use local or remote storage.

Solution: The connector provides configurable directory type settings (local/remote) for both import and export paths, along with username and password parameters for Windows credentials-based impersonation when accessing remote shares.

Benefit: Flexible deployment options allow the same connector to work in different network topologies, from standalone servers with local files to distributed environments with centralized file shares.

Technical Reference

Prerequisites

  • DataMiner 10.3.0.0 or higher is required.

  • Circuit Configuration (CC) files are needed in XML or CSV format containing device names under Remotes/Remote/Name (XML) or a Name column (CSV) to filter inventory records.

  • A mapping configuration file is required to define how source inventory fields are transformed into output fields. Refer to the Mapping JSON File section in the technical documentation for configuration details.

  • A global inventory JSON file is required containing a records array with device data for the entire system.

  • Network credentials are required when using remote directory types for import/export paths (domain\username format supported).

Note

For detailed technical information, refer to our technical documentation.

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