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Network Management System: Gas Utility (SAP HANA)

This test study was conducted in August 2023 and evaluates the reference architecture for a Network Management System with:

  • Workflows representative of a gas utility
  • An enterprise geodatabase configured with SAP HANA
  • Amazon Web Services (AWS) cloud infrastructure.

The system presented in this test study was designed at a physical level, and incorporates several design choices that are described in detail. The system was deployed and tested for both performance and end-user experience, with a target design load of 15 ArcGIS Pro Editors and 200 ArcGIS Web Users (General User personas)

Note:

It is important that you become familiar with the reference architecture before the test study, as there is important information and resources that are not duplicated here.

Overview of capabilities

A foundational network management system delivers the following capabilities as defined in the conceptual architecture:

  • Service-based editing of relational data, including geometry and attributes.
  • Data collection workflows using forms and/or maps.
  • Complex utility network management using the ArcGIS Utility Network as an advanced data model.
  • Viewing and querying network assets through web applications.
  • Performing upstream & downstream trace analytics.

Software list

The system capabilities are delivered through the following software, deployed, and tested as part of this test study, at the listed versions with all available patches applied:

Note:

The software versions listed above were the latest available when this system test study was deployed and tested. Esri strongly recommends using the latest available software versions when possible.

The design was deployed on a Microsoft Windows operating system, apart from the database server, which was deployed on SUSE Linux.

Data characteristics

This test study tested a gas utility dataset with a geographic extent of roughly 55,000 square miles, and with an overall size of approximately 45 GB. The dataset contained roughly nine million features, 700 sub-networks, and 300,000 gas meters.

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