J11.2
Consolidating GOES analysis workstations using virtualization and Thin-Client technology

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Tuesday, 25 January 2011: 1:45 PM
Consolidating GOES analysis workstations using virtualization and Thin-Client technology
606 (Washington State Convention Center)
Subir Vasanth, Avaya Government Solutions, Lanham, MD; and A. Agarwal, R. Dahmani, S. Tehranian, and K. McKenzie

The Geostationary Operational Environmental Satellite (GOES) program is a critical NOAA satellite mission that provides complete and timely global weather monitoring including access to global environmental satellite data to help track major weather systems to protect the Nation's economy, security, environment, and quality of life.

The GOES Operations Ground Equipment (OGE) major components are the Sensor Processing System (SPS), Replacement Product Monitor (RPM), Orbit and Attitude Tracking System (OATS), OGE Data Acquisition and Patching Subsystem (ODAPS), SPS Database Servers, and Consolidated Analysis Workstations (CAWS). These components are based on standalone hardware systems that use legacy and outdated hardware platforms and operating systems, some of which have reached end of Life (EOL) and have been discontinued. With these constraints, a hardware and software migration is a necessity in order to keep the current GOES I-M and GOES NOP series of satellites in operation until their retirement when the new GOES-R series of satellites are deployed and put into operations.

The Office of Systems Development (OSD) Ground Systems Division (GSD) and Avaya Gov have conducted a comprehensive assessment of the existing GOES ground system components, implementing a migration strategy for the GOES ground system components in an effort to extend the longevity of the system, increase its operational reliability, combine functional components into a single architecture, and reduce long-term Operations and Maintenance (O&M) costs. A plan was devised to proceed with a hardware and software migration to a next-generation state-of-the-art architecture for the entire GOES OGE and Spacecraft Ground Support Segment (SSGS) components. Avaya Gov developed and implemented the GOES Enterprise Managed System (GEMS) architecture that facilitates continuity of operations for GOES OGE in addition to providing other key mission-support capabilities. GEMS architecture was developed based on emerging hardware and software technologies providing unified enterprise management capabilities and economies of scale. It reduces ground system life-cycle costs, improves future standardization between component systems, standardizes O&M of OGE components, provides reliable operation with hot backup and fault-tolerant component systems, and enhances IT security.

The latest OGE component that is migrated to GEMS is the Consolidated Analysis Workstation (CAWS). Currently, CAWS is installed on a single platform and hosts several OGE applications, including (1) RPM client used for real-time and archive data, landmarks, and image navigation and registration analysis (2) Star Sense Data Archive (SSDA) client used for long-term archiving and analysis of imager and sounder star sense data, (3) SPS Modernized History Browser (MHBR) client used for display and analysis of historical data archived on the SPS, and (4) Dynamic Interactive Diagnostic (DID) software used for plotting and analysis of telemetry data received from the Multi-use Data Link (MDL) Receive System & Server (MRS&S) within the SSGS environment.

CAWS is migrated to a GEMS virtualized environment based on Opteron blade servers and thin-client technology. Virtualization allows several workstations to be installed as virtualized machines (VMs) on a single server. This allows the consolidation of multiple workstations on a single blade server at each NOAA site, where each workstation is operating independently within a separate VM. Individual CAWS VMs can be accessed through thin clients. This paper describes the migration of the CAWS workstations at WCDAS, NSOF, FCDAS, and WBU to a GEMS virtualized environment with access through thin clients.