LLNL, Livermore, California, USA
The National Ignition Facility (NIF) is the world's largest and most energetic laser experimental facility with 192 beams capable of delivering 1.8 megajoules and 500-terawatts of ultraviolet light to a target. To aid in NIF control system troubleshooting, the commercial product Splunk was introduced to collate and view system log files collected from 2,600 processes running on 1,800 servers, front-end processors, and embedded controllers. We have since extended Splunk's access into current and historical control system configuration data, as well as experiment setup and results. Leveraging Splunk's built-in data visualization and analytical features, we have built custom tools to gain insight into the operation of the control system and to increase its reliability and integrity. Use cases include predictive analytics for alerting on pending failures, analyzing shot operations critical path to improve operational efficiency, performance monitoring, project management, and in analyzing and monitoring system availability. This talk will cover the various ways we've leveraged Splunk to improve and maintain NIF's integrated control system.
LLNL-ABS-728830
LLNL, Livermore, California, USA
The National Ignition Facility (NIF) is the world's largest and most energetic laser experimental facility with 192 beams capable of delivering 1.8 megajoules and 500-terawatts of ultraviolet light to a target. Officially commissioned as an operational facility on March 21, 2009, NIF is expected to conduct research experiments thru 2039. The 30-year lifespan of the control system presents several challenges in meeting reliability, availability, and maintainability (RAM) expectations. As NIF continues to expand on its experimental capabilities, the control system's software base of 3.5 million lines of code grows with most of the legacy software still in operational use. Supporting this software is further complicated by technology life cycles and turnover of senior experienced staff. This talk will present lessons learned and new initiatives related to technology refreshes, risk mitigation, and changes to our software development and test methodology to ensure high control system availability for supporting experiments throughout NIF's lifetime.
LLNL-ABS-727374
