ICALEPCS2011 - List of Authors (Teixeira, D.D.)

Paper

Title

Page

LHC Supertable

86

M. Pereira, M. Lamont, G.J. Müller, D.D. Teixeira
CERN, Geneva, Switzerland
T.E. Lahey
SLAC, Menlo Park, California, USA
E.S.M. McCrory
Fermilab, Batavia, USA

LHC operations generate enormous amounts of data. These data are being stored in many different databases. Hence, it is difficult for operators, physicists, engineers and management to have a clear view on the overall accelerator performance. Until recently the logging database, through its desktop interface TIMBER, was the only way of retrieving information on a fill-by-fill basis. The LHC Supertable has been developed to provide a summary of key LHC performance parameters in a clear, consistent and comprehensive format. The columns in this table represent main parameters that describe the collider's operation such as luminosity, beam intensity, emittance, etc. The data is organized in a tabular fill-by-fill manner with different levels of detail. A particular emphasis was placed on data sharing by making data available in various open formats. Typically the contents are calculated for periods of time that map to the accelerator's states or beam modes such as Injection, Stable Beams, etc. Data retrieval and calculation is triggered automatically after the end of each fill. The LHC Supertable project currently publishes 80 columns of data on around 100 fills.

THCHAUST06

Instrumentation of the CERN Accelerator Logging Service: Ensuring Performance, Scalability, Maintenance and Diagnostics

1232

C. Roderick, R. Billen, D.D. Teixeira
CERN, Geneva, Switzerland

The CERN accelerator Logging Service currently holds more than 90 terabytes of data online, and processes approximately 450 gigabytes per day, via hundreds of data loading processes and data extraction requests. This service is mission-critical for day-to-day operations, especially with respect to the tracking of live data from the LHC beam and equipment. In order to effectively manage any service, the service provider's goals should include knowing how the underlying systems are being used, in terms of: "Who is doing what, from where, using which applications and methods, and how long each action takes". Armed with such information, it is then possible to: analyze and tune system performance over time; plan for scalability ahead of time; assess the impact of maintenance operations and infrastructure upgrades; diagnose past, on-going, or re-occurring problems. The Logging Service is based on Oracle DBMS and Application Servers, and Java technology, and is comprised of several layered and multi-tiered systems. These systems have all been heavily instrumented to capture data about system usage, using technologies such as JMX. The success of the Logging Service and its proven ability to cope with ever growing demands can be directly linked to the instrumentation in place. This paper describes the instrumentation that has been developed, and demonstrates how the instrumentation data is used to achieve the goals outlined above.

Slides THCHAUST06 [5.459 MB]

Paper	Title	Page
MOPKN002	LHC Supertable	86
	M. Pereira, M. Lamont, G.J. Müller, D.D. Teixeira CERN, Geneva, Switzerland T.E. Lahey SLAC, Menlo Park, California, USA E.S.M. McCrory Fermilab, Batavia, USA
	LHC operations generate enormous amounts of data. These data are being stored in many different databases. Hence, it is difficult for operators, physicists, engineers and management to have a clear view on the overall accelerator performance. Until recently the logging database, through its desktop interface TIMBER, was the only way of retrieving information on a fill-by-fill basis. The LHC Supertable has been developed to provide a summary of key LHC performance parameters in a clear, consistent and comprehensive format. The columns in this table represent main parameters that describe the collider's operation such as luminosity, beam intensity, emittance, etc. The data is organized in a tabular fill-by-fill manner with different levels of detail. A particular emphasis was placed on data sharing by making data available in various open formats. Typically the contents are calculated for periods of time that map to the accelerator's states or beam modes such as Injection, Stable Beams, etc. Data retrieval and calculation is triggered automatically after the end of each fill. The LHC Supertable project currently publishes 80 columns of data on around 100 fills.

THCHAUST06	Instrumentation of the CERN Accelerator Logging Service: Ensuring Performance, Scalability, Maintenance and Diagnostics	1232
	C. Roderick, R. Billen, D.D. Teixeira CERN, Geneva, Switzerland
	The CERN accelerator Logging Service currently holds more than 90 terabytes of data online, and processes approximately 450 gigabytes per day, via hundreds of data loading processes and data extraction requests. This service is mission-critical for day-to-day operations, especially with respect to the tracking of live data from the LHC beam and equipment. In order to effectively manage any service, the service provider's goals should include knowing how the underlying systems are being used, in terms of: "Who is doing what, from where, using which applications and methods, and how long each action takes". Armed with such information, it is then possible to: analyze and tune system performance over time; plan for scalability ahead of time; assess the impact of maintenance operations and infrastructure upgrades; diagnose past, on-going, or re-occurring problems. The Logging Service is based on Oracle DBMS and Application Servers, and Java technology, and is comprised of several layered and multi-tiered systems. These systems have all been heavily instrumented to capture data about system usage, using technologies such as JMX. The success of the Logging Service and its proven ability to cope with ever growing demands can be directly linked to the instrumentation in place. This paper describes the instrumentation that has been developed, and demonstrates how the instrumentation data is used to achieve the goals outlined above.
	Slides THCHAUST06 [5.459 MB]