ReSS: A Resource Selection Service for the Open Science Grid

The Open Science Grid offers access to hundreds of computing and storage resources via standard Grid interfaces. Before the deployment of an automated resource selection system, users had to submit jobs directly to these resources. They would manually select a resource and specify all relevant attributes in the job description prior to submitting the job. The necessity of a human intervention in resource selection and attribute specification hinders automated job management components from accessing OSG resources and it is inconvenient for the users. The Resource Selection Service (ReSS) project addresses these shortcomings. The system integrates condor technology, for the core match making service, with the gLite CEMon component, for gathering and publishing resource information in the Glue Schema format. Each one of these components communicates over secure protocols via web services interfaces. The system is currently used in production on OSG by the DZero Experiment, the Engagement Virtual Organization, and the Dark Energy. It is also the resource selection service for the Fermilab Campus Grid, FermiGrid. ReSS is considered a lightweight solution to push-based workload management. This paper describes the architecture, performance, and typical usage of the system

ReSS: Resource Selection Service for National and Campus Grid Infrastructure

The Open Science Grid (OSG) offers access to around hundred Compute elements (CE) and storage elements (SE) via standard Grid interfaces. The Resource Selection Service (ReSS) is a push-based workload management system that is integrated with the OSG information systems and resources. ReSS integrates standard Grid tools such as Condor, as a brokering service and the gLite CEMon, for gathering and publishing resource information in GLUE Schema format. ReSS is used in OSG by Virtual Organizations (VO) such as Dark Energy Survey (DES), DZero and Engagement VO. ReSS is also used as a Resource Selection Service for Campus Grids, such as FermiGrid. VOs use ReSS to automate the resource selection in their workload management system to run jobs over the grid. In the past year, the system has been enhanced to enable publication and selection of storage resources and of any special software or software libraries (like MPI libraries) installed at computing resources. In this paper, we discuss the Resource Selection Service, its typical usage on the two scales of a National Cyber Infrastructure Grid, such as OSG, and of a campus Grid, such as FermiGrid

SVOPME: A scalable virtual organization privileges management environment

Grids enable uniform access to resources by implementing standard interfaces to resource gateways. In the Open Science Grid (OSG), privileges are granted on the basis of the user's membership to a Virtual Organization (VO). However, Grid sites are solely responsible to determine and control access privileges to resources using users identity and personal attributes, which are available through Grid credentials. While this guarantees full control on access rights to the sites, it makes VO privileges heterogeneous throughout the Grid and hardly fits with the Grid paradigm of uniform access to resources. To address these challenges, we are developing the Scalable Virtual Organization Privileges Management Environment (SVOPME), which provides tools for VOs to define and publish desired privileges and assists sites to provide the appropriate access policies. Moreover, SVOPME provides tools for Grid sites to analyze site access policies for various resources, verify compliance with preferred VO policies, and generate directives for site administrators on how the local access policies can be amended to achieve such compliance without taking control of local configurations away from site administrators. This paper discusses what access policies are of interest to the OSG community and how SVOPME implements privilege management for OSG

Hadoop distributed file system for the Grid

Data distribution, storage and access are essential to CPU-intensive and data-intensive high performance Grid computing. A newly emerged file system, Hadoop distributed file system (HDFS), is deployed and tested within the Open Science Grid (OSG) middleware stack. Efforts have been taken to integrate HDFS with other Grid tools to build a complete service framework for the Storage Element (SE). Scalability tests show that sustained high inter-DataNode data transfer can be achieved for the cluster fully loaded with data-processing jobs. The WAN transfer to HDFS supported by BeStMan and tuned GridFTP servers shows large scalability and robustness of the system. The hadoop client can be deployed at interactive machines to support remote data access. The ability to automatically replicate precious data is especially important for computing sites, which is demonstrated at the Large Hadron Collider (LHC) computing centers. The simplicity of operations of HDFS-based SE significantly reduces the cost of ownership of Petabyte scale data storage over alternative solutions

Distributing User Code with the CernVM FileSystem

The CernVM FileSystem (CVMFS) is widely used in High Throughput Computing to efficiently distributed experiment code. However, the standard CVMFS publishing tools are designed for a small group of people from each experiment to maintain common software, and the tools are not a good fit for publishing software from numerous users in each experiment. As a result, most user code, such as code to do specific physics analyses, is still sent with every job to the place the job is run. That process is relatively inefficient, especially when the user code is large. To overcome these limitations, we have built a CVMFS user code publication system. This publication system enables users to still submit their code with their jobs but the code is distributed and accessed through the standard CVMFS infrastructure. The user code is automatically deleted from CVMFS after a period of no use. Most of the software for the system is available as a single self-contained open source rpm called cvmfs-user-pub and is available for other deployments

Distributing User Code with the CernVM FileSystem

The CernVM FileSystem (CVMFS) is widely used in High Throughput Computing to efficiently distributed experiment code. However, the standard CVMFS publishing tools are designed for a small group of people from each experiment to maintain common software, and the tools are not a good fit for publishing software from numerous users in each experiment. As a result, most user code, such as code to do specific physics analyses, is still sent with every job to the place the job is run. That process is relatively inefficient, especially when the user code is large. To overcome these limitations, we have built a CVMFS user code publication system. This publication system enables users to still submit their code with their jobs but the code is distributed and accessed through the standard CVMFS infrastructure. The user code is automatically deleted from CVMFS after a period of no use. Most of the software for the system is available as a single self-contained open source rpm called cvmfs-user-pub and is available for other deployments

Metrics Correlation and Analysis Service (MCAS)

Abstract. The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information pool is disorganized, it is a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation, and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by loosely coupled or fully decoupled middleware

Metrics correlation and analysis service (MCAS)

The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware

Snowmass Energy Frontier Simulations using the Open Science Grid : A Snowmass 2013 whitepaper

Snowmass is a US long-term planning study for the high-energy community by the American Physical Society’s Division of Particles and Fields. For its simulation studies, opportunistic resources are harnessed using the Open Science Grid infrastructure. Late binding grid technology, GlideinWMS, was used for distributed scheduling of the simulation jobs across many sites mainly in the US. The pilot infrastructure also uses the Parrot mechanism to dynamically access CvmFS in order to ascertain a homogeneous environment across the nodes. This report presents the resource usage and the storage model used for simulating large statistics Standard Model backgrounds needed for Snowmass Energy Frontier studies

FERRY: access control and quota management service

Fermilab developed the Frontier Experiments RegistRY (FERRY) service that provides a centralized repository for access control and job management attributes such as batch and storage access policies, quotas, batch priorities and NIS attributes for cluster configuration. This paper describes the FERRY architecture, deployment and integration with services that consume the stored information. The Grid community has developed several access control management services over the last decade. Over time, services for Fermilab experiments have required the collection and management of more access control and quota attributes. At the same time, various services used for this purpose, namely VOMS-Admin, GUMS and VULCAN, are being abandoned by the community. FERRY has multiple goals: maintaining a central repository for currently scattered information related to users' attributes, providing a Restful API that allows uniform data retrieval by services, and providing a replacement service for all the abandoned grid services. FERRY is integrated with the ServiceNow (SNOW) ticketing service and uses it as its user interface. In addition to the standard workflows for request approval and task creation, SNOW invokes orchestration that automates access to FERRY API. Our expectation is that FERRY will drastically improve user experience as well as decrease effort required by service administrators