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Enhancing Real-Time Monitoring and Efficiency for Tier 0 and Tier 1 Data Transfers

This document discusses the critical need for real-time monitoring and analysis of throughput metrics across Tier 0 and Tier 1 sites involved in data management for experiments, specifically addressing issues such as MSS performance, low efficiency in reprocessing jobs, and communication challenges. It highlights the necessity of improving shared software areas, deployment strategies, and network infrastructure while ensuring better data access methods to enhance overall operational efficiency. Collaborative site visits and continuous testing are recommended for optimal results.

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Enhancing Real-Time Monitoring and Efficiency for Tier 0 and Tier 1 Data Transfers

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  1. Tier 0 + Tier 1s • All: • MSS metrics • Need instant real-time monitoring of throughput (and per day overview) and to view transfers per experiment (WAN in/out; LAN – WNs) • Tools for site and grid • NL-T1: • Communication & SIRs • Lack of tape drives (now installed) • DMF tuning needed? • Unexplained low performance • LAN b/w to WN too small • Shared SW area problems • Repeat tests • ASGC: • Castor version? • Job scheduling T2 v T1; ATLAS v CMS • Low efficiency for CMS reprocessing jobs • Repeat tests • FZK: • Improve communication to world • SAN issues • Shared SW area problems • SRM server overload • dcap access problems • Too many lcg-cp  overload gridftp • Repeat tests • NDGF: • No MSS performance monitoring • Low throughput • Analysis jobs overloaded network • No Panda pre-staging • What is action to improve? • CNAF: • Shared SW area problems • Site visits – planned for FZK + NL-T1

  2. Tier 2s • Shared SW areas affect CPU efficiencies in some sites (also T1) • ATLAS efficiencies different between WMS and PANDA • Likely due to different data access methods • Data transfer timeouts (what?  see analysis summary) • Intra-VO fairshares  how to manage? ( GDB?) • VO communications • Need for VO-independent channel to reach all T2 admins • Network infrastructure not good enough for data rates

  3. Data management • FTS • Timeouts for large files • Increase the number of concurrent jobs to increase bandwidth • Throttle/manage each VO bandwidth? • Deploy FTS 2.2 • LFC: • LHCb/Coral issues (Coral problem); Should LHCb use distributed LFCs (not essential if Coral problem fixed). • Deploy bulk methods (new additions) • Lcg-util – hangs at French sites (only?) • dcapaccess for LHCb (root issue?) • dCache: • Need a clear strategy for Chimera (and risk analysis) • Explain “golden” release v what we have (and risk analysis) • Site decisions, but must be based on understanding of risks • Data transfer timeouts • dcap/rfioproblems at high (analysis) load • 90% of (analysis) job failures are read failures • Are these the same issue? (what? SRM?) • Better data access strategies??? • Pre-stage vs copy locally vsPosix-io • General investigation of data access methods and problems

  4. Other services • WMS: • Stability/scalability (DNS load balancing, multi-core, ...) • WMS 3.2 to deploy? But critical bug (for at least LHCb) • LCG-CE: • Timeouts • Zombies • Globus-gma (>32k jobs) – workaround to clean up • MyProxy – single pof • Glexec/SCAS – need experience • CE: • Matching requirements to WN properties (blah integration with batch systems) • CREAM bugs to be fixed • BDII: • V5 more robust? Fix tools that cannot handle lists • APEL: • Tomcat problems • R-GMA problems (replace with MSG) • Shared sw areas (came up many times) • Problems at NL-T1, FZK, CNAF + Tier 2s • ALICE use of BitTorrent ? Is this a solution? • Monitoring: • ATLAS need more monitoring for analysis jobs (re-use CMS dashboard work?)

  5. Common themes ... • Data access strategies: • Investigations under way .. ATLAS, CMS, Massimo, Maarten, DM group • ... • Shared software areas: • ??? • dCache strategies and risks • Monitoring: • More real time on MSS transfers • MSS metrics • Improve dashboards – ATLAS vs CMS

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