Monitoring and Fault Tolerance Helge Meinhard / CERN-IT OpenLab workshop 08 July 2003

Monitoring and Fault Tolerance: Context Node Configuration System Monitoring Installation Fault Mgmt

History (1) In the 1990s, “massive” deployments of Unix boxes required automated monitoring of system state Answer: SURE Pure exception/alarm system No archiving of values, hence not useful for performance monitoring Not scalable to O(1000) nodes

History (2) PEM project at CERN (1999/2000) took fresh look at fabric mgmt, in particular monitoring PEM tool survey: Commercial tools found not flexible enough and too expensive; free solutions not appropriate Architecture, design and implementation from scratch

History (3) 2001 - 2003: European DataGrid project with work package on Fabric Management Subtasks: configuration, installation, monitoring, fault tolerance, resource management, gridification Profited from PEM work, developed ideas further

History (4) In 2001, some doubts about ‘do-it-all-ourselves’ approach of EDG WP4 Parallel to EDG WP4, project launched to investigate whether commercial SCADA system could be used Architecture deliberately kept similar to WP4

Monitoring and FT architecture (1) Monitoring: Captures non-intrusively actual state of a system (supposed not to change its state) Fault Tolerance: Reads and correlates data from monitoring system, triggers corrective actions (state-changing)

Monitoring and FT architecture (2) Sensor Monitoring Sensor Agent (MSA) MR – Monitoring Repository WP4: MR code with lower layer as flat file archive, or using Oracle CCS: PVSS system Sensor Sensor Local consumers Local consumers Local cache A P I Local consumers A P I DB

Monitoring and FT architecture (3) MSA controls communication with Monitoring Repository, configures sensors, requests samples, listens to sensors Sensors send metrics on request or spontaneously to MSA Communication MSA – MR: UDP or TCP based

Monitoring and FT architecture (4) FT system subscribing to metrics from monitoring subsystem Rule-based correlation engine takes decisions on firing actuators Actuators controlled by Actuator Agent, all actions logged by monitoring system

Deployment (1) End 2001: Put early versions of MSA and sensors on big clusters (~800 Linux machines), sending data (~100 metrics per machine, 1/min…1/day) to a PVSS-based repository At the same time, ~300 machines started sending performance metrics into flat file WP4 repository

Deployment (2) Sensors more refined over time (metrics added according to operational needs) Both exception and performance oriented sensors now deployed in parallel (some 150 metrics per node) More special machines added, currently ~1500 machines being monitored Test in May 2003: some 500 metric changes per second into the repository (~150 changes/s after “smoothing”)

Deployment (3) Repository requirements: Repository API implementation Oracle based fully functional alarm display for operators Currently using both an Oracle-MR based repository, and a PVSS based one Operators using PVSS based alarm screen as alternative to Sure display

Deployment (4) Interfaces: C API available, simple command line interface by end July, prototype Web access to time series of a metric available Fault tolerance: Just starting to look at WP4 prototype Configuration of monitoring: ad-hoc, to be migrated to CDB

Outlook Near term: Production services for LCG-1 Add more machines (e.g. network), metrics Software and service monitoring Medium term (end 2003): Monitoring for Solaris and Windows, … 2004 or 2005: Review of chosen solution for monitoring and FT Some of 1999 arguments no longer valid Will look at commercial and freeware solutions

Machine control High level: interplay of State Management System, Configuration Management, Monitoring, Fault Tolerance, … Low level: Past: CPU boxes didn’t have anything (5 rolling tables with monitors and keyboards per 500…1000 machines), disk and tape servers with analog KVM switches Future: Have investigated various options, benefit/cost analysis. Will go to serial consoles on all machines, 1 head node per 50…100 machines with serial multiplexers