1. DDM Monitoring David Cameron Pedro Salgado Ricardo Rocha

2. How it works DDM Monitoring (today) Dashboard Monitoring (near future)

3. How It Works

5. http://atlas-ddm-monitoring.web.cern.ch/atlas-ddm- monitoring/ Monitoring information is sent using callbacks They are regularly sent to a central monitoring service based on the same code as DQ2 central catalogs Apache web service with backend MySQL DB The callback parameter can be configured on the site services installation Extra callbacks on events/errors can be specified on the registerDatasetSubscription command dq2 registerDatasetSubscription --monitor=mail:someone@cern.ch my_ds CERNCAF

6. How It Works Types of callbacks --monitor executed each time there is a state transition on the site services agent --callbacks-file-done executed each time a file on that subscription is successfully transferred --callbacks-vuid-complete executed when all dataset subscription files are copied --callbacks-error in case an error occurs while processing the subscription sends error type and description Examples --monitor=mail:some.email@domain --callbacks-file-done=http://some.url/

7. How It Works Database is composed by three tables file states errors summary information per hour (just throughput, no of files copied and no of errors) Data is deleted from the first two tables after a week only file DONE states from the file table - we keep HOLD states For the web pages.. on the ‘current transfers’ pages, data is read directly from the DB cron jobs run every 10 minutes to produce the plots on the main page and fill the summary table

8. DDM Monitoring

9. The main page shows what is going on overall, with throughput plots to each site for the last 4 hours, last day and last week On the current transfers page for each site we can see summary of the status of the files subscribed to the site the datasets currently being processed and datasets completed recently the recent throughput in numbers and the ratio of successful transfers to errors the last events and errors that occurred for each dataset, the state of each file for each file, all its attributes and errors

10. DDM Monitoring

19. There were about 220,000 accesses to the webpage in the last 2 months ~180,000 from googlebot.com… but the rest quite distributed around the world Dataset overview with different colours Last 100/2h errors page but should be variable It’s fast apart from when errors table gets very full - see next slide

20. DDM Monitoring The errors table grew to about 3 million rows after 2 months! which made errors queries and slow this was before automatic deletion after 1 week Much of this was because errors were continually re-sent (unlimited retries) Site overviews of errors Automatic notification of errors to those responsible Measurements of the quality of the transfers We have an open savannah task with more feature improvements https://savannah.cern.ch/task/?func=detailitem&item_id=3613

21. DDM Monitoring We need to get the feeling of how a site is doing overall rather than looking at individual file error messages i.e. the equivalent of site functional tests but for DQ2 but this is difficult, e.g. how to tell the difference between no data subscribed to a site and a problem at the site? How to synchronise monitoring with site when site DB is recreated Success/error ratio is not realistic ‘File exists’ error on file registration in LRC can be repeated 1000’s of times The callbacks put quite a heavy load on the site services (A wider issue) the coordination of downtimes/blacklisting sites

22. Dashboard monitoring

23. Dashboard Monitoring Based on the currently available monitoring For the same data being collected you get in addition: different output formats for the same data you see in the webpage (CSV, XML,...) command line tools for all available queries [testing] more flexible queries when dealing with large amounts of data (you can provide a starting date, offset and limit and a subset of states to be retrieved) A new web interface This has been running successfully (collecting data from 2 sites – ASGCDISK and ASGCTAPE)

24. Dashboard Monitoring But you also get: an ORACLE backend for the collected data (service provided by CERN IT) LCG SAM (Service Availability and Monitoring) critical test results for the fabric services at each site (FTS, LFC, SRM, SE,...) Site Status Evaluation – taking different sources into account (DDM Site Services events, SAM data, other tests...) from here we can also have the state of clouds, not only individual sites When: backend and data querying are finished, CLI tools are completed, we are now fixing last issues with the web interface

25. Dashboard Monitoring - Plans Immediate: provide historical information on site behavior/performance – like in the current monitoring, but allow also dynamic queries Immediate: deploy the different CLI tools on AFS (will be done by the end of the week) Monitor fabric services individually – especially interesting in the case of the FTS Implement the missing features listed in the Savannah task (most of them are already available) Add dataset browsing (especially dataset location) capabilities to the interface

37. Dashboard Command Line list complete datasets in ASGCDISK dashb-dataset-list -S COMPLETE ASGCDISK retrieve dataset and dataset location information

38. Dashboard Command Line file summary on ASGCDISK dashb-file-summary ASGCDISK retrieve a summary of the state of files

39. Dashboard Command Line list files with state HOLD_NO_REPLICAS in ASGCDISK dashb-file-list -L 6 -S HOLD_NO_REPLICAS ASGCDISK retrieve file and file location information

40. Dashboard Command Line list errors in ASGCDISK dashb-site-errors ASGCDISK retrieve the errors collected

41. Dashboard Command Line summary of error types in ASGCDISK dashb-site-summary ASGCDISK retrieve a summary of the error types collected

42. Dashboard Command Line retrieve status of each site dashb-site-status

43. Dashboard Command Line all monitoring information on a command line tool user can page results multiple output formats text/xml, application/xhtml+xml, text/csv filtering of results by file state, date of the last event