DKB@ATLAS instance

Current status: OK.

ToDo:

1. Check/update AMI client version (viktor)
2. Check master vs. data4es-prod (mgolosova)
3. (If item 2 is OK) Reset data4es-prod on master and apply the new version in production (viktor)

Integration w/ BigPanDA Mon

Study report on the "time series issue":

1. Task metadata from DEFT give us not pure "time series", but "cumulative sums" series -- with gaps.
2. Cumulative sums with gaps cannot be aggregated over multiple series as-is.
3. ES derivative aggregation cannot correctly reconstruct time series from cumsums (gaps are treated incorrectly).
4. InfluxDB correctly works with gaps, but the whole query that will generate the goal series (for whole campaign) is not constructed yet.
5. Theoretical study of InfluxDB technical characteristics say that it can work with "ephemeral" time series (multiple short series instead of few indefinitely continuous series).

ToDo:

1. This week:
   • full InfluxDB query for campaign step statistics;
   • storage scheme;
   • data load module (stage);
   • prepare the real-life data sample;
   • load sample to InfluxDB@bamboo instance;
2. Next steps:
   • InfluxDB instance installation/configuration via Puppet;
   • pre-load T-stage (after 040?);
   • adjustment of the data4es process;
   • run new version in production;
   • REST API server method.

Paperwork

Suggestion: publish ex-ICCS paper and DKB new-instance-guide as preprints.

ToDo:

1. Check if KI preprint is an option.
2. ...