Download presentation
Presentation is loading. Please wait.
Published byEmil Ward Modified over 7 years ago
1
Dashboard upcoming features A Hales, ALMA and M Chavan, ESO
2
Unambitious Goal Turn the original prototype into an ICT deliverable
Revision control Release cycle Change requests recorded as Jira tickets … Rewrite backend maintaining same API Prototype backend required reengineering Change should be transparent to users
3
A Troubled History First Dashboard Jira ticket: Jan 2014
Development started soon after Dedicated developer: Sep 2015 Initial Dashboard delivery: Dec 2015 Validation completed in: Aug 2016 Programming errors Database migration issues Communication issues
4
Good Initial Results, but…
Dashboard 2 deployed in October Initial goals were met Dashboard is an ICT deliverable Back-end completely rewritten Database size went from ~1 GB to ~40 MB Scales much better Minimal changes to the front-end However, several issues surfaced…
5
Issue Types Database migration issues Programming errors
Improper caching Frontend issues (inherited from prototype) Performance issues HOT! Unexpected usage HOT!
6
Performance Issues Database was completely redesigned
Goal: reduce data size and growth Query performance turned out much worse than expected “We’ll optimize later” approach OSF Oracle server is much less performing than test servers (and 1.5 server, possibly)
7
Unexpected Usage Database redesigned for GUI interaction
~100 of changes per day A few queries per minute But backend is being scripted as well Submitting up to 37 changes/sec Querying every ~30 msec More performance issues!
8
Mitigation Aggressive query optimization Extensive caching
Hit the DB only when needed “System events” not to be saved “Stow Pin”, “hvac”, … sent by utility script “Throttling” of incoming requests Prevent scripts from issuing excessive requests
9
Future Development In the process of collecting new requirements from DSO, ADE and AOG
10
Future Development From DSO:
SCIREQ-978: Allow dashboard to determine imaging characteristics of an array from selection of antennas Use Case: predict the array performance given a selection of antennas in the Dashboard (angular resolution, sidelobe level, min max level, Maximum Recoverable Scale). That way one can e.g. anticipate the selection that will perform better given a particular need, and also readily assess what will be the impact of leaving out given antenna elements (e.g. good for planning which antennas can be given to engineering)
11
Future Development From DSO: SCIREQ-978
Implementation: the Dashboard should allow the user to define an array interactively, then run a Python script (via an external service) to compute that array's characteristics. The python script already exist, and use the algorithm described in SCIREQ-328.
12
The Atacama Large Millimeter/submillimeter Array (ALMA), an international astronomy facility, is a partnership of Europe, North America and East Asia in cooperation with the Republic of Chile. ALMA is funded in Europe by the European Organization for Astronomical Research in the Southern Hemisphere (ESO), in North America by the U.S. National Science Foundation (NSF) in cooperation with the National Research Council of Canada (NRC) and the National Science Council of Taiwan (NSC) and in East Asia by the National Institutes of Natural Sciences (NINS) of Japan in cooperation with the Academia Sinica (AS) in Taiwan. ALMA construction and operations are led on behalf of Europe by ESO, on behalf of North America by the National Radio Astronomy Observatory (NRAO), which is managed by Associated Universities, Inc. (AUI) and on behalf of East Asia by the National Astronomical Observatory of Japan (NAOJ). The Joint ALMA Observatory (JAO) provides the unified leadership and management of the construction, commissioning and operation of ALMA.
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.