Large Synoptic Survey Telescope: From Cloud Native to Dark Energy
Relying on the largest camera sensor ever designed, the Large Synoptic Survey Telescope (LSST) will revolutionize astronomy. The LSST data processing pipeline requires computational power of thousands …
| Talk Title | Large Synoptic Survey Telescope: From Cloud Native to Dark Energy |
| Speakers | Fabrice Jammes (Senior cloud architect, LSST Corporation & French National Institute of Nuclear and Particle Physics (IN2P3)) |
| Conference | KubeCon + CloudNativeCon Europe |
| Conf Tag | |
| Location | Barcelona, Spain |
| Date | May 19-23, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Relying on the largest camera sensor ever designed, the Large Synoptic Survey Telescope (LSST) will revolutionize astronomy. The LSST data processing pipeline requires computational power of thousands of processors and several petabytes of data storage capacity per year. Celestial objects physical properties are stored in a database which will include trillions of entries. With a volume of many petabytes, this catalog will play a major role in research from identifying asteroids to understanding dark energy and matter. To meet those needs, a highly distributed software called Qserv, is being developed by an international team of engineers from USA (Stanford University) and France (IN2P3) Fabrice Jammes (IN2P3) will present the Qserv architecture, the challenges it must address, and how this disrupting database efficiently leverages Kubernetes.
