| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 04035 | |
| Number of page(s) | 8 | |
| Section | T4 - Data handling | |
| DOI | https://doi.org/10.1051/epjconf/201921404035 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921404035
Storage events: distributed users, federation and beyond
1
Deutsche Electron Synchratron (DESY)
2
Fermilab National Laboratory
3
University of Oslo
* e-mail: [paul.millar@desy.de]
Published online: 17 September 2019
For federated storage to work well, some knowledge from each storage system must exist outside that system, regardless of the use case. This is needed to allow coordinated activity; e.g., executing analysis jobs on worker nodes with good accessibility to the data.
Currently, this is achieved by clients notifying central services of activity; e.g., a client notifies a replica catalogue after an upload. Unfortunately, this forces end users to use bespoke clients. It also forces clients to wait for asynchronous activities to finish.
dCache provides an alternative approach: storage events. In this approach the storage systems (rather than the clients) become the coordinating service, notifying interested parties of key events.
At DESY, we are investigating storage events along with Apache OpenWhisk and Kubernetes to build a "serverless" cloud, similar to AWS Lambda or Google Cloud Functions, for photon science use cases.
Storage events are more generally useful: catalogues are notified whenever data is uploaded or delete, tape becomes more efficient because analysis can start immediately after the data is on disk, caches can be "smart" fetching new datasets preemptively.
In this paper we will present work within dCache to support a new event-based interface, with which these and other use cases become more efficient.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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