Data Avenue on MTA Cloud
Data Avenue is a data storage management service that enables to access different types of storage resources (including S3, sftp, GridFTP, iRODS, SRM servers) using a uniform interface. The provided REST API allows of performing all the typical storage operations such as creating folders/buckets, renaming or deleting files/folders, uploading/downloading files, or copying/moving files/folders between different storage resources, respectively, even simply using 'curl' from command line. Data Avenue automatically translates users' REST commands to the appropriate storage protocols, and manages long-running data transfers in the background.
Data Avenue is available on the MTA Cloud's official website (https://cloud.mta.hu/dataavenue). In the tutorial which is available under services menu, we establish a cluster with two nodes types. On the Data Avenue node the Data Avenue application will run, and on a predefined number of storage nodes an S3 storage will run, in order to be able to try Data Avenue file transfer software such as making buckets, download or copy files. We used Ceph and Docker components to build-up the cluster.
Publications:
- Hajnal Á, Márton I, Farkas Z, Kacsuk P: Remote storage management in science gateways via data bridging, CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE 27:(16) pp. 4398-4411. (2015)
Publisher: https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.3520
Eprint: http://eprints.sztaki.hu/8593/
- Hajnal, A., Farkas, Z., and Kacsuk, P. Data Avenue: Remote Storage Resource Management in WS-PGRADE/gUSE, 6th IEEE International Workshop on Science Gateways (IWSG), pp. 1–5, 2014
Kiadó: https://hungary.pure.elsevier.com/hu/publications/data-avenue-remote-storage-resource-management-in-ws-pgradeguse
Eprint: http://eprints.sztaki.hu/8097/
- Hajnal Á, Farkas Z, Kacsuk P, Pintér T: Remote Storage Resource Management in WS-PGRADE/gUSE. In: Kacsuk P (szerk.)Science Gateways for Distributed Computing Infrastructures: Development Framework and Exploitation by Scientific User Communities. 301 p. Cham (Németország): Springer, 2014. pp. 69-81. (ISBN:978-3-319-11267-1)
Kiadó: https://www.springer.com/gb/book/9783319112671
Eprint: http://eprints.sztaki.hu/8116/