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  1. SAFe Program
  2. SP-1481

Deploy a Rucio instance on IRIS

Details

    • Feature
    • Not Assigned
    • PI9
    • None
    • None
    • Data Processing
    • Hide

      Gain experience in deploying and operating Rucio, this will allow us to initiate long haul data transfers in the future and assess if and where Rucio as a data management solution fits into the SRC-tech sphere. 

      Show
      Gain experience in deploying and operating Rucio, this will allow us to initiate long haul data transfers in the future and assess if and where Rucio as a data management solution fits into the SRC-tech sphere. 
    • Hide

      Rucio server running with the essential daemons, test transfers to/from UK sites successfully performed via Rucio. 

      Show
      Rucio server running with the essential daemons, test transfers to/from UK sites successfully performed via Rucio. 
    • 2.5
    • 2.5
    • 10
    • Team_ESCAPEES
    • Sprint 5
    • Show
      Documented in the repo README: https://gitlab.com/ska-telescope/src/ska-rucio-prototype
    • 11.3
    • Stories Completed, Integrated, Outcomes Reviewed, Demonstrated, Satisfies Acceptance Criteria, Accepted by FO
    • PI22 - UNCOVERED

    • SPO-895

    Description

      Deploy an SKA-owned Rucio instance on multi-node K8s cluster running on IRIS cloud machines.

      This will mostly entail:

      • Rucio server with the essential daemons running. These are packaged in the helm charts (core functionality only atm which is what we desire)
      • Server auth: using existing Robot certificate 
      • User auth: user accounts created manually, no IAM integration planned till at least next PI
      • RSE config: Will be done manually,
      • FTS: CERN FTS + RAL FTS
      • Storage: UK storage sites to start with
      • Resources: multinode k8s cluster on STFC Cloud (c2.large flavour)
      • (Stretch) Monitoring: Helm charts exist, also for daemon monitoring (LIGO)

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                b.mort Mort, Ben
                r.brederode Brederode, Ray
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                Feature Progress

                  Story Point Burn-up: (100.00%)

                  Feature Estimate: 2.5

                  IssuesStory Points
                  To Do00.0
                  In Progress   00.0
                  Complete820.0
                  Total820.0

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                    Resolved:

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