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  1. SAFe Program
  2. SP-1048

Assess performance latency needed to launch a containerised (receive) workflow using k8s

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      There is still concern & unresolved risk that the launching a set of containers for a time critical workflow (such as receive) incurs more latency than the current design allows. Making an initial quantitative assessment which can be repeated and scaled in future is therefore an important step towards mitigating this risk.

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      There is still concern & unresolved risk that the launching a set of containers for a time critical workflow (such as receive) incurs more latency than the current design allows. Making an initial quantitative assessment which can be repeated and scaled in future is therefore an important step towards mitigating this risk.
    • Hide

      < To be discussed with the FO at PI planning>

      • Benchmark scripts added to suitable repo in SKA Gitlab
      • Benchmark results captured on confluence and socialised with stakeholders at a system demo.
      Show
      < To be discussed with the FO at PI planning> Benchmark scripts added to suitable repo in SKA Gitlab Benchmark results captured on confluence and socialised with stakeholders at a system demo.
    • 2
    • 2
    • 6.5
    • Team_PLANET
    • Sprint 5
    • 7.5

    • PI24 - UNCOVERED

    • Team_PLANET
    • SPO-575

    Description

      Assess performance latency needed to launch a containerised (receive) workflow using k8s eg. "Launch" here means the time until we know receive addresses and have reserved all required resources (especially buffer) to the point where SDP can indicate that it is okay to proceed with the scheduling block. This feature is basically about whether we can do this through Kubernetes or need an intermediate reservation/allocation process of our own to buffer delays.

      Ultimate goal might be to test this for 500 nodes, ~6PB of storage but we should scale incrementally towards this. This is related to ADR-8, we would ideally like a <5second response time for the assign resources command (might become an NFR).

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          relates to

          Enabler - An Enabler supports the activities needed to extend the Architectural Runway to provide future business functionality. These include exploration, architecture, infrastructure, and compliance. SP-1179 Extend k8s platform performance tests to include buffer provisioning

          • Won't have (this time) - Items labelled as "Won't have", have been agreed by stakeholders as the least-critical, lowest-payback items, or not appropriate at that time. As a result, "Won't have" items are not planned into the schedule for the next delivery timebox.
          • Funnel

          Feature - A Feature is a service that fulfills a stakeholder need. Each feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI). SP-950 Updated visibility receive workflow integrated into the SDP prototype

          • Not Assigned - Priority is not assigned yet.
          • Done

          Enabler - An Enabler supports the activities needed to extend the Architectural Runway to provide future business functionality. These include exploration, architecture, infrastructure, and compliance. SP-1035 Test deployment of MeerKAT SDP stack using k8s

          • Not Assigned - Priority is not assigned yet.
          • Done

          Enabler - An Enabler supports the activities needed to extend the Architectural Runway to provide future business functionality. These include exploration, architecture, infrastructure, and compliance. SP-1178 Test updated visibility receive code with preallocated nodes

          • Won't have (this time) - Items labelled as "Won't have", have been agreed by stakeholders as the least-critical, lowest-payback items, or not appropriate at that time. As a result, "Won't have" items are not planned into the schedule for the next delivery timebox.
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                m.deegan Deegan, Miles
                b.mort Mort, Ben
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                Feature Progress

                  Story Point Burn-up: (41.94%)

                  Feature Estimate: 2.0

                  IssuesStory Points
                  To Do39.0
                  In Progress   00.0
                  Complete36.5
                  Total615.5

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