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  1. SAFe Program
  2. SP-4288

Add benchmark metrics into a dashboard

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    • SRCnet
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      The SRC workloads Gitlab repository hosts workloads that are representative of what users will be running at SRC sites. The STARS script collects metrics (currently only processing duration) for the tasks, which are recorded on confluence. This feature would use existing monitoring infrastructure (likely Elastic + Grafana) to store the metric data output from STARS. This will be the first step towards enabling us to view in real time the performance of different SRC machines, a key component of the eventual compute tests described in the SRCNet 0.1 Implementation Plan.

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      The SRC workloads Gitlab repository hosts workloads that are representative of what users will be running at SRC sites. The STARS script collects metrics (currently only processing duration) for the tasks, which are recorded on confluence. This feature would use existing monitoring infrastructure (likely Elastic + Grafana) to store the metric data output from STARS. This will be the first step towards enabling us to view in real time the performance of different SRC machines, a key component of the eventual compute tests described in the SRCNet 0.1 Implementation Plan.
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      AC1: At least one task in the src-workloads repo has a means of verifying that the task completed successfully each time it is run (via checksum or hardcoded success criteria)

      AC2: Script is added to the src-workloads repo, or STARS is modified, such that when the task(s) in AC1 are run, the performance data is pushed (along with easily obtainable machine data) to a user-specified Elastic (or other NoSQL document store) DB.

      AC3: New dashboard added to existing Grafana instance to display results from task runs at different sites.

      Show
      AC1: At least one task in the src-workloads repo has a means of verifying that the task completed successfully each time it is run (via checksum or hardcoded success criteria) AC2: Script is added to the src-workloads repo, or STARS is modified, such that when the task(s) in AC1 are run, the performance data is pushed (along with easily obtainable machine data) to a user-specified Elastic (or other NoSQL document store) DB. AC3: New dashboard added to existing Grafana instance to display results from task runs at different sites.
    • 2.5
    • 2
    • 0
    • Team_MAGENTA

    • PI23 - UNCOVERED

    • PI23 SRC23-PB SRCNet0.x example-workflows-and-benchmarks tests-compilation

    Description

      Reducing scope of feature to fit within PI23 (yet to discuss with Alex):

      The deployment of new monitoring infrastructure has been removed from the previous version of this feature, since it is possible to use existing DB/dashboard instances.

      This feature is now to focus on the development needed within the src-workloads repository. Before automated performance metrics about task runs can be captured, it needs to be possible to automatically determine whether a task ran successfully (or failed). This can use e.g. hardcoded checksum validation (or even just verify that expected output files created successfully) for now.

      Once this has been done, the STARS script should be modified so that it can push the performance score, together with other easily obtainable (or user-set) metadata, to a running Elastic instance (or other document-type NoSQL DB). During local development this can use an ephemeral Elastic container.

      Finally, a simple dashboard view of this data can be added to an existing Grafana instance.

      Feature Point estimate sized to give time to learn about relevant technologies.

       

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          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-4326 Service monitoring v0.1 infrastructure

          • Must have - Items labelled as "Must have" are critical to the current delivery timebox in order for it to be a success.
          • Implementing

          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-4394 Retain src-workloads execution statistics in a DB that enables performance monitoring

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          • Discarded

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                Jesus.Salgado Salgado, Jesus
                A.Clarke Clarke, Alex
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                Feature Progress

                  Story Point Burn-up: (27.78%)

                  Feature Estimate: 2.5

                  IssuesStory Points
                  To Do411.0
                  In Progress   12.0
                  Complete35.0
                  Total818.0

                  Dates

                    Created:
                    Updated:

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