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  1. SAFe Program
  2. SP-2589

Centralised Logging and Monitoring with zero-trust principles

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    • Feature
    • Must have
    • PI15
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      Having a centralised logging and monitoring solution will contribute the following:

      • A more robust implementation of logging and monitoring
      • Eliminate many dashboards
      • Aggregate data from different datacenters for further analysis
      • Lower maintenance overhead for management of the services
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      Having a centralised logging and monitoring solution will contribute the following: A more robust implementation of logging and monitoring Eliminate many dashboards Aggregate data from different datacenters for further analysis Lower maintenance overhead for management of the services
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      • Centralised Monitoring solution is implemented based on Thanos and Prometheus with all of the ST clusters: STFC Techops, STFC SDH&P, EngageSKA, PSI-Low (PSI-Mid) with HA and zero-trust network setup
      • Grafana dashboards are updated to work with the above monitoring solution
      • ELK is deployed and configured with a HA and zero-trust network setup with all of the ST clusters: STFC Techops, STFC SDH&P, EngageSKA, PSI-Low (PSI-Mid)
      Show
      Centralised Monitoring solution is implemented based on Thanos and Prometheus with all of the ST clusters: STFC Techops, STFC SDH&P, EngageSKA, PSI-Low (PSI-Mid) with HA and zero-trust network setup Grafana dashboards are updated to work with the above monitoring solution ELK is deployed and configured with a HA and zero-trust network setup with all of the ST clusters: STFC Techops, STFC SDH&P, EngageSKA, PSI-Low (PSI-Mid)
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    • Team_SYSTEM
    • 15.6

    • PI22 - UNCOVERED

    Description

      Centralised Logging and Monitoring is implemented so that there's no need to have different managed grafana dashboards and kibana.

      This means that we only have the dashboards on STFC for global usage with integrated dashboards and all logging and monitoring is aggregated using in-transit encrypted traffic for security. 

      Current logging is based on Prometheus and on PI14, as part of ST-1195 a preliminary analysis of Thanos is investigated as a tool for centralised logging solution. (Report is here: https://confluence.skatelescope.org/display/SE/Thanos+Investigation )

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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-2800 Centralised Logging with zero-trust principles

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

          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-2281 Zero trust networking

          • Must have - Items labelled as "Must have" are critical to the current delivery timebox in order for it to be a success.
          • 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-1816 multi-DC Logging as a Service

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

          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-1817 multi-DC monitoring as a Service

          • Not Assigned - Priority is not assigned yet.
          • Discarded
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                m.deegan Deegan, Miles
                U.Yilmaz Yilmaz, Ugur
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                Feature Progress

                  Story Point Burn-up: (100.00%)

                  Feature Estimate: 2.0

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