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HNSciCloud Project

This presentation provides an analysis of the HNSciCloud Project, including material used, project engineering techniques, and findings. It highlights methods used to define and analyze the project, as well as recommendations for improvement.

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HNSciCloud Project

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  1. HNSciCloud Project MSc in Project Engineering delivered by Professor Gilles Vallet Oxford Academicsfor Computing Science Department, University of Chester. Students Yassine Benaddou and David Carr

  2. Presentation to Partners • Background and Explanation for the Analysis. • Material used, for the benchmarking of the project   • Highlight Methods used, Project Engineering techniques. • Analysis of findings • Summaries Points • Greater Areas at Risk.

  3. Background and Explanation for the Analysis. The objective is to stress analysis the HNSciCloud Project. • Against the Project Engineering Professional framework results. • With the objective of reporting observation to the Project Coordinator for consideration and evaluation.

  4. Material used, for the benchmarking of the project   • The analysis of Document No {687614-HNSciCloud}-Part B. • PISCE No 644014 Research Procurement Model. • Consortium Document. • Project Engineer, Project Definition Scope Engineering Framework. • Strategic Plan for a Scientific Cloud Computing infrastructure for Europe. • Cloud for Europe D9.5 Risk Analysis Certification and other measures.

  5. Highlight Methods used, Project Engineering techniques to analysis HOW the project was defined. • Analysis of the Project Definition Baseline from the project document (Project Costs) to determine gaps. • Analysis of the Project Requirements Baseline from project document (Project Value) to determine gaps. • Production and Gap Analysis of Compliance Matrix (Definition/Requirement Baselines) • Analysis of Project Document against State of the Art Best Practice. • Project Document Analysis of the Critical Risk and Success Factors to determine gaps. • Project Plan and Schedule Analysis.

  6. Highlight Methods used, Project Engineering techniques. CERN has secured a budget of 75K Euro to subcontract legal/expert consultancy and the benchmarking activity. CERN will coordinate the work performed by subcontractors, in compliance with the description of each tasks and thus ensure that the outputs of each task serve the purpose of the work package; i.e. completion of the procurement and tendering. Our analysis provides 17 best-practices in relation to 13 categories were identified, this consistency clearly demonstrates that the project has been thoroughly studied and filled without leaving any margin of error. In our case, we suggest to add three best-practices that could complete the identified best-practices. A or Gartner CCMM (See Appendix)

  7. Analysis of findings. The comprehensive analysis concluded, that :- The HNSciCloud Project plan is very robust for the implementation of the Hybrid Cloud Pilot given the strategic and actual support from the European Commission and the consortium of European Science Partners.

  8. Analysis of findings. The Project Engineering Methodology observations were made from analysis of the Project Design Document and reference to the PICSE document. The key points from our observations for future work, agreed with the Project Coordinator are: 1) Introduce change control management (WP1). The Project Coordinator has advised that the Project Coordination Team concur with our analysis and they are implementing the best practice standard for Change Control.

  9. Analysis of findings. 2) Define customer acceptance criteria, notably for scientific end users (WP6). The majority of the end-users (scientific researchers) should not be impacted by the introduction of the new IaaS (Infrastructure as a Service) services. • However, it will represent significant change for another group of ‘users’, the IT staff, at the procurer’s Data Centre’s who will be responsible for integrating the procured commercial IaaS, into their existing computer services delivery models. • Consequently, we need to differentiate between the scientific researchers and IT staff with a tailored communications and education programmed for each group.

  10. Analysis of findings. 3) Refine the Requirement KPIs to include tolerance & frequency and identify who will be responsible for measuring each KPI (WP1). Project team see the potential for delays in the project schedule due to the execution of the EC’s procurement process as being a significant risk. This has been recognised by the procurement group at CERN which has already taken some actions: • To reflect this new schedule in the project plan to be produced in January. • Hiring of a PCP expert into the procurement group. This person has accepted the contract and should start during February 2016. • In addition, the Project Team have foreseen that additional legal expertise will be subcontracted to assist the project on two points: • Define terms and conditions that are suitable for the commercial cloud market which will be part of the contract signed with IaaS service providers (WP1, month 3). • Perform a review of the PCP tender material before its publication (WP2, month 4).

  11. Summaries Points • HNSciCloud Project plan is very robust for the implementation of the Hybrid Cloud Prototype given the strategic and actual support from the European Council Commission and the consortium of European Science Partners. • Our observations for the project • Introduce change control management (WP1). • Define customer acceptance criteria, notably for end users (WP6). • Refine the KPIs to include tolerance & frequency and identify who will be responsible for measuring each KPI (WP1).

  12. Greater Areas at Risk for Project Management Observation given the Procurement Task dominate the Project Plan do to the EC Call of requirements. Consider paralleling the Design, Prototype and Pilot Detailed Planning Element to the Procurement to maximise the DO, Review and Act elements. This is low risk/cost option, which increase the time available for the DO, element.

  13. Greater Areas at Risk for Project Management This model presents an example of risk impact definitions for Four different project objectives. It is a useful "benchmark” for the HNSciCloud Project Objectives against the scale of risk, determined by Risk Management. Analyzing the level of Risk against the Project Plans Project Objectives, our observation was a 10% time increase risk consistent with the EC Procurement process. REF: PMBOK-Guide

  14. Appendix : Gartner cloud computing maturity model (CCMM) A cloud computing maturity model (CCMM) is a model for managing the provision of cloud computing services. This model should serve to help business leaders and handlers make progress in providing cloud services to a set of customers. This type of model is generally useful in "benchmarking" services and analyzing a level of success, consistency and achievement of service goals

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