HNSciCloud Project
MS c i n Proj ect E ng i nee ri ng
d e l i vered by Pro fe ssor G i l l e s Va l l et Ox ford A cademi cs fo r
C o mput i ng S c i ence Department, U n iversity o f C hester.
S t udents Ya ssi ne B e naddou a nd D av i d C a rr
Presentation to Partners
1.
Background and Explanation for the Analysis.
2.
Material used, for the benchmarking of the project
3.
Highlight Methods used, Project Engineering techniques.
4.
Analysis of findings
5.
Summaries Points
6.
Greater Areas at Risk.
Background and Explanation for the Analysis.
The objective is to stress analysis the HNSciCloud Project.
1.Against the Project Engineering Professional framework
results.
2.With the objective of reporting observation to the Project
Coordinator for consideration and evaluation.
Material used, for the benchmarking of the project
1.
2.
3.
4.
5.
6.
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.
Highlight Methods used, Project Engineering
techniques to analysis HOW the project was defined.
1. Analysis of the Project Definition Baseline from the project document (Project
Costs) to determine gaps.
2. Analysis of the Project Requirements Baseline from project document (Project
Value) to determine gaps.
3. Production and Gap Analysis of Compliance Matrix (Definition/Requirement
Baselines)
4. Analysis of Project Document against State of the Art Best Practice.
5. Project Document Analysis of the Critical Risk and Success Factors to determine
gaps.
6. Project Plan and Schedule Analysis.
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)
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.
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.
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.
1.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.
2.Consequently, we need to differentiate between the scientific researchers
and IT staff with a tailored communications and education programmed for
each group.
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:
1.To reflect this new schedule in the project plan to be produced in January.
2.Hiring of a PCP expert into the procurement group. This person has accepted the contract and
should start during February 2016.
3.In addition, the Project Team have foreseen that additional legal expertise will be
subcontracted to assist the project on two points:
4.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).
5.Perform a review of the PCP tender material before its publication (WP2, month 4).
Summaries Points
1.
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.
2.
Our observations for the project
1.
2.
3.
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).
Greater Areas at Risk for Project Management
CERN
Design Procurement
CNRS
Design
Plan
DESY
Design DO
Design
Review
75 Days
15/07/2016
05/10/2016
Design
Act
Prototype Procurement
84 Days
16/01/2017 27/01/2017
Prototype
Detailed
Plan
CERN
75 Days
Design Plan
Design DO
Design
Review
84 Days
16/01/2017 27/01/2017
Design
Act
Proto
Act
108 Days
Design Procurement
05/10/2016
Design
Review
10/05/2017
Prototype Procurement
Pilot Procurement
84 Days
09/10/2017
10/05/2017
15/07/2016
15/07/2016
Prototype DO
03/11/2017
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.
CNRS
84 Days
15/07/2016
Prototype Initial Planning
DESY
27/01/2017
Pilot Detailed Plan
108 Days
84 Days
09/10/2017
10/05/2017
Pilot DO
Pilot
Review
Pilot
Act
Pilot Procurement
03/11/2017
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
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