Starting a new Cloud Computing Project


More and more companies start Cloud Computing Projects, with a lot of Startups also among them. But what do you have to take into account when you start a new Cloud Computing Project? Is it save to just start or should you consider some best practices in project management? And if so, what do you need to do regarding Cloud Computing? In this article we will give a brief overview on what is necessary to get started with Project Management for Cloud Computing.

Project Management itself consists of the following 5 Iterations:

1.Project Initialisation
2.Project Creation
3.Project Planing
4.Execution
5.Introduction

Each Iteration contains some sub-processes which we will describe more detailed now.

Project Management in the cloud
Project Management in the cloud

The first iteration, Project Initialisation, basically starts when someone realizes that there is a need for a project or someone has a business idea. Normally, you start building some KO-Criterias, like feasability or already existing products/platforms. If your project “passes” these KO-criterias, you might move on on evaluate Project Risks. This task often comes with a SWOT-Analysis. In a SWOT-Analysis you check the project for Strength, Weaknesses, Opportunities and Threads. Another important factor to analyse are the Stakeholders, since they can take affect on the project. Stakeholders are people or organizations that have a special interest in the project or product, such as the top-management, customers, owners or co-workers.

Once you are done with the basics, it is necessary to do a less corse-grained evaluation of the project. Initially, you would analyse what platform will be used. This is a very important part for Cloud Computing as we have different platforms that server different technology and offer various possibilities. A major thread is the risk of a vendor lock-in, what shouldn’t happen at all. Therefore, it is necessary to look at the platform and figure out how easy it is to move to other platforms or services. Once you decide to use a specific platform, it is necessary to evaluate what knowledge about this platform is available within the team/company. Other important factors are the platform costs and the interoperability with external services.

In the next phase, Project Creation you start with planing the project and setting some variables for it. You would also create the initial project plan and select the project organisation. The project organisation heavily depends on team size and knowledge of team members. If you are in a very agile environment, you might not want to have a very strict project organisation, whereas other environments require a rather “fixed” organisation form.

With Project Planing, you start detailing your project with costs and detailed delivery dates. In Project Planing, you would also select the Iteration model for the project, like in “Project Creation”, you need to select the iteration model based on your environment. If it is heavily agile, you might not use the “V-Model” but rather xP or Scrum-like techniques.

The phase Execution requires detailled monitoring about what is going on in the project. Some key indicators are the project milestones and the budget. If these indicators are out-of-bound, adjustment might be necessary.

The last phase, Introduction is an often underestimated phase, since it requires additional knowledge of go-to-market strategies and very good marketing. Often, there is no more budget available after the project has finished. Now imagine you got a great product but no money to tell it to possible customers? A clear go-to-market strategy is necessary in order to complete a project successful.
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Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

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