In this post, I will describe success factors and inhibitors for self service IT. I will evaluate how the impact of each factor might be. There are three possibilities: high, medium and low.
The first table will display the success factors:

In the next table, I will describe inhibitors for self service IT:

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Self Service Platforms often provide a lot of possibilities and features, but not all of them are necessary to end users in all situations. Therefore, it should be possible to disable features if they are not required. Disabling features should not affect the platform itself. This approach is also described as Service Oriented Architecture (SOA). (Jossutis, 2007) defines SOA as the following:
 

“Service-oriented architecture (SOA) is a paradigm for the realization and maintenance of business processes that span large distributed systems. It is based on three major technical concepts: services, interoperability through an enterprise service bus, and loose coupling.” –  (Jossutis, 2007)

 (Jossutis, 2007) describes 3 main aspects of SOA: services, interoperability and loose coupling. A service can handle different things such as providing simple read or write operations or more complex functionality that might be used in workflows. Services are normally described in an abstract way, which should help bridging the gap between IT and Business. In a self Service Platform, different services enables us to simply disable services that are not necessary, add new services to the platform or enable existing services. As stated earlier in this section, adding or removing services should not affect the platform in any kind. To achieve this, it is necessary to decouple the services.
Another key concept of SOA is loose coupling, which basically states that services should continue to work even if other services are missing and that services might not know about other services. Loose coupling also means that dependencies should be removed. If one service is updated to a new version, all other services that might interact with the now updated service should still be able to work without any modifications. This requires a very abstract way of communication: messaging. Messaging via an Enterprise Service Bus improves interoperability for system integration. Services now simply don’t communicate with each other directly but they rather post messages to an Enterprise Service Bus. The Enterprise Service Bus keeps the message alive until someone (typically a service) processes the message. Services usually don’t know about the service they are interacting with since it is like in a fabric: Person A leaves a message that the new tools are ready for pick-up. Person B that is in charge for picking up tools sees the message and brings the Tools to another department. The communication is much more asynchronous now, since the service simply doesn’t know when the task will be processed. This type of communication is very similar to the communication used by people on smartphones/mobile phones. Person A sends a text message to Person B and Person B will eventually reply (or maybe not) to Person A. Synchronous communication would now be if Person A simply phones Person B.  (Miller & Cardoso , 2012) also describes SOA as a key driver for Internet-based self Services in their work on SEASIDE.
Image Copyright: Intel Free Press

The easiest way to implement a self Service Platform is to provide an IaaS-Platform. Some IaaS self Service Platforms that are available open source are described and evaluated in Chapter 2. Infrastructure as a Service often serves as a foundation for Platform as a Service or Software as a Service Platforms. There are also some Platform as a Service Implementations available such as ConPaaS  (Pierre & Stratan , 2012). Software as a Service Applications usually needs a lot of customization to make them available as self Service Applications.
To transform the IT to a self Service IT, there are some possible process optimizations available: IT departments could start with the most manual, the most time critical or the most error-prone process. If a process is manual and there are a lot of repeatable tasks, there is a good chance that this process can be transformed into an automated task. Time critical processes also have huge potential in automation since it might be possible to save money by reducing time-to-market.
Once the processes automated are identified, there are some other steps the enterprise might execute:

• Break down high-level processes. Processes, which are defined as high-level processes can now be split into smaller, granular components. It is also possible to include sub-processes if needed.
• Create abstract processes. Identify locations where lower-level processes can be „packaged“ and reused in multiple high-level components. This reduces process complexity and improves maintainability of processes.
• Identify process triggers and end-points. Process Triggers are End-user requests, time events, … and end-points are Notifications, validation actions…
• Identify linkages and interfaces between steps of each process.
• Codify any manual steps wherever possible. Manual steps can be automated by adding custom code.

self service storage (C) Seth Anderson

Simple to use

Since users of the self Service Platform are now end-users and not members of the IT department, the platform should provide a clear and understandable interface. The platform should also offer the possibility to integrate within existing platforms such as the internal portal to lower confusion of end users and improve the level of integration of different applications. A simple platform helps the end users to learn about the capabilities and possibilities of the self Service Platform. Furthermore, it lowers the support calls to the IT department. Self Service Platforms transfer a lot of responsibility from trained IT staff to end users in departments within the enterprise. This requires a lot of attention to design such portals, since users must only see what they need to see. If marketing regularly needs to launch new websites, this possibility should be presented to the end user in a simple and understandable way. Typically, end users don’t care about how powerful their instances are, unless it is a technical department. The marketing department might only be interested in how many customers can use this platform. If we set up a website powered by WordPress, the type could be indicated like that: “each instance allows 1 million views per hour”. This would give a much better understanding to the end users how many instances they might need and how they can estimate costs that will occur by each instance they decide to launch. The platform should allow elasticity on that as well. If instances are not needed any more, they can be shut down automatically. The end user shouldn’t care about that.

simple to use IT self services at Intel (C) The Intel Free Press

Quota Configuration and User Roles

With self Service Platforms, end users get more responsibility as with the traditional way how people deal with IT. More responsibility might also lead to greater risk of misuse. People could launch instances and simply forget that other departments might also need instances. This could lead to a over-utilization of the datacenter. Usually, resources within a company’s datacenter are not infinite and unused instances can be used better for other load. Therefore, the platform should allow some sort of quota configuration. A quota configuration within a self Service IT Platform offers the possibility to set how many instances a specific user or department can use. The IT department could set that the marketing department can utilize a maximum of 100 concurrent instances of a specific type (e.g. 4 cores with 8gb of RAM per instance). This could start with a coarse-grained configuration (e.g. 100 instances maximum for the marketing department, 100 instances for the R&D during business hours and 500 after 8pm) and gets fine-grained in the departments. This would mean that each department gets more responsibility on how to use the available IT resources, but it also requires someone that is responsible for IT within a department. Typically, this would be a manager or assistant to a manager. The IT responsible can now set different quotas within their own quotas (let’s assume it is the marketing department with a maximum of 100 instances). Different websites, applications and projects would have different quota sets, which are combined with the department quota. However, this requires different user roles with different rights.

For Cloud Solutions, Scalability and Elasticity are key requirements. In private Cloud Solutions, this should also be supported, even if scalability and elasticity might has a lower border as we see in the public Cloud. Private Cloud Computing environments basically use dedicated Hardware and resources are not shared. Public Cloud Solutions use resource sharing, which is basically not available in private Cloud Solutions. Scaling applications means that we can add a new instance of Linux or a Windows Server. Elasticity is something “more advanced” to that as described by Reuven Cohen, an opinion leader in Cloud Computing (Cohen, 2010). Reuven describes scalability as the possibility to “grow to the demands of the users on a platform” whereas he states that elasticity is something that reflects real-time conditions. A platform might have millions of users, but if this platform is only available in the United States, there might be significant fewer load on the servers during night. The load will be much higher at peak times and elasticity means that unnecessary instances are shut down if the load is lower or that new instances are started if the load is higher. Elasticity is something very important to self Service Platforms, since they basically exist within an enterprise environment. Demand might change over time as not all enterprises act globally and even if they do, different platforms are used in a different manner. Let’s look back to the marketing department introduced earlier; especially in marketing, different groups of users are targeted and it is about targeting regions individually. What works well for customers in the United Kingdom might not work for customers in France and therefore, the website(s) might be different. That makes elasticity important since unused instances can be shut down to use the now free instances for other applications and services.  (Owens, 2010) defines Elasticity as „the golden nugget of Cloud Computing“ and a key inhibitor to move to Cloud Environments. A very similar definition on what Cohen defined as elasticity is also provided by the National Institute of Standards and Technology  (Mell & Grance , 2011):
 

elastictiy and scalability for self service platforms (C) Polycart

“Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.” –  (Mell & Grance , 2011)

As stated in the beginning of this section, the hardware available to run these services is not infinite and it is much lower as we in public Cloud Solutions. Better utilization of the Datacenter can now enable less critical tasks to be run overnight and use free instances. The IT department could even offer them at lower prices, as we can already see them with spot instances on Amazon Web Services, a popular public Cloud provider  (Amazon Web Services, Inc, 2012). A possible use-case could be the research department, which calculates non time-critical tasks during night and saves money by doing so. Since self-Service platforms should be easy to use, most of the elasticity has to be handled by the platform. The IT-department would only set a quota of how many instances are available for a specific service or application and set the rules and boundaries for elasticity. The consumer (or customer) only starts the new service or application and don’t have to care about scaling and elasticity issues, since it should be easy to use.