When is PaaS the best Option? Explained

Cloud

The National Institute of Standards and Technology (NIST) is responsible for the definitions of cloud computing and its attributes available today. It defines cloud computing as a model that helps in the ubiquitous, convenient and on-demand network access towards configurable computing resources.

According to the NIST standard, there are:

–    Five essential characteristics (on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service)
–    Three service models (SaaS, PaaS and IaaS)
–    Four deployment models (private cloud, community cloud, public cloud and hybrid cloud)

The focus here is on the service models, specifically on the Platform as a Service (PaaS) model. The role of Software as a Solution (SaaS) is towards applications, whilst PaaS tilts towards software development area. It is also different from Infrastructure as a Service (IaaS) in the sense of the platform used for software development. PaaS targets the workflow management irrespective of the data source in use for the application.

PaaS can be treated as a platform that allows developers to build web apps without the fiscal and maintenance difficulties conventionally faced.

Relevance of PaaS

A large number of professionals ranging from IT managers to small business enterprises are shifting towards cloud. As McAfee aptly puts it, switching from traditional IT infrastructure to the cloud is like a manufacturing company changing from steam to electricity 100 years ago.

PaaS has found a broad spectrum of consumers. This is evident from a case study done on a medical institute where doctors were using PaaS for patient screening. It was found that the average wait time dropped from 18 hours to less than sixty minutes, a massive breakthrough for health care professionals.

PaaS may also be considered useful in the following areas:

1.    A developing project which involves multiple developers.
2.    Interaction of external parties in the development process.
3.    Leveraging a data source for creating applications
4.    Automation of testing and deployment services
5.    Quality of service management in cloud and for SaaS

Whilst other uses are evolving, the abovementioned cover a holistic approach.

Case studies validate the usage of PaaS in different cloud instances

1st Case Study:

Use of PaaS architecture for Quality of Service (QoS) Management in Clouds
The University of Southampton in UK recently published a recent research study indicating that novel protocol presents real-time QoS at both application and infrastructure levels. The targeted problem was that whilst cloud computing greatly reduces cost of IT services, inefficiencies can be introduced in the absence of QoS measures.

PaaS helps in the management process by controlling the service life cycle, which includes service engineering, service level agreement design, provisioning and monitoring. Then parameters are set up for giving policies that would tackle temporal constraints. The study checked the setup on important application areas including film postproduction, augmented reality, eLearning tools and general virtual usage.

Cloud service providers such as Rackspace manifest a model similar. Most of the reputable ones provide general tools and techniques to application users in the management of QoS.

2nd Case Study: Simulation of Cloud Business Models

On the proceedings of the 21st European Conference on Information System, the use of PaaS for simulating cloud business models was mentioned several times.

There are three phases to develop a PaaS-based business model:

1.    Method Setup and the Acquisition of Data

This involves identifying the scope and target customers. The next step requires analysis of different business models and selection of one. Then, the data set needs to be selected before the user instantiates the data.

2.    Business Model Design

In this step, the business model would be created on the PaaS platform. The attributes have to be instantiated, and the meta-model has to be refined. Enriching the data set is the last requirement of this step.

3.    Business Model Simulation

This shows the market relevance of PaaS, since it allows for competition analysis based on the data attributes provided. The user can either run a price simulation or focus on analysis including ‘direct benchmark’ or ‘attribute variation.’

The holistic analysis provided above elucidates the scope, range and relevance of PaaS in different situations.

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