Cloud Computing Architectures: aims and characteristics of cloud systems


To find out about the Cloud Architectures we want to use, it is necessary to know the characteristics of distributed systems. Another important aspect we should consider looking at are the aims of cloud systems. If we know what aims and characteristics are, it might be easier to build a software architecture for the cloud. However, each implementation requires different approaches since each system is different from each other.

Let us start with the characteristics of cloud systems.

Cloud computing systems have a characteristic, that it is a sum of many systems (instances), but it feels like a single system for the end user. This means that it is transparent for end-users and end-users typically don’t see how many servers are involved. End users might even believe that this is running on a single server (but it is not like that). End users should not be confronted with the challenges architects/developers have to face when building a SaaS-Application. Just imagine Facebook, Twitter or Flickr: end users don’t really care about distribution, they simply want to use that platform. This means that our application has to look like a single software and hide the challenges we face for distribution.

A cloud computing system typically consists of different components. Components are various things such as instances, services, … If we build a distributed system, we have to utilise different instances with different roles. Some roles might host the website, other roles might do some background work. Different components is often implemented by SOA (Service Oriented Architectures) which is described later.

Different components as described above have to communicate with each other. Communication can be done with various technologies such as messaging. This requires the use of a message buffer.

Users of a cloud computing system can use the system in a transparent and consistent way. If a user travels, the system should represent the same state as it did before traveling. If the user works on a presentation for a client and saves the presentation, it should look absolutely the same when the user arrives at the customer’s site. Consistency is a challenge we often have to deal with in the Cloud and we will focus on that in a later post.

Cloud computing systems have to be extendable. If we have a SaaS-Application, it might serve 90% of all use-cases, but what happens with the 10% it can’t serve? It should be extented by additional services. If we look at a very important platform – Salesforce – it can be extended by a PaaS-Platform named “force.com”. To achieve extensibility, the platform must offer well-defined interfaces for potential consumers.These interfaces are typically served via an API.

The last characteristic we want to focus on is that distributed systems are often using a middleware. This middleware abstracts things from the operating system and serves interfaces to handle common things. We can see this with PaaS, where the middleware spans a large number of virtual instances. However, we simply don’t care about the operating system that is under the middleware.

Picture Copyright by Moyan Brenn

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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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