Big Data and Cloud Computing

Background

The emergence of cloud data storage and cloud computing is known to be a big facilitator and precursor to the big data rise. It may be referred to as the commodification of data storage as well as computing time using standardized technological advancements.

There are numerous advantages associated with using this kind of computing over the traditional techniques that were previously used in data storage. However, different kinds of cloud platforms sometimes also require to be incorporated with some traditional computing architectures as well.

This entire concept proves to be a dilemma for the big stake holders involved in the decision making process of high end big data management projects. There are several questions that need to be answered. These include which techniques along with which kind of cloud computing infrastructure may be deployed in order to create an optimal solution for different projects. Different kinds of big data projects in this regard exhibit different challenges including unpredictability, high capacity storage needs and immense computing power. At the very same time, the projects also expect inexpensive, dependable and swift products as well as other project outcomes. The aim of this article is to give you an introduction to cloud storage, cloud computing and the core architectures involved in the process.

Cloud Providers

Almost ten years ago, a startup that required a reliable computing infrastructure with connectivity to high speed internet had to hire some space in a data center or in several data centers sometimes. On contrary to it, presently any one of us may get whatever amount of storage and computing powers that we may require much easily in comparison to the troubles that we had to go through in the past. This starts off with small virtual machines and the range goes up to mini super computers. These services are paid per hour. In other words, you can enjoy several hours of super computing powers in exchange of a few hundreds of dollars. The services offered by cloud computing companies are usually globally distributed which ensures a high level of durability which was almost impossible in the past.

Cloud Storage

A professional grade cloud storage service requires to have a high level of durability and availability along with the ability to scale from just a few bytes to several petabytes. The cloud storage offered by Amazon’s S3 is known to be the best spacing solution in this regard. It promises a 99.9% rate of availability every month while the per annum durability is even higher than that. Similarly there are many other options that offer different packages of readily available cloud storage and computing powers.

Cloud Computing

Cloud computing makes use of computing resources visualization for running several standardized virtual servers that are present on just one physical machine. The cloud services providers make succeed in achieving this kind of accessibility using scale economies that allow low prices along with a billing facility based on several smaller intervals of time.

Cloud Big Data Challenges

There are several different challenges that are faced by cloud big data in order to provide the users with flawless accessibility to storage and other computing powers. There are different software products like Hadoop that are especially designed on the model of distributed systems in order to benefit from vertical scaling. They make sure to process smaller independent tasks on a massive parallel computing scale. These distributed systems also have the ability to serve as a high end data store or database like NoSQL. Hadoop’s HDFS, HBase and Cassandra are a few common examples in this regard. There are a few different alternatives as well. They are designed to offer a well coordinated stream of data processes in approximated real time using a cluster of different machines having complex work flows. 

The entire concept of interchangeability of different resources that are deployed in association with distributed software designs has the ability to absorb most of the failures in order to scale different computing instances. Bursting or spiking demands may also be accommodated as well. Renting out literally unlimited amounts of resources for different intervals enable us to carry out wonders in exchange of a very nominal amount of money. Web crawling and data mining are two of the biggest examples in this regard.

Cloud Architecture

There are three primary models of cloud architecture that have been developed so far. These include hybrid, public and private clouds. All of them share the same idea of commodification of resources which enable us to enjoy uninterrupted storage with incredible computing powers.

Private Cloud

As the name suggests, private clouds are designed to offer dedicated services to a single organization. They do not share any of their physical resources with others. These resources may be provided both externally as well as in house. The most typical underlying requirements in this regard include different regulations as well as security requirements in order to make sure the isolation of the resources of the organization from any malicious or accidental access through the shared resources. The setups of private clouds are considered to be very challenging as it is hard to achieve the economical benefits of scale within most of the projects even if all the industry standards are utilized. But even then this kind of cloud storage is considered to be the best and the safest among the rest.

Public Cloud

As the name suggests, public clouds make use of shared physical resources for processing, storage and transfer of data. However, the clients get to have isolated storage as well as a private visualized computing environment. There are a few security concerns that are associated with this kind of cloud which make high end clients to switch to a private cloud system.

Hybrid Cloud

A hybrid cloud architecture may be referred to as a merger of both public as well as private cloud deployments. This usually is deployed as an attempt for achieving elasticity and security or in order to provide inexpensive burst capabilities and base load. Several organizations are known to experience short intervals of high loads especially in rush hours.
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