CLOUD COMPUTING SEM 3

  Hello students, In this last blog of Unit 3, we look at Data Intensive Computing. Data intensive computing are types of computing problems where data is very huge in numbers and size from few mega bytes to tera bytes to peta bytes to zeta bytes to exa bytes. Such data sizes are called to be Big Data.  There has been data explosion in last many years ever since technology has become mature and advanced.  Relational model based databases made up of tables, records, keys and relationship are not able to  manage Big Data due to huge amount of exponentially growing data and due to its strict structured format and ACID restrictions. NoSQL databases was the answer to Big Data, to all data that was huge in numbers, were unstructured or semi structured.  Big data could be split horizontally as well as vertically into managed datasets, which could be stored in repositories as required.  One could query the datasets to know its content using meta data attributes ...

Dear students, In our last blog, we came across concurrent computing, where the focus was how a single program can be computed faster by decomposing either based on data sets (Domain Decomposition) or based on functionality (Function Decomposition). Once the decomposition is planned properly in the program, it can be assigned to multiple cores or multiple threads. Concurrent computing is a form of parallelism on the same machine. When we talk about task computing, we are looking at executing not single program, but multiple programs. Each program can be considered as a task with lot of data or consisting of many work units. These tasks can be executed using multiple machines. Task Computing is a form of parallelism on multiple machines. It is a network of machines, where one machine (called local node) becomes responsible to submit the task, then one machine schedules it , checks status on all submitted tasks (access nodes) , one machine provides any resources such as files, data...

Hello students, In this blog, we focus on concurrent computing. The word 'concurrent' means at the same time. In computing world, when we execute two programs at the same time, we can say it is concurrent. Concurrency can be achieved by executing two programs on two different processors or if the processor has multiple cores, then concurrency can be achieved by executing two programs on different cores or if we can also run two programs on two different computers at the same time. Throughput Computation When we have a high level of computation to be done in a single program itself to achieve at a result, then parallel computation techniques are used to break down the entire program into independent work units (computational unit) and execute them concurrently. Such computation problems are throughput computing problem. Examples of throughout computation could be scientific modelling, video encoding, gaming, machine learning, deep learning and much more. Multitask...

Hello students, If you are ever asked a question in exam about “Cloud Platform” (not PaaS), remember three cloud platform providers namely AWS, GCP, Azure In this blog we look at the cloud computing features provided by three cloud providers namely Amazon Web Services (AWS) Google Cloud Platform (GCP) Microsoft Azure Cloud Amazon Web Services We look specifically at 13 services provided Amazon Web Services cloud provider 1. Management Console – user interface for customers to use AWS services over the internet 2. Elastic Compute Cloud (EC2) – virtual machine provisioning 3. Internet Users – User access is secured via public key infrastructure and Identity Access Management services 4. Amazon Machine Image (AMI) – linux, windows images are readily available to use and go, with many other complex machine image via AMI services 5. Static Network Addresses – Elastic , public and static IP addresses is available readily for use over the internet 6. Servers – any number o...

Hello students, In this blog, we delve on Multitenant software. As we have known through our Virtualization assignment, Multitenancy is all about taking one physical thing shared with multiple customer.  Cloud implements Multitenancy at all levels, from hardware to software, from infrastructure to platform to software. Virtualization is an example of using one physical machine and creating multiple virtual machines from it.  One processor have multiple cores that can be shared with multiple tasks from different customers.  A network device with multiple ports can be divided into different virtual networks utilized by different customers.  Multitenancy is about supporting multiple entities and hence Multitenancy is all about  Multiple Entity Support. Multitenancy in achieved in SaaS using three techniques Single Schema Model Meta-Data Customization  Multiple Schema Model Single Schema Model A Schema refers to the design. In databases it re...

Dear students, We start our Unit 3 with one of cloud technologies Web 2.0 When internet was born, lot of applications that were created could be termed as Web 1.0. Then Web 2.0 technology enhanced the Web technologies. Web 2.0 covered four different technologies namely SOAP services REST services AJAX services MASHUP services We covered the entire Semester 2 learning about SOAP services and REST services SOAP Services SOAP services utilized SOAP protocol 1.0, 1.1, 1.2. It initially operated using HTTP, was inter-operable between any type of systems, languages, applications. SOAP made application integration easier and was loosely coupled. SOAP utilized XML data structure for any type of communication over HTTP application protocol. SOAP now works on protocol other than HTTP too and is suitable for complex applications. REST services REST services later was introduced to be much simpler that worked in distributed system with simple URI links and plain HTTP CRUD methods (GET...