Cloud Computing Questions

Q:

What is Hypervisor in Cloud Computing and its types?

Answer

The hypervisor is a virtual machine monitor (VMM) that manages resources for virtual machines. The name hypervisor is suggested as it is a supervisory tool for the virtual machines. There are mainly two types of hypervisors :


- Type-1: the guest Vm runs directly over the host hardware, e.g Xen, Hyper-V, VmWare ESXi


- Type-2: the guest Vm runs over hardware through a host OS, e.g Kvm, Oracle virtualbox

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Q:

What are the security laws which take care of the data in the cloud?

Answer

The security laws which are implements to secure data in the cloud are as follows:


- Input validation : controls the input data which is being to any system.


- Processing  : control that the data is being processed correctly and completely in an application.


- File : control the data being manipulated in any type of file.


- Output reconciliation : control the data that has to be reconciled from input to output.


- Backup and recovery: control the security breaches logs and the problems which has occurred while creating the back.

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Q:

What is the use of eucalyptus in cloud computing environment?

Answer

Eucalyptus stands for “Elastic Utility Computing Architecture for Linking Your Programs to Useful Systems” and provides an open source software infrastructure to implement clusters in cloud computing platform. It is used to build private, public and hybrid clouds. It can also produce your own datacenter into a private cloud and allow you to extend the functionality to many other organizations. Eucalyptus provides APIs to be used with the web services to cope up with the demand of resources used in the private clouds.

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Q:

What do you understand by MapReduce?

Answer

MapReduce is a software framework that was created by Google. It`s prime focus was to aid in distributed computing, specifically large sets of data on a group of many computers. The frameworks took its inspiration from the map and reduce functions from functional programming.

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Q:

What are the three cost factors involves in cloud data center?

Answer

Cloud data center doesn’t require experts to operate it, but it requires skilled people to see the maintenance, maintain the workloads and to keep the track of the traffic. The labor cost is 6% of the total cost to operate the cloud data center. Power distribution and cooling of the datacenter cost 20% of the total cost. Computing cost is at the end and is the highest as it is where lots of resources and installation has to be done. It costs the maximum left percentage.

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Q:

How to upload files in Amazon S3?

Answer

Amazon S3 provides uploading of large files and retrieve small offsets for end-to-end transfer data rates. The large file gets stored into small files that are smaller in size. Amazon S3 stores multiple of files together in a bundle or in a compressed form, For example in .gzip or .gz format and then convert them into Amazon S3 objects. The files get uploaded on the Amazon server by the use of FTP or another protocol and then retrieved through the HTTP GET request. The request includes the defined parameters like URL, offset (byte-range) and size (length).

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Q:

What is the use of multi-threaded fetching in Amazon S3?

Answer

- Multi-threading fetching in Amazon S3 is used to fetch the objects concurrently using the multiple threads and map the task so that fetching can be made simpler. 


- It is not a good practice to increase the threading for a particular object as every node on the server has some bandwidth constraints. 


- It provides user the ease with which they can upload the files and upload the threads in parallel. 


- It provides high speed of data transfer and easy maintenance of the sever as well.

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Q:

How does fault tolerance work in mapreduce?

Answer

In a mapreduce job the master pings each worker periodically. In case a worker does not respond to that system then the system is marked as failed. Even completed tasks are rescheduled because the output was stored in a in a local disk of a worker which failed. Hence mapreduce is able to handle large-scale failures easily by simply restarting a task. The master node always saves itself at checkpoints and in case of any failure it simply restarts from that checkpoint.

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