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Managing information systems: Read the following paper and answer the questions below - Assignment Example

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On the other hand, Platform as a Service abbreviated as PaaS is a model which has been proven for running applications with the…
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Managing information systems: Read the following paper and answer the questions below
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Question One Infrastructure as a Service abbreviated as IaaS is a provision model whereby an organization outsources the equipment that enhances operations. On the other hand, Platform as a Service abbreviated as PaaS is a model which has been proven for running applications with the exception of maintaining the software and hardware infrastructure at an organization.
Software as a Service abbreviated as SaaS is a software model for distribution in which a vendor or service provider hosts applications and make them available to customers over a network.
Question Two
I agree with the statement since the elasticity of resources with no payments made for premium for large scale, has never occurred in IT history. Again, developers are not concerned by over provisioning for a service which does not meet their predictions through its popularity, thus wasting resources, or under provisioning for a service that increases its popularity, thus missing revenue and customers.
Question Three
There are three cases that give utility computing an upper hand over convectional hosting. Firstly, is the case when service demand changes with time. For instance, data center provisioned for the peak load is supposed to sustain a few days in a month leads to underutilization sometimes. Instead, cloud computing allows an organization pay for computing resources by the hour, leading to saving the cost even if the hourly rate for hiring a machine is higher than the one to own a machine. Secondly, the case when demand is not known in advance.
For instance, a Web startup needs to back up a spike in, demand when people gets to know, followed by a potential reduction once some visitors turn away from it. Finally, organizations that perform batch analytics can make use of cost associativity of cloud computing to do away with computations quickly: using 1000 EC2 machines for a single hour totals to the same amount making us of one machine for 1000 hours (Gattiker).
Question Four
1. Business continuity and service Availability
Organizations are concerned whether the availability of utility computing services will be sufficient, this leads to cloud computing wary in some. Ironically, high standards have been set by existing SaaS products in this regard. Google Search are highly available and this ensures business continuity.
2. Data Lock-In
Difficulties of data extraction from the cloud is a major concern and is preventing some organizations embracing cloud computing. Customer lock-in attracts providers of cloud computing, but their users are subject to increase in price, providers abandoning the business, or even to reliability problems.
3. Data Confidentiality
Cloud users are faced security threats from everywhere in the cloud. Majority security issues associated clouds protections from outside threats are similar to the ones facing large data centers. Despite numerous organizations outsourcing payroll and majority of the companies making use of external email services to keep sensitive data, security is a major issue.
4. Data Transfer Bottlenecks
Applications are becoming data-intensive day in day out. Cloud providers and cloud users have to figure out the implications of traffic and placement at each level if they aim to reduce costs.
5. Performance Unpredictability
We have in mind that several virtual machines can share main memory and CPUs in cloud computing, but that disk I/O and network sharing is a problem to share. Scheduling of virtual machines for certain classes of batch processing programs, specifically quality performance is also unpredictability obstacle.
6. Scalable Storage
It is not clear to apply the properties which have combinations that give cloud computing its appeal, to persistent storage.
7. Bugs in Large-Scale Distributed Systems
Errors removal in large-scale distributed systems means a challenge to cloud computing. These bugs cannot be reproduced in configurations which are minute, so debugging is supposed to take place at scale in data centers production.
8. Scaling Quickly
Pay-as-you-go is applicable to network bandwidth and to storage, both of which counts the usage of bytes. Google AppEngine scales in response to load decreases and increases, and users are charged by the cycles that have been used.
9. Reputation Fate Sharing
This is where one customer’s bad behavior affects the behaviors of others customers using the same cloud. For instance, in the case where EC2 IP addresses are black-listed by spam-prevention services may lead to obstruction of which applications can be hosted.
10. Software Licensing
Present software licenses restrict the computers on the software which to run.
Work cited
Gattiker, Urs E. The Information Security Dictionary. Boston: Kluwer Academic Publishers, 2004. Print. Read More
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