Migrating to the Cloud: Suggestions, Steps and Comparison of AWS, Azure and Google Cloud Services

This document discusses the cloud service and deployment models, steps to mitigate airline flight booking sub-system to the cloud, and comparison of AWS, Azure and Google Cloud Services. It also includes references for further reading.

Running head: MIGRATING TO THE CLOUD
Migrating to the cloud
Name of the Student:
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1MIGRATING TO THE CLOUD
Table of Contents
1. Suggestions on the cloud service and deployment models..........................................................2
2. Steps expect to be taken to mitigate the airline flight booking sub-system to the cloud.............3
3. Comparison of cloud related commercial offerings of Amazon AWS, Microsoft Azure and
Google Cloud Services....................................................................................................................4
References........................................................................................................................................7

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1. Suggestions on the cloud service and deployment models
The cloud service model which is suggested to use in the private low-budget airline is
IaaS (Infrastructure as a Service). This cloud provider provides the airline industry with entire
range of the computing infrastructures like storage, server, networking hardware, maintenance as
well as support. Amazon Web Services is used as leading IaaS cloud service providers. AWS
provides the airlines with opportunity to leverage benefits of cloud for creation off application,
deployment as well as management (Narula and Jain 2015). In order to improve reliability and
flexibility, the company decided to improve website environment plus internal business
applications to cloud. Using AWS, the airline can support extreme traffic loads and eliminate
risk in terms of the system outage (Iorga et al. 2018). The airline can improve its data analytics
capabilities by means of Amazon Redshift.
The cloud deployment model used in airline industry is private cloud. This deployment
model has advantages of individual development, storage and network components those are
customizable and higher control in the corporate information. This model provides higher
security and privacy in the business environment (Ramachandran and Chang 2016). As the data
centers architectures are reside into the firewall, and then it provides to enhance security. The
airline runs the workloads on private based, the third party can manage and the server can host
externally and on premises of the organization.
The airline industry develops and deploys interoperable IT management standards for
virtualisation and other aspects of cloud operations (Singh and Sidhu 2017). By means of this
standard, the customers can able to select cloud technology that will enable that on-demand

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flexibility they are required. It allows vendors of IT technology to be focused on functionality
and performance improvements rather than focused on the protocol development.
2. Steps expect to be taken to mitigate the airline flight booking sub-system to
the cloud
Assessment of the workloads and alignment of the proper cloud type (private) and
delivery model (infrastructure as a service) is a step in cloud migration strategy which
determines success of the strategy. When the workload assessment is not completed, then it can
mitigate workload to the cloud which would prove to be hassle free which can end the project
failures as well as unsatisfied customers (Persico et al. 2015). Following are the steps which are
to be taken to mitigate airline flight booking sub-system to the cloud such as:
I. Performing workloads classification and determination of the requirements of
airline flight booking system such as test development and production
II. Understanding the data flows throughout the enterprise and related to core
services and business processes to document the business impacts of transferring
application to the cloud (Nawaz et al. 2016)
III. Assessment of application architecture to determine the impact of application
migration to the cloud
IV. Considering the technical characteristics of the airline booking system such as
integrations, dependencies, integration, customization and support
(Ramachandran and Chang 2016).
V. Understanding security concerns of the customers and regulatory compliance
needs

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VI. Ensuring that the plan is used to migrate application to the cloud is location
independent
VII. Evaluating support resources needed for workloads and operational migration cost
help to assess benefits of the application to cloud (Iorga et al. 2018).
3. Comparison of cloud related commercial offerings of Amazon AWS,
Microsoft Azure and Google Cloud Services
Factors Amazon AWS Microsoft Azure Google Cloud Services
Functionality Provides compute
power, storage of
database moreover
functionality to assist
the trade scale and
development (Singh
and Sidhu 2017).
Function as service to
eliminate infrastructure
considerations for the
users (Persico et al.
2015)
Big data processing and
Google offers cloud
machine learning engine
to direct services which
will enable to build and
train the machine learning
(Nawaz et al. 2016).
Performance
scalability
AWS auto scaling Azure Autoscaling and
Azure app service scale
capability (PaaS)
Auto Scaling
Degree of
standardizatio
n
Key management Data storage _
Ease of use Transaction tracking
to the blockchain
Easy to manage the
platform
Provides the developer
with comprehensive

5MIGRATING TO THE CLOUD
solutions with focused on
ease of use plus speed
Cost $0.0125 for Amazon
S3 standard
$0.0152 $0.01
Virtual servers Elastic compute cloud
(EC2) instances and
Amazon lightsail
Azure virtual machines Google virtual servers
Disaster
recovery
ASW disaster
recovery
Sire recovery _
Cloud virtual
networking
Virtual private cloud Virtual network Google virtual private
cloud
Virtualisation QuickSight Power BI Google data studio (Beta)
Among the mentioned three project vendors, AWS is preferred as best for migrating of
the legacy system of airline to the cloud based scheme. It is the biggest strength of Amazon to be
dominance of public cloud market. It is the market leader in the cloud IaaS. It manages the
project cost effectively when there is running of higher volume of workloads on the airline
services (Iorga et al. 2018). Each of the platforms of AWS has its own features as well as pricing
which could match with the airline ticket booking system. As compared to other two cloud
service providers, AWS allows to gain easier access to the computing power, storage of data as
well as other functions related to application developers. It offers free tiers of services for the
startups plus individuals.

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The weaknesses of AWS are related to the cost. It lowers the prices so that the airline
finds it critical to understand the cost structure of the industry. Amazon passes profits of the cost
investments on the clients in appearance of lesser prices because it can manage as well as build
the global infrastructure at the scale. AWS consumes as much storage and computing power as it
is required (Narula and Jain 2015). No such upfront investment and minimum expenditures are
required in this case. It is easier to use and the users are not required about the servers and
security. This company uses end-to-end approaches for securing and hardening the
infrastructure, included physical as well as software related measures.
ASW has higher secured infrastructure both physically as well as over the internet. The
data centres are being staffed 24*7 and access is being authorized strictly on the privileged basis
(Ramachandran and Chang 2015). It has ability to build in the firewall policies on or after the
public to the private and in connecting to manage access to the business cases.

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References
Iorga, M., Feldman, L., Barton, R., Martin, M.J., Goren, N.S. and Mahmoudi, C., 2018. Fog
computing conceptual model(No. Special Publication (NIST SP)-500-325).
Narula, S. and Jain, A., 2015, February. Cloud computing security: Amazon web service.
In 2015 Fifth International Conference on Advanced Computing & Communication
Technologies (pp. 501-505). IEEE.
Nawaz, H., Juve, G., Da Silva, R.F. and Deelman, E., 2016, May. Performance analysis of an i/o-
intensive workflow executing on google cloud and amazon web services. In 2016 IEEE
International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 535-
544). IEEE.
Persico, V., Marchetta, P., Botta, A. and Pescapé, A., 2015, December. On network throughput
variability in microsoft azure cloud. In 2015 IEEE Global Communications Conference
(GLOBECOM) (pp. 1-6). IEEE.
Ramachandran, M. and Chang, V., 2016. Towards performance evaluation of cloud service
providers for cloud data security. International Journal of Information Management, 36(4),
pp.618-625.
Singh, S. and Sidhu, J., 2017. Compliance-based multi-dimensional trust evaluation system for
determining trustworthiness of cloud service providers. Future Generation Computer
Systems, 67, pp.109-132.