ICC104 Assessment 2
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School
Torrens University - Melbourne *
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Course
CCF501
Subject
Information Systems
Date
Dec 6, 2023
Type
docx
Pages
10
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Introduction of the case
What was the challenge?
How was the challenge solved?
What were the different service models each utilized?
What are the different deployment models each utilized?
What services of public cloud providers each case study used?
Reflection
Case Study 1:
Introduction of the webpage:
The webpage showcases how XTO Energy, a subsidiary of ExxonMobil,
tackled the challenges of monitoring and optimizing their widely
dispersed field assets in the Permian Basin by digitalizing their
operations using Microsoft Azure IoT technologies and Microsoft
Dynamics 365 . The purpose of the digitalization was to collect and
analyze data from the field assets, gaining insights into well operations
and future drilling possibilities . XTO Energy utilized Azure IoT
technologies, Azure solutions, and Microsoft Dynamics 365 to
electronically collect and analyze data, enabling more efficient access
to data from field assets
[
1
]
. The webpage highlights the integration of
Dynamics 365 and Data Lake for seamless data transfer and
availability, aiding in the analysis of vast quantities of information
[
2
]
.
XTO Energy's holistic approach, leveraging Microsoft, Azure, IoT
technologies, and Dynamics 365, positions them as an innovation
leader in the oil and gas industry
[
3
]
.
Challenge:
The challenge faced by XTO Energy was the monitoring and
optimization of their widely dispersed field assets in the Permian Basin,
which involved manually collecting data from oil wells that were often
spaced many miles apart, and then uploading it for analysis at the
central office .
Solution:
XTO Energy solved this challenge by digitalizing their operations using
Microsoft Azure IoT technologies and Microsoft Dynamics 365. They
electronically collected data from field assets using Azure IoT
technologies and analyzed it using Azure solutions and Dynamics 365,
gaining new insights into well operations and future drilling possibilities
.
Service Models:
XTO Energy utilized Microsoft Azure IoT technologies, Azure solutions,
and Microsoft Dynamics 365 for data collection, analysis, and insights
into well operations
[
1
]
.
Deployment Models:
XTO Energy deployed their digitalization solution using Microsoft Azure
as a base platform, leveraging its capabilities to move data within the
environment and into the hands of their staf
[
2
]
.
Public Cloud Services:
XTO Energy used Microsoft Azure IoT technologies, Azure solutions, and
Microsoft Dynamics 365 for their digitalization solution, leveraging the
services provided by Microsoft
[
1
]
[
2
]
.
Reflection:
The digitalization of XTO Energy's operations using Microsoft Azure IoT
technologies and Dynamics 365 enabled more efficient access to data
from field assets, leading to improved well operations and the ability to
address problems promptly. The integration of Azure services and
Dynamics 365 provided a scalable, secure, and supportable system for
data collection, storage, and analysis
[
1
]
[
2
]
.
Introduction of the Case
ExxonMobil, through its subsidiary XTO Energy, has been digitalizing its
operations in the Permian Basin, a significant oil-producing region. The
company has adopted Microsoft Azure IoT technologies to collect data
electronically and Azure solutions for data storage and analysis. This
digital transformation has enabled XTO Energy to gain new insights into
operational efficiency and future drilling possibilities.
The Challenge
The primary challenge faced by XTO Energy was monitoring and
optimizing a vast number of field assets spread across the Permian Basin.
The traditional methods of data collection and analysis were inefficient
and did not provide the level of insight required for optimal operations and
strategic decision-making.
How the Challenge was Solved
The challenge was addressed by adopting Microsoft Azure IoT
technologies. These technologies enabled electronic data collection from
the field assets. The collected data was then stored and analyzed using
Azure solutions. This approach provided XTO Energy with a more efficient
way of monitoring its assets and gaining insights into operational
efficiency and future drilling possibilities.
Service Models and Deployment
Models Utilized
The service model utilized in this case is Platform as a Service (PaaS).
Microsoft Azure provides a platform that includes infrastructure, runtime
environment, and development tools for developing, testing, and
managing applications.
The deployment model utilized is Public Cloud. Azure is a public cloud
provider, meaning its services are delivered over the internet and
available to anyone who wants to purchase them.
Services of Public Cloud Providers
Used
The specific services of Azure used in this case are Azure IoT technologies
for data collection and Azure solutions for data storage and analysis.
Reflection
This case study demonstrates the potential of cloud technologies in
transforming operations in the oil and gas industry. By adopting Azure IoT
technologies and solutions, XTO Energy was able to overcome the
challenge of monitoring and optimizing a vast number of field assets. This
digital transformation not only improved operational efficiency but also
provided valuable insights for strategic decision-making.
Case Study 2:
Introduction of the Webpage:
Autodesk, a leading provider of 3D design and engineering software,
has developed a unified log analytics solution on AWS to enhance the
user experience and address software problems efficiently .
The previous log solution struggled to handle the increasing volume of
data, hindering quick problem detection .
Autodesk aimed to monitor logging-incident data in real-time and find a
cost-efective logging solution
[
1
]
.
By leveraging Amazon OpenSearch Service and Kibana, the unified
logging solution ofers improved visibility and in-depth data analysis,
enabling faster correlations between logging events and quicker
problem resolution .
Dashboards created using Kibana help identify trends, patterns, and
anomalies for detailed log analysis
[
2
]
.
The logging data is processed through a pipeline, with additional
metrics displayed in standardized dashboards using Amazon
CloudWatch, and interactive log analytics performed using Amazon
Athena and AWS X-Ray
[
3
]
.
Challenge:
The challenge faced by Autodesk was the inability of their previous
application-data log solution to keep up with the growing volume of
data, making it difficult to detect software problems quickly.
[
1
]
Solution:
Autodesk built a unified log analytics solution on Amazon Web Services
(AWS) using Amazon OpenSearch Service and Kibana. This solution
provided better visibility into data logs in real-time and enabled faster
detection and resolution of software problems.
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Service Models:
The unified log analytics solution utilized Amazon OpenSearch Service,
an open-source search and analytics engine, for data analysis and
visualization.
[
2
]
Deployment Models:
The solution was deployed on AWS, leveraging the cloud infrastructure
provided by the platform.
[
1
][
2
]
Public Cloud Provider Services:
Autodesk utilized various services from Amazon Web Services (AWS) for
their unified log analytics solution, including Amazon OpenSearch
Service, Kibana, Amazon CloudWatch, Amazon Athena, and AWS X-Ray.
[
1
][
2
]
Reflection:
By implementing the unified log analytics solution on AWS, Autodesk
was able to overcome the challenges of handling large volumes of data
and improve their ability to monitor and fix software problems quickly.
The solution provided real-time visibility into log data, enabling better
correlations between logging events and faster problem resolution.
Additionally, the use of AWS services allowed Autodesk to achieve cost-
efectiveness and streamline log data management.
[
1
][
2
]
Case Study 2: Autodesk Builds
Unified Log Analytics Solution on
AWS
Introduction
Autodesk, a leading provider of 3D design and engineering software,
aimed to ensure its millions of global users have the best experience
running their software. To achieve this, Autodesk needed to monitor and
fix software problems as quickly as possible.
Challenge
The main challenge Autodesk faced was that their previous application-
data log solution struggled to keep up with the growing volume of data
needing to be analyzed and stored. This hindered their ability to quickly
identify and resolve software issues, impacting the user experience.
Solution
Autodesk turned to Amazon Web Services (AWS) to build a unified log
analytics solution. This solution enabled Autodesk to efficiently analyze
and store large volumes of data, thereby improving their ability to monitor
and fix software problems promptly.
Service Model Utilized
Autodesk utilized the
Platform as a Service (PaaS)
model. This model
allowed Autodesk to focus on the development and management of their
software, while AWS handled the underlying infrastructure.
Deployment Model Utilized
Autodesk utilized the
Public Cloud
deployment model. This model
provided Autodesk with the scalability needed to handle large volumes of
data and the flexibility to access their applications from anywhere.
Public Cloud Services Used
Autodesk used several AWS services, including:
Amazon Kinesis
: for real-time data streaming and analytics.
Amazon S3
: for scalable and secure data storage.
Amazon EMR
: for big data processing.
Reflection
By leveraging AWS's robust and scalable services, Autodesk was able to
build a unified log analytics solution that could handle their growing data
needs. This not only improved their ability to monitor and fix software
problems quickly but also enhanced the overall user experience.
Case Study 3:
Introduction of the page:
The page provides information about Coca-Cola's International Bottling
Investments Group (BIG) and its implementation of a new model that
optimizes service requirements for cloud deployment, resulting in
increased efficiencies and revenues
[
1
]
[
2
]
.
BIG aimed to reduce the complexity, rigidity, and costs of running
mission-critical applications common to each bottler, leading them to
transition to cloud computing in 2012
[
3
]
.
In 2016, BIG began transitioning to the Virtustream Enterprise Cloud,
which eliminated the need for complex pricing options and
negotiations, and dynamically optimized service levels for cloud
deployment
[
4
]
.
Note: The provided sources do not directly mention a "page" or provide a
specific URL. The information is derived from the context of the sources.
Challenge:
The challenge for Coca-Cola's International Bottling Investments Group
(BIG) was to address the unique complexities and requirements of a
diverse group of bottlers with an efficient infrastructure and
standardized processes .
Solution:
BIG began its foray into cloud computing in 2012 to reduce the
complexity, rigidity, and costs of running mission-critical applications
common to each bottler
[
1
]
.
In 2016, BIG transitioned to the Virtustream Enterprise Cloud, which
dynamically optimized service requirements for cloud deployment,
eliminating the need for complex pricing options and negotiations
[
2
]
.
Service Models:
The sources do not explicitly mention the diferent service models
utilized by each bottler within BIG.
Deployment Models:
The sources do not explicitly mention the diferent deployment models
utilized by each bottler within BIG.
Public Cloud Providers:
The sources do not mention the specific public cloud providers used by
each case study within BIG.
Reflection:
The provided sources do not provide information regarding the
reflection on the implementation or outcomes of the cloud deployment
optimization by BIG.
Case Study 3: 'Pay by the Drink'
Flexibility Creates Major
Efficiencies and Revenue for
Coca-Cola's International Bottling
Investments Group (BIG)
Introduction
The International Bottling Investments Group (BIG) of Coca-Cola aimed to
drive efficiencies, higher revenue, greater transparency, and higher
standards across all its bottlers. However, each bottler within BIG faced
unique challenges inherent to their business and markets. The full case
study can be found
here
.
Challenge
The main challenge was addressing the unique complexities and
requirements of a very diverse group of bottlers with efficient
infrastructure and standardized processes.
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Solution
The challenge was solved by implementing a 'Pay by the Drink' model.
This model provided the flexibility needed to address the unique needs of
each bottler while maintaining efficiency and standardization.
Service Models Utilized
The service model utilized in this case was Infrastructure as a Service
(IaaS). This model allowed BIG to outsource the equipment used to
support operations, including storage, hardware, servers, and networking
components.
Deployment Models Utilized
The deployment model utilized was a hybrid cloud model. This model
combines a private cloud with one or more public cloud services, with
proprietary software enabling communication between each distinct
service.
Public Cloud Services Used
The public cloud services used in this case study were provided by
Virtustream, a Dell Technologies business. Virtustream's enterprise-class
cloud service and software solutions were used to manage mission-critical
applications.
Reflection
This case study demonstrates the power of flexible and scalable cloud
solutions in addressing unique business challenges. By leveraging a 'Pay
by the Drink' model, BIG was able to drive major efficiencies and increase
revenue across its diverse group of bottlers.
Case Study 4:
Introduction of the webpage:
The webpage features a technology startup called Rocketbots that aims
to improve the relationship between businesses and their customers by
providing personalized communication experiences.
Rocketbots is a software solution built on the cloud, and they needed
reliable availability to ofer their high-end solution to customers in
Southeast Asia.
Alibaba Cloud, a cloud computing service provider, played a crucial role
in supporting Rocketbots by optimizing their solution and providing the
necessary availability.
[
1
]
Rocketbots leveraged over 11 diferent services from Alibaba Cloud,
which resulted in increased performance and decreased business costs.
Alibaba Cloud's CDN (Content Delivery Network) helped speed up the
loading of front-end and static resource files, enhancing user
experience.
Alibaba Cloud also supported other businesses, such as Emperor Group
and HelloToby, in various industries, including financial services,
property, entertainment, and local services matching platforms.
[
2
]
Note: The provided sources do not directly mention the webpage, but they
provide information about Rocketbots and Alibaba Cloud, which are relevant
to the webpage.
Challenge:
Rocketbots, as a cloud-based software solution, needed availability to
provide their high-end solution to customers in Southeast Asia.
However, finding providers that could ofer the required availability in
the region proved difficult.
[
1
]
Solution:
Rocketbots solved the challenge by leveraging Alibaba Cloud's data
centers throughout Asia. This allowed them to give their customers an
optimized solution that was available when needed.
Service Models:
Rocketbots utilized Alibaba Cloud's SLB (Server Load Balancer) to
distribute traffic to diferent servers throughout Asia. They also used
Alibaba Cloud's API Gateway to access various chat platforms for
communication. Additionally, they leveraged Alibaba Cloud's Function
Compute, which enabled them to run code without the need for a pre-
existing server.
Deployment Models:
Rocketbots deployed their solution on Alibaba Cloud's elastic and
secure virtual cloud servers, which ofered an online computing service.
They also utilized Alibaba Cloud's fully hosted and serverless running
environment, which eliminated the need for infrastructure
management.
[
2
]
Services of Public Cloud Providers:
Rocketbots used over 11 diferent services from Alibaba Cloud,
including SLB, API Gateway, and Function Compute. They also
benefited from Alibaba Cloud's CDN (Content Delivery Network) to
speed up request response times and enhance user experience.
[
3
]
Reflection:
By migrating to Alibaba Cloud, Rocketbots achieved a 25% increase in
performance through optimized instances and reduced costs by 65%
due to the absence of internal bandwidth charges. This demonstrates
the efectiveness of leveraging Alibaba Cloud's services for their
business needs.
Introduction
Rocketbots is a software solution built on the cloud, aiming to provide
high-end solutions to its customers at any time. The company faced
challenges in ensuring system availability in Southeast Asia due to
limitations with other providers.
Challenge
The primary challenge for Rocketbots was to ensure the availability of
their cloud-based software solution in Southeast Asia. The region's
infrastructure and network limitations made it difficult for other providers
to guarantee the level of availability Rocketbots required for their
operations.
Solution
Rocketbots solved this challenge by leveraging Alibaba Cloud's extensive
network of data centers throughout Asia. This allowed them to provide an
optimized solution that was not only efficient but also available when their
customers needed it.
Service Model
Rocketbots utilized the
Infrastructure as a Service (IaaS)
model. This
model allowed them to outsource the infrastructure required to support
their operations, including storage, servers, and networking components.
Deployment Model
The deployment model used by Rocketbots is the
Public Cloud
model.
This model allowed them to leverage the extensive infrastructure of
Alibaba Cloud, ensuring their services were available across Southeast
Asia.
Public Cloud Services
Rocketbots utilized various services provided by Alibaba Cloud. While the
specific services are not mentioned in the case study, they likely included
Alibaba's data storage, computing, and networking services.
Reflection
This case study demonstrates the importance of choosing the right cloud
provider and service model. By leveraging Alibaba Cloud's extensive
infrastructure, Rocketbots was able to overcome regional limitations and
ensure the availability of their services. This not only improved their
service delivery but also optimized their operational costs.
https://www.zendesk.com/au/blog/what-is-paas/#georedirect
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