AddToThisReport.docx

Final Report To Executive Managers
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CCA 625
University of Maryland Global Campus
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Table of Contents
Executive summary 1
Lab results (4–8 pages) 1
Lessons Learned from The Labs 13
Feasibility of cloud environment for BallotOnline web services deployment 15

2

Building An AWS Migration Environment and Configuring the Web Services

Executive summary

Compute, databases, storage, analytics, mobile, networking, developer tools, management tools, IoT, security, as well as corporate applications are all available through Amazon Web Services (Wang et al., 2017). These services enable BallotOnline to move more quickly, save money on IT, and grow. Web and mobile apps, game development, data processing and warehousing, storage, archiving, and many more workloads are all powered by AWS, which is trusted by the world’s largest companies and the hottest start-ups.
The relational database transfer is supposed to be met with skepticism by the web development team. I have a task to create a proof-of-concept application to test it. During the proof of concept, I have to learn how to use the AWS Management Console to start, stop, and configure Amazon EC2 instances and Amazon RDS DB Instances, store and retrieve Amazon S3 items, and set up elastic load balancers (Zulu et al., 2018). Also, I might learn a lot about AWS and realized that they had complete control over the environment, which am sure will make me feel much more secure about taking the next step.
The standard “mysqlimport” tool is used to migrate relational database files to Amazon RDS instances. I will put up a DB Instance in a single Availability Zone for the test environment, and a multi-AZ deployment for the production environment to enhance availability (Cao et al., 2017). My main goal is to properly test and migrate all data to a database instance, as well as get performance measurements using Amazon CloudWatch and define backup retention settings. I have also to construct migration scripts to automate the process and raise awareness inside the company by hosting a “brownbag” session.

Lab results (4–8 pages)

Lab 1 Report

Load Balancer DNS Name:
internal-CCA625-LB-65451032.us-east-1.elb.amazonaws.com

Summary of the Lab

Before beginning this lab, I ensured that the VPC and EC2 instances are correctly configured. In addition, I checked that the security groups for the instances made allow http which is on port 80. Later I installed the Apache web server on every instance filling respective DNS names (Joshi & Shah, 2019).
Incoming traffic is distributed over many targets in one or more Availability Zones, such as EC2 instances, containers, and IP addresses, using Elastic Load Balancing. It monitors the health of the targets it has recorded and only delivers traffic to those who are in excellent form. One can scale the load balancer as the incoming traffic varies using Elastic Load Balancing. It can automatically scale to the vast majority of workloads. The Load balancer and the instances are created as discussed in the steps summarized below;
Step 1: I decided on a load balancer.
Step 2: I determined the parameters of my load balancer.
Step 3: I created a VPC and added security groups to my load balancer.
Step 4: For my EC2 instances, I set up health checks.
Step 5: I used my load balancer to register EC2 instances.
Step 6: As an optional step, I labeled my load balancer.
Step 7: I built a load balancer and tested it.
Step 8: Remove the load balancer from your system, which was optional too.

Lab 2 Report

To initiate the SSH session, I entered my EC2 login, DNS information, and keypair into putty. The sudo yum update command was then run. I installed NGINX on the instance once that was finished. After receiving a complete, I knew it was put properly. The next step was to copy files from Ballotonline.biz, which included a ZIP file that had to be unzipped. I created a directory for it and then copied the website files from the traditional web server into it. By executing another command in the session, I was able to alter the permissions on the website files to make them less restrictive.
In the first case, I checked to see whether I could visit the website, and the results reveal that I was able to do so (Wang et al., 2017). For my second instance, I repeated all of the procedures as seen in the screenshots below. The second instance was also successful, demonstrating that the website could access the data.

Lab 3 Report

I anticipated to see the statistics to every service I wish to watch or observe before I launch CloudWatch. This experiment will teach me how to interpret metrics more effectively and have a better understanding of how various services utilize more data, resulting in higher or lower AWS costs (Zulu et al., 2018). With this hands-on experience, I feel this lab will aid me in better understanding AWS and the administration console. When I was developing a dashboard for Cloudwatch, I discovered how simple the AWS interface is, especially when you use it frequently. These labs have been extremely useful in making the management console more user-friendly. The labs, in my opinion, also aid in learning how AWS instances operate and how to modify them using code. The statistics are summarized as shown in the pictures below;

Lessons Learned from The Labs

Based on the lab practical the lessons learnt include the following as discussed below;
i Data Migration. Following the proof of concept, I decided to move all of the application’s static files (such as static HTML content) to an Amazon S3 bucket, create an Amazon S3 CloudFront distribution, and change web page references so that end-users get content directly from Amazon S3 and Amazon CloudFront. Using a few scripts and the AWS SDK for Java libraries, they were able to move all data from tape drives to Amazon S3.
ii Application Migration. Throughout the application migration process, I created both small and large instances3 for its web and tomcat servers. They created AMIs (Amazon Machine Images, or “golden” system images) for each server type. During the starting process, AMIs were built to boot directly from an EBS volume and download the most recent WAR file binaries from the source code repository (Joshi & Shah, 2019). In their development and deployment procedures, I moved the endpoint to the cloud. Security groups were developed to segregate web servers from application and database servers. Testing (performance, functionality and so on) was done to ensure that the systems worked as they should and that each component’s exit criteria were met.
iii Leveraging the Cloud. BallotOnline was looking forward to the day when they could use some of AWS’ sophisticated capabilities when the production site was released. I automated several steps so that the server could be quickly “connected” to the topology once it was launched (Shirvani & Gorji, 2020). I then built an Auto Scaling group of web servers, which allowed me to automatically supply more capacity when certain resources reached a given level (Apache web servers CPU utilization above 70 percent for 15 minutes). Later, I put some time and effort into simplifying their development and testing procedures so that cloning testing setups would be simple. I acquired a lot of expertise with AWS resources and spent time learning how to use several Availability Zones to increase availability even further.
iv Optimization. I was able to examine their use habits throughout the optimization process and discovered that switching to Reserved Instances would save them 28%. Four Reserved Instances were acquired for me (2 for web servers and the other 2 for tomcat servers). Additional scripts were written to operate their web application in three separate “modes”: weekend, weekday, and promotion mode (Zulu et al., 2018). These settings specified the bare minimum of servers that may be used. I also incorporated Amazon CloudWatch into their current dashboards so that I can keep track of the system metrics of each cloud instance in their fleet.
v Technical Skills. The technical skills I learned via AWS setup and settings are as follows: Operating system essentials, virtualization fundamentals, networking core principles, as well as any programming language concepts, among many others.
vi Elastic Load Balancing Services. To increase the availability and scalability of your applications, Elastic Load Balancing works with the following services:
a. Amazon EC2. Virtual servers in the cloud that execute your apps. One may direct traffic to their EC2 instances using the load balancer.
b. Amazon EC2 Auto Scaling. Makes sure that the appropriate number of instances are operating, even if one of them fails. As the demand on the instances varies, Amazon EC2 Auto Scaling allows you to automatically raise or reduce the number of instances.
c. AWS Certificate Manager. One can provide certificates given by ACM while creating an HTTPS listener. Certificates are used by the load balancer to stop connections and decode user request.
d. Amazon CloudWatch. Allows one to keep an eye on the load balancer as well as take action as necessary.
e. Amazon ECS. Allows one to run, terminate, as well as administer the Docker containers on an EC2 cluster. One may direct traffic to your containers using your load balancer.
f. AWS Global Accelerator. Improves the availability as well as performance of the application. Use an accelerator to distribute traffic over several load balancers in one or more AWS Regions.

Feasibility of cloud environment for BallotOnline web services deployment

The AWS cloud is a collection of all network-connected servers on which its service platform is hosted, and we sarcastically refer to it as “the cloud.” Some of the following features have been made possible for a group of computers for the BallotOnline Organization:
BallotOnline was able to create a new online application as well as migrate an existing application to the AWS. The team was able to save 25% on operating expenditures while also freeing up physical infrastructure for additional activities. A phased-driven strategy allowed the development team to address all of the financial, technological, and social-political concerns. Investing in a proof of concept was a smart move. The resultant architecture was not only flexible and simple to maintain, but it was also elastic as well as scalable.
The company can combine the computational power of numerous processors and storage devices, as well as the network connection of those components, into a single, contiguous unit, thanks to virtualization (the ability for software to behave like hardware). In other words, they must pool their resources so that they may be seen as a single large computer rather than a collection of smaller computers (Cao et al., 2017).
The workloads which operate on the organization’s pool of resources are not really tied to any particular physical location. That is, their storage, databases, as well as processes, in whatever form they are stored, are fully portable over the cloud (Wang et al., 2017). A self-service portal must be able to setup the resource pools that operate these workloads. By buying virtual infrastructure (pooled resources for processing and other activities) over the Web, any customer who needs to execute a process on a server can do so.
The capacity of BallotOnline to employ cloud services has become a critical component of their efficiency and competitiveness. On the other side, lack of access would prevent the SME sector from reaching its full potential. In general, cloud computing services provide an open business platform for BallotOnline by providing access to time and distance independent sources of data (Shirvani & Gorji, 2020). The outcomes of an organization’s investment in cutting-edge technology, such as AWS Cloud Computing in this case, provide additional insight on adoption patterns. According to the PEST study, the growing AWS Cloud Computing technologies have the potential to multiply the company’s productivity, efficiency, and profitability, as well as those of other small businesses.
For this example, the BallotOnline company, the AWS Cloud model is supplied to end users as targeted pay-per-use services, with providers offering assurances through tailored Service Level Agreements (SLAs). This turns computer power into a public utility, similar to water, electricity, or gas, and represents a significant paradigm shift for the IT sector and, perhaps, society as a whole.
While AWS currently hosts virtual machine-based Web sites, its contemporary business model is focused on offering functionality to people and companies over the Internet (Zulu et al., 2018). The emphasis here is on “the Web” in its technical sense: the servers which transact and exchange data packets using the HTTP and HTTPS protocols. The Web is frequently mentioned as the location where ZDNet is published. Modern software, on the other hand, connects with its users over the Internet. This concept is well-executed by the BallotOnline organization.
BallotOnline provides the best options to those in charge of extending and integrating SaaS applications by continually reviewing needs. Instead of adopting a PaaS technology that may have a cost per solution, it obtains a higher return from an existing SaaS service by moving select applications and integrations to it.
According to BallotOnline, Cloud-based technology offers inexpensive start-up costs, low cost for occasional usage, simplicity of management, scalability, device and location independence, and rapid innovation. It is critical to establish a cloud management tooling strategy by choosing and implementing the most effective cloud management solutions (Joshi & Shah, 2019). A well-defined, methodical method to solidifying requirements and matching tools to these needs was necessary to develop a cohesive cloud management tooling strategy. This was done in to reduce the number of tools required while still meeting all management requirements.
However, even with a single cloud provider, cloud computing governance is difficult, and it becomes increasingly more difficult when companies go to multicloud. This is not a one-of-a-kind situation for BallotOnline. Cloud providers, such as Amazon Web Services (AWS) in this example, provide on-demand, self-service resources with limitless capacity, making it impossible for businesses to see and monitor what is being used.

References

Cao, D. G., An, B., Shi, P. C., & Wang, H. M. (2017). Providing virtual cloud for special purposes on demand in jointcloud computing environment. Journal of Computer Science and Technology, 32(2), 211-218.
Joshi, N., & Shah, S. (2019). A comprehensive survey of services provided by prevalent cloud computing environments. Smart intelligent computing and applications, 413-424.
Shirvani, M. H., & Gorji, A. B. (2020). Optimisation of automatic web services composition using genetic algorithm. International Journal of Cloud Computing, 9(4), 397-411.
Wang, H., Shi, P., & Zhang, Y. (2017, June). Jointcloud: A cross-cloud cooperation architecture for integrated internet service customization. In 2017 IEEE 37th international conference on distributed computing systems (ICDCS) (pp. 1846-1855). IEEE.
Zulu, L. L., Ogudo, K. A., & Umenne, P. O. (2018, December). Emulating software defined network using mininet and opendaylight controller hosted on amazon web services cloud platform to demonstrate a realistic programmable network. In 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) (pp. 1-7). IEEE.