In the IT sector, cloud computing has become one of the
most pervasive ideas. Its success is attributed to its on-demand
services rather than the deployment of a full infrastructure,
which would entail extra expenses for things like hiring staff,
paying for equipment, and so forth. The National Institute of
Standards and Technology (NIST) classifies whether or not a
service is a cloud service according to the following
characteristics [1]: broad network access, rapid elasticity,
measured service, on demand self-service and resource
pooling. The cloud services are available in three different
models [2]:
• Infrastructure as a service: the customer is
provisioned with compute, storage and networking
in order to manage operating systems (OS),
middleware, runtime, data and applications.
• Platform as a service : in this model, the customer is
additionally provisioned with OS, middleware and
runtime for managing data and applications. This
model is similar to the concepts of serverless
computing
• Software as a service: compared to the previous
models, SaaS delivers applications that are managed
by a third-party provider directly to the customer.
With increasing competition in software market,
organizations pay significant attention and allocate resources
to develop and deliver high-quality software at much
accelerated pace [3]. Some of the techniques targeted at
assisting organisations in speeding up the development and
delivery of software features without sacrificing quality
include continuous integration (CI), continuous delivery
(CDE), and continuous deployment (CD), referred to as
continuous practices for the purposes of this study [4].
Whereas CDE and CD focus on the capacity to swiftly and
reliably distribute value to consumers by introducing as much
automation support as feasible, CI promotes integrating work-
in-progress several times a day.[5], [6]. Continuous practices
are expected to provide several benefits such as: (1) getting
more and quick feedback from the software development
process and customers; (2) having frequent and reliable
releases, which lead to improved customer satisfaction and
product quality; (3) through CD, the connection between
development and operations teams is strengthened and manual
tasks can be eliminated [7], [8]. A growing number of
industrial cases indicate that the continuous practices are
making inroad in software development industrial practices
across various domains and sizes of organizations [7], [9],
[10]. The main purpose of this project is to automate the
development process of a project that includes the phrases of
building the code, testing and deployment of the project which
need more time when doing these tasks manually. Eight builds
are involved which would take a huge time if done manually.
JetBrains TeamCity is a user-friendly and a powerful
Continuous Integration and Continuous Deployment server
that works out of the box [11]. It can run parallel builds
simultaneously on different environments and platforms.
Some of the main advantages of TeamCity are optimizing the
code integration, reviewing on-the-fly test results reporting,
using intelligent tests re-ordering, running code coverage,
finding duplicates, customizing statistics on build duration,
code quality, success rate and custom metrics. TeamCity
contains an integrated builds antifactory repository.
Bamboo Atlassian is a CI tool which is suitable for
multiple programming languages and other popular
technologies like Docker, Amazon S3 and AWS Code
Deploy. The user can choose from a big variety of tasks for
both builds and deployment projects. Bamboo represents a CI
server which can be connected with other Atlassian products
and can be used to automate the release for a software
application. According to [12], Bamboo uses the concept of a
Deploying Application Using CI/CD Tools on AWS
ABDULLAH, MOHAMMAD ZEESHAN, ANSARI ABDURRAHMAN,
IMRAN AKHTAR, SALMAN BAIG
Bachelor of Computer Engineering, Maulana Mukhtar Ahmad Nadvi
Technical Campus Malegaon, INDIA
Abstract: — These days, most businesses turn to cloud computing as their go-to answer. Due to this, DevOps methodologies in
which developers work have been introduced. together with network engineers to guarantee their applications are deployed quickly
and reliably. Continuous Integration and Delivery (CI/CD) pipelines, which automate the build process on specialized equipment,
have been shown to yield a number of benefits, such as quicker release cycles, higher productivity, and early fault discovery. This
work describes an automated pipeline from scratch, beginning with the detection of modifications in the source code of web
applications, building new. This new version will be hosted using resources in the EC2, and the application will eventually be
deployed in AWS. The solution uses Jenkins for Continuous Integration and adheres to DevOps best practices. We highlight two
main issues that we encountered: lengthy wait times for builds and releases to be queued and finished.
Key-words: — DevOps, Amazon Web services, Continuous Integration, Continuous Deployment, Continuous delivery, Jenkins.
Received: March 19, 2024. Revised: August 29, 2024. Accepted: September 19, 2024. Published: October 17, 2024.
1. Introduction
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.22
Abdullah, Mohammad Zeeshan,
Ansari Abdurrahman, Imran Akhtar, Salman Baig
E-ISSN: 2769-2507
184
Volume 6, 2024
plan with tasks and jobs in order to configure the actions in the
workflow.
Jenkins is an open-source automation tool written in Java
with different plugins developed for the purpose of continuous
integration [13]. It is widely used for building and testing
software projects continuously, facilitating the integration of
changes in the project and obtaining a new build by
developers. Jenkins integrates with a large number of testing
and deployment technologies (such as Selenium, Kubernetes,
etc.) offering an easy way to configure an environment of
continuous integration or delivery (CI/CD) for almost any
combination of programming languages or repository hosting
services using pipelines. It can work in master-slave
architecture and in this type of architecture a master node can
execute jobs on multiple slaves running on different platforms.
Although Jenkins does not eliminate the need of creation of
scripts for individual steps, it brings a faster and more robust
way to integrate the entire chain of tools for building, testing
and deployment.
Fig. 1. Jenkins Architecture [26]5
An example of continuous integration with a Jenkins
server is presented in Fig. 1. The developers commit changes
to the source code to a source code management (SCM) tool
such as GitHub. The changes are verified and validated (or
not) by the Jenkins server and the builds with the test results
are fed back to the developers.
TABLE I. Comparison of Integration Tools
Team City
Jenkins
Open Source
No
Yes
Ease of Use
5/5
3/5
Built in Features
5/5
2/5
Integration
338
1447
Support
5/5
4/5
Cloud Support
Yes
Yes
Pricing
From $299
Free
We employed one of the most popular research techniques
in Evidence Based Software Engineering (EBSE), Systematic
Literature Review (SLR).
A clear method for locating, assessing, and interpreting all
relevant evidence for a given research question or topic is
what systematic literature review (SLR) attempts to provide.
There are three primary stages to this research method:
developing a review protocol, carrying out a review, and
reporting a review.
In order to retrieve as many relevant studies as possible,
we defined a search strategy [14], [15]. The elements of the
search technique that were employed for this review are as
follows:
1) Search Method
We used automatic search method to retrieve studies in six
digital libraries (i.e., IEEE Xplore, ACM Digital Library,
Springer Link, Science Direct, and Scopus) using the search
terms introduced in Section III.B.2. We complemented the
automatic search with snowballing technique [16].
2) Search Terms
We formulated our search terms based on guidelines
provided in [14]. The resulting search terms were composed
of the synonyms and related terms about ‘‘continuous’’ AND
‘‘software’’. After running a series of pilot searches and
verifying the inclusion of the papers that we were aware of,
we utilized the final search string as presented in the
following. It should be noted that the search terms were used
to match with paper titles, keywords, and abstracts in the
digital libraries (except SpringerLink) during the automatic
search.
A recent qualitative study on DevOps in practice revealed
that the concept is not well defined and that there are
significant variations in how it is implemented [17].
Therefore, the desired and expected benefits of implementing
DevOps vary just as much. [17] indicated the varying benefits
organizations set out to achieve by initiating DevOps:
reduced lead and release time, improved problem solving,
feedback gathering and overall product quality, increased
velocity, and increased focus on new features. The main
benefits realized in these authors’ case study organizations
were, in fact, higher deployment frequency, shorter lead
times, improved automated testing, feedback gathering, and
problem solving, fewer escalations (caused by friction
between development and operations departments), more
public facing services, and an increased velocity. However,
these authors also reported that not all of these benefits were
actually achieved by the organizations that implemented
DevOps.
Furthermore, a 2017 SLR on DevOps [18] presents a set
of 17 benefits that can potentially be achieved by
implementing DevOps. These are all benefits found in
literature up to 2017, however it does not necessarily mean
that all these benefits are always achievable in practice.
Next, a case study on DevOps implementation in an
IT company in New-Zealand [19] lists the realized benefits
and their relations. It reports two main categories of benefits,
namely, increased development team engagement and
improved customer experience. Furthermore, [20] presents
from a practitioner’s perspective the potential benefits of
architecting for CD. The author outlines five types of benefits
that were noticed following the transfer of 22 software
programs to CDs: quicker time to market, enhanced capacity
to reliably create the ideal product, and increased output,
improved product quality and improved customer satisfaction.
we also found five papers that have reported reviews on
different aspects of continuous software engineering - two
studies have investigated continuous integration in the
2.1 Search Strategy
2. Research Method
3. Related Work
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.22
Abdullah, Mohammad Zeeshan,
Ansari Abdurrahman, Imran Akhtar, Salman Baig
E-ISSN: 2769-2507
185
Volume 6, 2024
literature [23], two papers have explored continuous delivery
[10] and deployment [21], and one study has targeted rapid
release [24] (See Table 2). We summarize the key aspects of
these studies. Ståhl and Bosch [23] have presented a SLR on
different attributes or characteristics of CI practice.
An automated pipeline for CI/CD of a web application in
AWS is presented in this paper. The suggested architecture,
shown in Fig. 2, is made up of VPC.
Fig. 2. The proposed architecture
The web application was developed using Java which
helps describe the software project, its dependencies and other
external components in a Project Object Model (POM). Once
created, the source code of the application was loaded in
GitHub.
A Jenkins server was set up and installed on an EC2 AWS
instance in order to carry out continuous integration. Jenkins
utilizes TCP port 8080 by default, thus you must allow
incoming connections on this port. This was accomplished by
establishing a new security group, which enables us to specify
various security guidelines according on IP source address,
protocol, and port range. Installing the GitHub. In final step in
setting up Jenkins to guarantee that all three servers work
together. The WAR file is used by Maven WAR Plugin for
collecting all dependencies, classes and resources of the
application. The new customized Docker image, called
tomcat8, was pushed to DockerHub to be used from now on.
To monitor the complete CI/CD workflow was the last
step: Dedicated processes for the web application on the
Apache2 server, CloudWatch for the AWS resources, and the
Email Jenkins notification extension plugin.
Which's implementation was covered in the section before this
one. DevOps was the finest tool for implementing CI/CD
concepts. procedures and equipment. Ansible was used to
coordinate the CD process, whereas the Jenkins server is in
charge of the CI process. Jenkins is used by most pipelines for
both CI and CD, although. Jenkins on the other hand needs a
separate SSH connection and specialized plugins for each
target.
A change made to the project's source code in the GitHub
repository starts the continuous integration task. This was
accomplished by choosing Jenkins' Poll SCM configuration,
which makes use of a Java plugin that is based on Timestamp.
The GitHub repository in the local workspace is then
replicated via the Jenkins process. Next, using, the code from
the local workspace is compiled and packed.
This section presents the results obtained in every step of
the pipeline. GitHub resources, specifically a load balancer
service, are used to host the web application on an AWS
server. As seen in Fig. 3, the web application's initial version
is thereby made available on the Internet.
Fig. 3. The first version of the web application
The next step in the pipeline was to make a change in the
application and push the new version to GitHub. This change
was automatically detected by Jenkins which starts deploying
resources for hosting the new application (see Fig. 4):
Fig. 4. Jenkins Dashboard Node
The CI portion of the pipeline will come to an end once
this step is successfully completed. The CD portion is then
implemented via a different Jenkins task, as seen in Fig. 4
shows that the deployment processes take 0.68 seconds and
on AWS (EC2).
While the application is still accessible at the same IP
address and port number as before, the changes are easily
visible.
CloudWatch was utilized for the purpose of monitoring the
application. The CPU utilization for each host running a
pipeline process is shown in real time in Fig. 7.
4. Implementation
4.1 Solution Architecture
4.2 CI/CD Process
5. Result
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.22
Abdullah, Mohammad Zeeshan,
Ansari Abdurrahman, Imran Akhtar, Salman Baig
E-ISSN: 2769-2507
186
Volume 6, 2024
Fig. 6. The new version of the application
Even when utilizing AWS instances with the fewest resources
possible, all of the figures are less than 10%. The Jenkins
server's increased CPU usage is correlated with the start of an
automated deployment procedure. The deployment resource
can be set up to restart the overloaded pods if the CPU usage
beyond the pre-allocated limit.
Fig. 7. CPU utilization of the pipeline
The automated CI/CD pipeline for AWS web application
deployment using Java is presented in this paper. When using
the existing system, developers must manually complete the
building, testing, and deployment processes, which takes more
time. Even when using scripts, users cannot pause a process
while it is being executed. However, when using automation
systems, developers can complete these tasks in a pipeline
manner and receive reports on a regular basis. In addition,
even if a phase contains errors, the system doesn’t move
forward.
The suggested solution is fast, easily scalable, dependable, and
has a 0 second downtime, according to the experimental
results. Therefore, any modifications made to the application's
source code is automatically identified, it starts a whole series
of events. When a Jenkins task fails during the deployment of
a new version of the application, the most recent stable version
of the application is rolled back by the system.
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6. Conclusion
References
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.22
Abdullah, Mohammad Zeeshan,
Ansari Abdurrahman, Imran Akhtar, Salman Baig
E-ISSN: 2769-2507
187
Volume 6, 2024
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare
that are relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.22
Abdullah, Mohammad Zeeshan,
Ansari Abdurrahman, Imran Akhtar, Salman Baig
E-ISSN: 2769-2507
188
Volume 6, 2024