AWS Services Research Articles

Configuring Real-Time Event Processing of Api Gateway with Aws and Websocket Api’s

This monitor explores how to leverage AWS API Gateway's WebSocket APIs for building real-time event processing systems. Unlike traditional HTTP-based APIs, WebSocket APIs allow bidirectional communication, enabling instant data exchange between clients and servers. This setup is ideal for applications that require low-latency interactions, such as chat applications, IoT monitoring, gaming, and live notifications. By configuring API Gateway's WebSocket integration with AWS services like Lambda and DynamoDB, developers can create responsive and scalable event-driven architectures. The document also covers strategies for managing connection states, handling errors, and ensuring secure access, offering a complete framework for real-time data processing in AWS environments. Configuring real-time event processing with AWS API Gateway and WebSocket APIs enables dynamic, bidirectional communication between clients and servers, facilitating instant data transmission. “Unlike traditional REST APIs, WebSocket APIs allow for continuous, persistent connections, making them ideal for applications that require real-time updates, such as chat applications, gaming platforms, financial tickers, and IoT systems. AWS API Gateway provides a fully managed WebSocket solution that simplifies setup, scaling, and management of real-time APIs. By integrating WebSocket APIs with AWS Lambda, DynamoDB, or Amazon Kinesis, developers can process events in real time, store data, or trigger workflows based on incoming messages. This approach not only reduces latency but also enhances application responsiveness and scalability, leveraging AWS’s serverless architecture to handle high volumes of real-time events efficiently.

Building a Data Lake on AWS: From Data Migration to AI-Driven Insights

As organizations generate and process increasing amounts of data, building data lakes on cloud platforms like AWS has become crucial to managing large datasets efficiently. This paper outlines the key steps in constructing a scalable data lake on AWS, starting from data migration to leveraging AI for insights. It explores how AWS services like S3, Glue, and SageMaker work together to facilitate data storage, transformation, and machine learning. In addition, it highlights the importance of orchestrating data pipelines with automation tools like AWS Lambda and Apache Airflow to ensure smooth, scalable, and efficient workflows. This paper explores the end-to-end process of migrating data to AWS, constructing scalable data lakes, and leveraging AI capabilities to drive actionable insights. Through practical examples, diagrams, and pseudocode, this paper provides a comprehensive guide to implementing data lakes with AWS services such as S3, Glue, and SageMaker, highlighting key considerations around data migration, storage, processing, and analytics. The role of automation tools like AWS Lambda and Airflow in orchestrating these pipelines is also discussed. Keywords AWS, Data Lake, AI-driven Insights, Data Migration, Amazon S3, AWS Glue, Amazon SageMaker, Cloud Analytics, Data Pipeline, ETL, Machine Learning

Making a Mobile-Based Social Media Information System for Environmentalists with Flutter and AWS

This research explores an effective role in environmental conservation through technological innovation. This study aims to design and develop a mobile-based social media application by utilizing Flutter technology and AWS architecture. The research focuses on managing user data securely and efficiently through AWS services. This research uses an applied method based on the Scrum framework, emphasizing technology integration for environmental preservation and AWS implementation for data security. The results showed successful application development in line with the company's environmental sustainability mission. The data management system ensures safe and efficient handling of user information. The study concludes with a summary of findings, emphasizing the positive impact of technology on environmental initiatives.

Automated Dashboard for AWS Services Monitoring

Abstract: Cloud computing has become an integral part of modern business operations, offering flexibility, scalability, and costefficiency. However, the migration to the cloud brings forth a new set of challenges, with security being a top concern. Organizations need to continuously monitor and audit their cloud environments to identify vulnerabilities, detect threats, and ensure compliance with security standards. In today's digital landscape, cloud computing has become the backbone of many organizations, offering scalability, flexibility, and cost-effectiveness. However, with the increasing reliance on cloud services comes the crucial need for robust security measures to protect sensitive data and ensure compliance with industry regulation. Traditional security audits and monitoring processes are often manual, time-consuming, and prone to human error. They lack the agility and real-time insights required to effectively protect cloud assets. To address these limitations, the Automated Reporting and Dashboards for Cloud Security Audits project leverages Artificial Intelligence (AI) and Machine Learning (ML) technologies to revolutionize cloud security management.

Design of intelligent monitoring of loneliness in the elderly using a serverless architecture with real-time communication API.

Loneliness and social isolation are recognized as critical public health issues. Older people are at greater risk of loneliness and social isolation as they deal with things like living alone, loss of family or friends, chronic illness, and hearing loss. Loneliness increases a person's risk of premature death from all causes, including dementia, heart disease, and stroke. To address these issues, the inclusion of technological platforms and the use of commercial monitoring devices are vastly increasing in healthcare and elderly care. The objective of this study is to design and develop a loneliness monitor serverless architecture to obtain real-time data from commercial activity wristbands through an Application Programming Interface. For the design and development of the architecture, the Amazon Web Services platform has been used. To monitor loneliness, the Fitbit Charge 5 bracelet was selected. Through the web Application Programming Interface offered by the AWS Lambda service, the data is obtained and stored in AWS services with an automated frequency thanks to the event bridge. In the pilot stage in which the system is, it is showing great possibilities in the ease of collecting data and programming the sampling frequency. Once the request is made, the data is automatically analyzed to monitor loneliness. The proposed architecture shows great potential for easy data collection, analysis, security, personalization, real-time inference, and scalability of sensors and actuators in the future. It has powerful benefits to apply in the health sector and reduces cases of depression and loneliness.

Let Us Create an Alexa-Enabled IoT Device Using C#, AWS Lambda, and ESP Module

Purpose: Voice-operated query is becoming popular. Alexa Such a device that is now widely used. Several vendors provide built-in Alexa services to their devices. In our fast day-to-day life, it is the most relevant Technology. It is safe and convenient also. Doing multiple work at a time is a common scenario. We can quickly get weather updates while cooking. We use our voice to operate AC, Fan, light, and electronic gadgets. Several tech giants like Amazon made Technology easy for us. Our non-Alexa devices can easily convert into Alexa enabled. We can operate our device or electric equipment just over voice. Here we provide the procedure for creating an Alexa-enabled device quickly. Using several AWS services like Alexa Skill, Lambda, and IoT, We can quickly build an Alexa-enabled custom device for us. Design/Methodology/Approach: The Alexa-enabled devices can be built following a series of processes. To create the Alexa-enabled device, we develop Alexa skills inside the Alexa developer console, write and upload command processor Lambda function using C# language inside the Microsoft visual studio, and configure the IoT profile inside the AWS IoT cloud server. Furthermore, finally, create ESP firmware to operate the equipment. To send the voice command, we need any Alexa-enabled devices. It may be an echo dot, mobile phone, or PC application. Findings/Result: Combining Amazon Alexa with IoT devices presents a potent synergy, bringing immense potential for improved user experiences and expanded automation and control capabilities. Developing an Alexa-enabled IoT device with C# and AWS Lambda is relatively uncomplicated, provided you possess some programming skills and familiarity with cloud computing. The device gains internet connectivity by leveraging an ESP module, facilitating seamless communication with the Alexa Voice Service, and empowering voice-based commands and responses. The versatility of this device spans a wide array of applications, encompassing the management of lights, switches, appliances, and more, all of which can be further tailored to specific user requirements. Originality/Value: Several documents are available to create Alexa-enabled devices. Here we provide the procedure with a block diagram and data flow so that the researcher can easily create and integrate it into their research work. All information is practical-oriented. We can quickly build Alexa-enabled devices using the practical example following this work. Paper Type: Experimental-based Research.

Implementation of Light-load automation in a lab using AWS services

Implementation of Light-load automation in a lab using AWS services

Optimization of DevOps Transformation for Cloud-Based Applications

Rapid software development is critical for meeting company objectives and competing more effectively in the competitive IoT infrastructure. DevOps is a growing technique that enables enterprises to provide high-quality software capabilities through automation, to improve team communication, and to increase efficiency across the software product lifecycle. Research problem: Due to the increased demand for new products and technologies, a huge overwork shifted on the organizations for introducing software with pace and to become stable to compete with others. Due to this, the majority of organizations prefer an automated system for product development and require cloud-based applications. The git version control system is used for version management and Docker is used to package code and provide libraries. AWS services are leveraged to deploy an application as a cloud. Jenkins is used as a CI/CD pipeline to manage various phases of development and to make the development process continuous. The ELK stack is used to monitor and visualize the execution of code. In light of the findings, DevOps is an efficient method for cloud application deployment and resource selection based on the relative importance of each optimized objective in terms of value parameters such as cost, memory, and CPU capacity, and that the method can be tailored to specific application requirements. The findings of this analysis indicate that an application can be deployed to the cloud using DevOps techniques. The proposed approach cost 60% less at full weight 1.0 and 11.3% less with no weight compared to the benchmark solution’s 15.078%

Deployment of a Serverless Web Application using AWS services

Deployment of a Serverless Web Application using AWS services

Benefits of AWS in modern Cloud over On-premises Method

Abstract: This research paper gives an overview of the benefits of AWS in the modern cloud over the On-premises methods that we use earlier before cloud computing is introduced. Cloud computing is performing well in today’s World and boosting the ability to use the internet more than ever. Cloud computing gradually developed a method to use the benefits of it in most of the organizations. It is very demanding in all businesses tasked with improving the quality of service, reducing costs as the organization pays for the service only what they consume based on the incoming and outgoing traffic. Keywords: Cloud Computing, AWS services, On-premises method, Compute Services, Networking Services, Database Services, Storage Services.

Cloud-Based System for Identifying Vaccinated Individual

Abstract: In Covid's predicament Many colleges, companies, healthcare facilities, and universities have only permitted students who have obtained vaccinations, as required by Indian government regulations. Even so, checking all of the pupils' covid vaccinations one by one will take a long time, needing more than two or three employees. As a result, the project's mission is to support the institution by delivering an automated status that shows whether or not student has been vaccinated[30]. Organizations will use a web app to collect information on the immunisation status of students and workers. Students or staff members will be required to input their name, phone number, USN number, and whether or not they have indeed been vaccinated, as well as a backend end for face recognition in raspberry pi with a camera and database as MYSQL database. Abstract. Keywords: AWS services, MySQL databases, facial recognition, PCA, LDA,

Recommendation System on Questions and Answers on Social Issues with Lifestyle in the Cloud

Abstract: Social Questions and Answers are a relatively recent feature on social media sites. It presents unique obstacles as well as potential for referral. In this project, we will examine the user's lifestyle. We will compute based on the results of the search. In this, we search any question, and the system reads these things and identifies the user's character. Based on this, we recommend the query to a user with a similar character. We show via trials with actual social networking sites, that social network and appears information may greatly improve the accuracy of popularity-based voting recommendations, but also that social media site information dominates corresponds information in NN-based methods. voting traces. We also discovered that chilly users value social and group information far more than heavy users. (Abstract) Keywords: Life-Style,, Aws services,

Indetifying Vaccinated People System Using Cloud

Abstract: In the Covid situation many Colleges, Company, Hospital and university have only allowing student who got vaccination as by the rule of govt of India but to check all the student one by one with their covid vaccination will take a lot of time as it will take more than two or three staff. so, Our project is to help the college by giving then automated status weather the student got vaccinated or not Web app will be used by the institutes to get the information about Students or Employees vaccination status Students or Employees have to enter their name, select department or enter department id, put phone number, select 1st or 2nd dose of vaccination. Then they have to upload the vaccination certificate. Then it will ask them to upload a recent photo of theirs without mask. We can also ask them few questions about their health status in past 1 month. Abstract. (Abstract) Keywords: Facial Recognition, PCA, LDA, Aws services,

Optimizing SAP Migration Strategies to AWS: Best Practices and Lessons Learned

The following paper aims at discussing the utilization of the SAP migration to AWS in details by pointing out the appropriate tactics, the challenges, and the general performance of the servers. These are AWS services useful in the context of SAP applications such as EC2 and S3, data migration approaches, enhancing SAP performance and general controlling of costs. It also takes care of important aspects like planning and evaluation, picking right migration method, as well as, compliance, security, and regulatory issues. Some of the trend in SAP and AWS integration include Artificial intelligence, the serverless architecture, and SAP in hybrid environments are also covered. The paper thus offers the following strategic interventions for organisations that seek to migrate their SAP environments to AWS seamlessly, and with maximum efficiency.

Design of Scalable IoT Architecture Based on AWS for Smart Livestock.

Simple SummaryDue to the growing number of connected IoT devices, the scalability capacity and available computing power of the existing architectural frameworks would be reached. This necessitates finding a solution that meets the growing demands. Cloud-based IoT is becoming an increasingly popular and desirable solution. This work presents a specially designed architecture based on Amazon Web Services (AWS) for monitoring livestock using cyber–physical systems (CPS) and Internet of things (IoT) equipment and a wide range of cloud native services. Used services in AWS cloud are described in detail and their tasks according to the application area are clarified. A stress test to prove the ability of the developed architecture for data processing was completed. Experimental results showed that the proposed architecture with the services provided by Amazon is fully capable of processing the required amount of data and allows the CPS/IoT infrastructure to use automated scaling mechanisms.In the ecological future of the planet, intelligent agriculture relies on CPS and IoT to free up human resources and increase production efficiency. Due to the growing number of connected IoT devices, the maximum scalability capacity, and available computing power of the existing architectural frameworks will be reached. This necessitates finding a solution that meets the continuously growing demands in smart farming. Cloud-based IoT solutions are achieving increasingly high popularity. The aim of this study was to design a scalable cloud-based architecture for a smart livestock monitoring system following Agile methodology and featuring environmental monitoring, health, growth, behaviour, reproduction, emotional state, and stress levels of animals. The AWS services used, and their specific tasks related to the proposed architecture are explained in detail. A stress test was performed to prove the data ingesting and processing capability of the proposed architecture. Experimental results proved that the proposed architecture using AWS automated scaling mechanisms and IoT devices are fully capable of processing the growing amount of data, which in turn allow for meeting the required needs of the constantly expanding number of CPS systems.

Serverless Computing Using Amazon Web Services

In the last decade cloud computing transformed the way in which we build applications. The boom in cloud computing helped to develop new software design and architecture. Helping the developers to focus more on the business logic than the infrastructure. FaaS (function as a service) compute model it gave developers to concentrate only on the application code and rest of the factors will be taken care by the cloud provider. Here we present a serverless architecture of a web application built using AWS services and provide detail analysis of lambda function and micro service software design implemented using these AWS services.

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

Commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems. Cloud computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work provides a comprehensive evaluation of EC2 cloud in different aspects. We first analyze the potentials of the cloud by evaluating the raw performance of different services of AWS such as compute, memory, network and I/O. Based on the findings on the raw performance, we then evaluate the performance of the scientific applications running in the cloud. Finally, we compare the performance of AWS with a private cloud, in order to find the root cause of its limitations while running scientific applications. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud in terms of both raw performance and scientific applications performance. Furthermore, we evaluate other services including S3, EBS and DynamoDB among many AWS services in order to assess the abilities of those to be used by scientific applications and frameworks. We also evaluate a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.

Implementation of docker integrated with cloud computing and code quality analysis (test automation)

The computer science industry is projected to grow much faster than other industries over the next 10 years focusing on delivering the best quality of soft wares and application to client within a short period of time using Agile Methodology this method anticipates change and allows for much more flexibility than traditional methods of development of software. The process involves breaking down each project into prioritized requirements, and delivering each individually within an iterative cycle. Iteration is the routine of developing small sections of a project at a time. Each iteration is reviewed and assessed by the development team and client. Quality of the code is essential for agile development environment as there can be frequent changes in requirements which lead to frequent code changes. Therefore the source code should be written in a way that it can be maintained and extended easily. In order to achieve this, developers should be thoroughly concerned about the coding standards and best practices. SonarQube can be highly beneficial for developers to ensure that their code is in high quality. Whereas Docker is an open-source technology that allows you to build, run, test, and deploy distributed applications inside software containers. It allows you to package a piece of software in a standardized unit for software development, containing everything the software needs to run: code, runtime, system tools, system libraries, etc. Docker enables you to quickly, reliably, and consistently deploy applications regardless of environment. Running Docker on AWS provides a highly reliable, low-cost way to quickly build, run, test, and deploy distributed applications at any scale. AWS provides support for Docker open-source and commercial solutions within AWS services

An efficient multi-task PaaS cloud infrastructure based on docker and AWS ECS for application deployment

The setup environment and deployment of distributed applications is a human intensive and highly complex process that poses significant challenges. Nowadays many applications are developed in the cloud and existing applications are migrated to the cloud because of the promising advantages of cloud computing. Presenting two common serious challenging scenarios in the application development environment, we propose a multi-task PaaS cloud infrastructure using Docker and AWS services for application isolation, optimization and rapid deployment of distributed applications. We fully utilized Docker, a lightweight containerization technology that uses a host of the Linux kernel's features such as namespaces and cgroup's to sandbox processes into configurable virtual environments. The Amazon EC2 container service helps our container management framework. The cluster management framework uses optimistic, shared state scheduling to execute processes on EC2 instances using Docker containers. Several experimentations were carried out, one of the experimentation focused on a simulation of application deployment scheduling that shows our propose infrastructure is flexible, efficient and well optimized.