Cloud Computing Case Study Topics
Several case studies exist in the domain of cloud computing. The following are the case studies that could encompass different factors of cloud computing, like optimization, migration, protection, and progressive applications:
- Migration to Cloud: A Case Study of XYZ Corporation
- Aim: The procedure and limitations of migrating on-premises architecture to the cloud has to be investigated.
- Significant Areas: Cost exploration, interruption management, migration policy, performance enhancement, tools employed such as Azure Migrate, AWS Migration Hub.
- Result: In cloud migration, assess the advantages and disadvantages such as scalability, expense savings, and possible problems confronted at the time of evolution.
- Cloud-Based Disaster Recovery: A Case Study of ABC Company
- Aim: Specifically, for a crucial business application, aim to explore the deployment of a cloud-related disaster recovery approach.
- Significant Areas: Backup policies, recovery point objectives (RPO), Disaster recovery scheduling, recovery time objectives (RTO), tools utilized like Azure Site Recovery, AWS Backup, Google Cloud Backup.
- Result: For emphasizing any enhancements in business consistency and data security, evaluate the performance of the disaster recovery approach.
- Optimizing Cloud Costs: A Case Study of DEF Enterprise
- Aim: For improving cloud spending and resource allotment, investigate appropriate tools and policies.
- Significant Areas: Resource allotment, reserved instances, cost management, auto-scaling, cost tracking tools such as Google Cloud Billing, AWS Cost Explorer, Azure Cost Management.
- Result: Typically, effective cost-saving criterions have to be detected and it is approachable to offer suggestions for other companies intending to enhance their cloud expenses.
- Implementing Serverless Architecture: A Case Study of GHI Startup
- Aim: For constructing a scalable application, examine the enactment of serverless infrastructure.
- Significant Areas: Framework design, effectiveness, scalability, expense comparison with conventional architecture, serverless services like Azure Functions, AWS Lambda, Google Cloud Functions.
- Result: In serverless framework, assess the advantages and limitations such as scalability, cost-efficiency, and development speed.
- Cloud Security Best Practices: A Case Study of JKL Financial Services
- Aim: For protecting confidential financial data in the cloud, focus on investigating suitable safety criterions and efficient ways.
- Significant Areas: Access control, adherence to rules like HIPAA, GDPR, data encryption, safety tools like Azure Security Center, AWS Security Hub, Google Cloud Security Command Center.
- Result: It is appreciable to evaluate the performance of safety ways. For improving cloud safety in the financial division, offer beneficial suggestions.
- Big Data Analytics in the Cloud: A Case Study of MNO Retail
- Aim: In what way a retail firm employs cloud-related big data analytics in order to obtain perceptions based on consumer activities and enhance business functions have to be examined.
- Significant Areas: Data gathering, storage, and processing (For instance., Azure Synapse Analytics, AWS Redshift, Google BigQuery), influence on business choices, analytics tools, data visualization.
- Result: Based on the utilization of cloud-related analytics, emphasize the merits, like actual-time perceptions and scalability, and any problems confronted has to be considered.
- Hybrid Cloud Implementation: A Case Study of PQR Healthcare
- Aim: In order to stabilize the advantages of public as well as private clouds, investigate the deployment of a hybrid cloud approach.
- Significant Areas: Data synchronization, security, combination among private and public clouds, adherence, workload dissemination, tools employed like Azure Arc, AWS Outposts, Google Anthos.
- Result: Concentrating on protection, adaptability, and cost management, aim to assess the merits and demerits of the hybrid cloud technique.
- AI and Machine Learning in the Cloud: A Case Study of STU Manufacturing
- Aim: To improve production procedures, examine in what way a manufacturing firm utilizes cloud-related machine learning and AI services.
- Significant Areas: Model training and implementation, predictive maintenance, AI/ML services like Azure Machine Learning, AWS SageMaker, Google AI Platform, influence on production performance.
- Result: In production procedures and decision-making, evaluate the enhancements facilitated by cloud-related AI/ML approaches.
- Cloud-Based DevOps Practices: A Case Study of VWX Software Company
- Aim: Specifically, to optimize software creation and implementation, aim to explore the enactment of cloud-related DevOps practices.
- Significant Areas: Automation, collaboration tools, tracking, influence on creation cycles, CI/CD pipelines like Azure DevOps, AWS CodePipeline, Google Cloud Build.
- Result: In cloud-related DevOps, assess the advantages, like improved software quality, rapid implementation, and enhanced collaboration.
- Educational Institution’s Transition to Cloud: A Case Study of YZ University
- Aim: Focus on investigating the conversion of an academic institution’s IT architecture to the cloud in order to assist remote learning.
- Significant Areas: Virtual classrooms, scalability, architecture setup, cost exploration, online collaboration tools, tools employed such as Azure for Education, AWS Educate, Google for Education.
- Result: The influence on remote learning abilities, student involvement, and entire IT management have to be evaluated.
What are the research opportunities in cloud computing?
Cloud computing is determined as a fast emerging field in current years. We provide few significant areas that offers efficient possibilities and chances for research:
- Cloud Security and Privacy
- Data Encryption: To improve data protection in the cloud, aim to investigate novel encryption methods and approaches.
- Access Control: Progressive access control frameworks have to be constructed in such a manner to assure only consented users can access confidential data.
- Privacy Preservation: For conserving user confidentiality in cloud platforms, examine techniques, like differential privacy and homomorphic encryption.
- Cloud Performance Optimization
- Resource Allocation: Mainly, to enhance the purpose of cloud sources, examine dynamic and effective resource allocation methods.
- Performance Monitoring: For actual-time tracking and performance analysis of cloud services, focus on creating approaches and tools.
- Load Balancing: It is approachable to investigate progressive load balancing approaches in order to enhance the consistency and scalability of cloud applications.
- Cloud-Based Big Data Analytics
- Scalable Analytics: For scalable data processing and analytics in the cloud, examine novel methods and models.
- Real-Time Analytics: To carry out actual-time data processing and exploration with cloud sources, focus on researching methods.
- Data Integration: In a cloud platform, construct approaches for combining and exploring data from various sources.
- Edge Computing and IoT Integration
- Edge-Cloud Collaboration: To optimize the effectiveness and efficacy of IoT applications, investigate the combination of cloud computing and edge computing.
- Latency Reduction: In edge-cloud frameworks, explore approaches to decrease delay.
- Data Management: For handling and processing data produced by IoT devices in the cloud, it is appreciable to examine suitable techniques.
- Serverless Computing
- Function-as-a-Service (FaaS): The structure and enhancement of serverless infrastructures and FaaS environments have to be researched.
- Resource Management: Focus on exploring effective resource management and planning for serverless implementations.
- Cost Optimization: For cost optimization in serverless computing platforms, aim to investigate policies.
- Cloud Migration and Multi-Cloud Strategies
- Migration Techniques: Generally, for migrating legacy applications to the cloud, it is better to explore tools and methodologies.
- Interoperability: To enhance interoperability and combination among various cloud environments, construct valuable approaches.
- Multi-Cloud Management: For handling applications and sources among numerous cloud suppliers, study tools and models.
- Artificial Intelligence and Machine Learning in the Cloud
- Scalable ML: The scalable machine learning methods have to be examined that are capable of utilizing cloud-based resources.
- Distributed AI: By means of employing cloud architecture, research distributed AI and federated learning approaches.
- AI-as-a-Service: The creation and enhancement of AI-as-a-Service contributions in the cloud has to be investigated.
- Energy Efficiency and Sustainability
- Green Cloud Computing: To decrease the carbon footprint of data centers, research energy-effective cloud computing infrastructures and approaches.
- Resource Optimization: Specifically, to improve energy effectiveness, enhance resource utilization by exploring approaches.
- Sustainable Data Centers: In sustainable cloud data centers energized by renewable energy resources, focus on examining the model and function.
- Blockchain and Cloud Computing
- Blockchain Integration: To improve clarity and protection, investigate the combination of blockchain mechanisms with cloud services.
- Decentralized Applications: Through the utilization of cloud-related blockchain environments, examine the creation of decentralized applications (DApps).
- Smart Contracts: In a cloud platform, research the implementation and management of smart contracts.
- Cloud-Native Application Development
- Microservices Architecture: By employing microservices infrastructure, investigate the model, implementation, and management of cloud-native applications.
- DevOps Practices: For continuous integration and continuous deployment (CI/CD) in the cloud, aim to study progressive DevOps practices and tools.
- Containerization: For cloud-native application creation, examine the efficiency of containerization mechanisms such as Kubernetes and Docker.
- Quantum Computing in the Cloud
- Quantum Algorithms: Typically, novel quantum methods have to be explored in such a way that could be utilized on cloud-related quantum computing environments.
- Hybrid Quantum-Classical Computing: To address complicated issues, investigate the combination of quantum computing with traditional cloud sources.
- Quantum Security: On cloud safety, study the impacts of quantum computing and focus on constructing quantum-resilient cryptographic approaches.
- Economic and Policy Aspects of Cloud Computing
- Cost Modeling: To forecast and enhance the expenses related to cloud computing, it is appreciable to create suitable frameworks.
- Regulatory Compliance: The influence of universal data security rules on cloud computing approaches have to be researched.
- Cloud Economics: It is significant to investigate the economic impacts of cloud computing enactment for governments and industries.
Cloud Computing Case Study Ideas
If you want to succeed in your career then read some of the inturging Cloud Computing Case Study Ideas that are listed below. We share novel thesis ideas with best results. In depth research will be conducted from our leading researchers so don’t hesitate to contact us for more research support.
- Challenges of cloud computing adoption from the TOE framework perspective
- Contracts for clouds: Comparison and analysis of the terms and conditions of cloud computing services
- A fad or future of IT?: A comprehensive literature review on the cloud computing research
- An efficient and secure dynamic auditing protocol for data storage in cloud computing
- Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open challenges
- Secure and practical outsourcing of linear programming in cloud computing
- Resource allocation in a network-based cloud computing environment: design challenges
- A proposed architecture of cloud computing for education system in Bangladesh and the impact on current education system
- Xenpump: a new method to mitigate timing channel in cloud computing
- Identifying Benefits and risks associated with utilizing cloud computing
- Cloud computing: A new phase in information technology management
- A classification and characterization of security threats in cloud computing
- Surveying and analyzing security, privacy and trust issues in cloud computing environments
- Cloud computing: Performance analysis of load balancing algorithms in cloud heterogeneous environment
- Identity-based Encryption to Implement Anti-Collusion Information Sharing Schemes in Cloud Computing
- A Cloud Computing Platform for FY-4 Based on Resource Scheduling Technology
- Measuring Effective Scheduling Interval Against VM Load with Rapid Elasticity in Cloud Computing
- A Hybrid Cryptography Algorithm to Improve Cloud Computing Security
- Multiobjective Optimization in the Cloud Computing Environment for Storage Service Selection
- Total Probability Decomposition Algorithm for Computer Network Reliability Analysis Based on Cloud Computing
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