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Top 15 Cloud Computing Research Topics in 2024

Cloud computing has suddenly seen a spike in employment opportunities around the globe with tech giants like Amazon , Google , and Microsoft hiring people for their cloud infrastructure . Before the onset of cloud computing , companies and businesses had to set up their own data centers , and allocate resources and other IT professionals thereby increasing the cost. The rapid development of the cloud has led to more flexibility , cost-cutting , and scalability .

The Cloud Computing market is at an all-time high with the current market size at USD 371.4 billion and is expected to grow up to USD 832.1 billion by 2025 ! It’s quickly evolving and gradually realizing its business value along with attracting more and more researchers , scholars , computer scientists , and practitioners. Cloud computing is not a single topic but a composition of various techniques which together constitute the cloud . Below are 10 of the most demanded research topics in the field of cloud computing .

What is Cloud Computing?

Cloud computing is the practice of storing and accessing data and applications on remote servers hosted over the internet, as opposed to local servers or the computer’s hard drive. Cloud computing, often known as Internet-based computing, is a technique in which the user receives a resource as a service via the Internet. Files, photos, documents, and other storable documents can all be considered types of data that are stored.

Let us look at the latest in cloud computing research for 2024! We’ve compiled 15 important cloud computing research topics that are changing how cloud computing is used.

1. Big Data

Big data refers to the large amounts of data produced by various programs in a very short duration of time. It is quite cumbersome to store such huge and voluminous amounts of data in company-run data centers . Also, gaining insights from this data becomes a tedious task and takes a lot of time to run and provide results, therefore cloud is the best option. All the data can be pushed onto the cloud without the need for physical storage devices that are to be managed and secured. Also, some popular public clouds provide comprehensive big data platforms to turn data into actionable insights.

DevOps is an amalgamation of two terms, Development and Operations . It has led to Continuous Delivery , Integration, and Deployment therefore reducing boundaries between the development team and the operations team . Heavy applications and software need elaborate and complex tech stacks that demand extensive labor to develop and configure which can easily be eliminated by cloud computing . It offers a wide range of tools and technologies to build , test , and deploy applications within a few minutes and a single click. They can be customized as per the client’s requirements and can be discarded when not in use hence making the process seamless and cost-efficient for development teams .

3. Cloud Cryptography

Data in the cloud needs to be protected and secured from foreign attacks and breaches . To accomplish this, cryptography in the cloud is a widely used technique to secure data present in the cloud . It allows users and clients to easily and reliably access the shared cloud services since all the data is secured using either encryption techniques or by using the concept of the private key . It can make the plain text unreadable and limit the view of the data being transferred. Best cloud cryptographic security techniques are the ones that do not compromise the speed of data transfer and provide security without delaying the exchange of sensitive data.

4. Cloud Load Balancing

It refers to splitting and distributing the incoming load to the server from various sources. It permits companies and organizations to govern and supervise workload demands or application demands by redistributing, reallocating, and administering resources between different computers, networks, or servers. Cloud load balancing encompasses holding the circulation of traffic and demands that exist over the Internet. This reduces the problem of sudden outages, results in an improvement in overall performance, has rare chances of server crashes and also provides an advanced level of security. Cloud-based server farms can accomplish more precise scalability and accessibility using the server load balancing mechanism . Due to this, the workload demands can be easily distributed and controlled.

5. Mobile Cloud Computing

It is a mixture of cloud computing , mobile computing , and wireless network to provide services such as seamless and abundant computational resources to mobile users, network operators, and cloud computing professionals. The handheld device is the console and all the processing and data storage takes place outside the physical mobile device. Some advantages of using mobile cloud computing are that there is no need for costly hardware, battery life is longer, extended data storage capacity and processing power, improved synchronization of data, and high availability due to “store in one place, accessible from anywhere”. The integration and security aspects are taken care of by the backend that enables support to an abundance of access methods.

6. Green Cloud Computing

The major challenge in the cloud is the utilization of energy-efficient and hence develop economically friendly cloud computing solutions. Data centers that include servers , cables , air conditioners , networks , etc. in large numbers consume a lot of power and release enormous quantities of Carbon Dioxide in the atmosphere. Green Cloud Computing focuses on making virtual data centers and servers to be more environmentally friendly and energy-efficient. Cloud resources often consume so much power and energy leading to a shortage of energy and affecting the global climate. Green cloud computing provides solutions to make such resources more energy efficient and to reduce operational costs. This pivots on power management , virtualization of servers and data centers, recycling vast e-waste , and environmental sustainability .

7. Edge Computing

It is the advancement and a much more efficient form of Cloud computing with the idea that the data is processed nearer to the source. Edge Computing states that all of the computation will be carried out at the edge of the network itself rather than on a centrally managed platform or data warehouse. Edge computing distributes various data processing techniques and mechanisms across different positions. This makes the data deliverable to the nearest node and the processing at the edge . This also increases the security of the data since it is closer to the source and eliminates late response time and latency without affecting productivity

8. Containerization

Containerization in cloud computing is a procedure to obtain operating system virtualization . The user can work with a program and its dependencies utilizing remote resource procedures . The container in cloud computing is used to construct blocks, which aid in producing operational effectiveness , version control , developer productivity , and environmental stability . The infrastructure is upgraded since it provides additional control over the granular activities of the resources. The usage of containers in online services assists storage with cloud computing data security, elasticity, and availability. Containers provide certain advantages such as a steady runtime environment , the ability to run virtually anywhere, and the low overhead compared to virtual machines .

9. Cloud Deployment Model

There are four main cloud deployment models namely public cloud , private cloud , hybrid cloud , and community cloud . Each deployment model is defined as per the location of the infrastructure. The public cloud allows systems and services to be easily accessible to the general public . The public cloud could also be less reliable since it is open to everyone e.g. Email. A private cloud allows systems and services to be accessible inside an organization with no access to outsiders. It offers better security due to its access restrictions. A hybrid cloud is a mixture of private and public clouds with critical activities being performed using the private cloud and non-critical activities being performed using the public cloud. Community cloud allows systems and services to be accessible by a group of organizations.

10. Cloud Security

Since the number of companies and organizations using cloud computing is increasing at a rapid rate, the security of the cloud is a major concern. Cloud computing security detects and addresses every physical and logical security issue that comes across all the varied service models of code, platform, and infrastructure. It collectively addresses these services, however, these services are delivered in units, that is, the public, private, or hybrid delivery model. Security in the cloud protects the data from any leakage or outflow, theft, calamity, and removal. With the help of tokenization, Virtual Private Networks , and firewalls , data can be secured.

11. Serverless Computing

Serverless computing is a way of running computer programs without having to manage the underlying infrastructure. Instead of worrying about servers, networking, and scaling, you can focus solely on writing code to solve your problem. In serverless computing, you write small pieces of code called functions. These functions are designed to do specific tasks, like processing data, handling user requests, or performing calculations. When something triggers your function, like a user making a request to your website or a timer reaching a certain time, the cloud provider automatically runs your function for you. You don’t have to worry about setting up servers or managing resources.

12. Cloud-Native Applications

Modern applications built for the cloud , also known as cloud-native applications , are made so to take full advantage of cloud computing environments . Instead of bulky programs like monolithic systems , they’re built to prioritize flexibility , easy scaling , reliability , and constant updates . This modular approach allows them to adapt to changing needs by growing or shrinking on demand, making them perfect for the ever-shifting world of cloud environments. Deployed in various cloud environments like public, private, or hybrid clouds, they’re optimized to make the most of cloud-native technologies and methodologies . Instead of one big chunk, they’re made up of lots of smaller pieces called microservices .

13. Multi-Cloud Management

Multi-cloud management means handling and controlling your stuff (like software, data, and services) when they’re spread out across different cloud companies, like Amazon, Google, or Microsoft. It’s like having a central command center for your cloud resources spread out across different cloud services. Multi-cloud gives you the freedom to use the strengths of different cloud providers. You can choose the best service for each specific workload, based on factors like cost, performance, or features. This flexibility allows you to easily scale your applications up or down as required by you. Managing a complex environment with resources spread across multiple cloud providers can be a challenge. Multi-cloud management tools simplify this process by providing a unified view and standardized management interface.

14. Blockchain in Cloud Computing

Cloud computing provides flexible storage and processing power that can grow or shrink as needed. Blockchain keeps data secure by spreading it across many computers. When we use them together, blockchain apps can use the cloud’s power for big tasks while keeping data safe and transparent. This combo boosts cloud data security and makes it easy to track data. It also lets people manage their identities without a central authority. However, there are challenges like making sure different blockchain and cloud systems work well together and can handle large amounts of data.

15. Cloud-Based Internet of Things (IoT)

Cloud-based Internet of Things (IoT) refers to the integration of cloud computing with IoT devices and systems. This integration allows IoT devices to leverage the computational power, storage, and analytics capabilities of cloud platforms to manage, process, and analyze the vast amounts of data they generate. The cloud serves as a central hub for connecting and managing multiple IoT devices, regardless of their geographical location. This connectivity is crucial for monitoring and controlling devices remotely.

Also Read Cloud computing Research challenges 7 Privacy Challenges in Cloud Computing Difference Between Cloud Computing and Fog Computing

Cloud computing has helped businesses grow by offering greater scalability , flexibility , and saving money by charging less money for the same job. As cloud computing is having a great growth period right now, it has created lots of employment opportunities and research work is done is different areas which is changing the future of this technology. We have discussed about the top 15 cloud computing research topics . You can try to explore and research in these areas to contribute to the growth of cloud computing technology .

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12 Latest Cloud Computing Research Topics

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Cloud Computing is gaining so much popularity an demand in the market. It is getting implemented in many organizations very fast.

One of the major barriers for the cloud is real and perceived lack of security. There are many Cloud Computing Research Topics ,  which can be further taken to get the fruitful output.

In this tutorial, we are going to discuss 12 latest Cloud Computing Research Topics. These Cloud computing topics will help in your researches, projects and assignments.

So, let’s start the Cloud Computing Research Topics.

List of Cloud Computing Research Topics

These Cloud Computing researches topics, help you to can eliminate many issues and provide a better environment. We can assoicate these issues with:

• Virtualizations infrastructure
• Software platform
• Identity management
• Access control

There is some important research direction in Cloud Security in areas such as trusted computing, privacy-preserving models, and information-centric security. These are the following Trending Cloud Computing Research Topics .

• Green Cloud Computing
• Edge Computing
• Cloud Cryptography
• Load Balancing
• Cloud Analytics
• Cloud Scalability
• Service Model
• Cloud Computing Platforms
• Mobile Cloud Computing
• Cloud Deployment Model
• Cloud Security

i. Green Cloud Computing

Green Cloud Computing is a broad topic, that makes virtualized data centres and servers to save energy. The IT services are utilizing so many resources and this leads to the shortage of resources.

Green Cloud Computing provides many solutions, which makes IT resources more energy efficient and reduces the operational cost. It can also take care of power management, virtualization , sustainability, and recycling the environment.

ii. Edge Computing

Although edge computing has several benefits, it is frequently combined with cloud computing to form a hybrid strategy. In this hybrid architecture, certain data processing and analytics take place at the edge, while more intense and extensive long-term data storage and analysis happen in the central cloud infrastructure. The edge-to-cloud continuum refers to this fusion of edge and cloud computing.

iii. Cloud Cryptography

Cloud cryptography is the practise of securing data and communications in cloud computing environments using cryptographic methods and protocols. Sensitive data is secured against unauthorised access and possible security breaches by encrypting it both in transit and at rest.

By allowing consumers to keep control of their data while entrusting it to cloud service providers, cloud cryptography protects the confidentiality, integrity, and authenticity of that data. Cloud cryptography improves the security posture of cloud-based apps and services, promoting trust and compliance with data privacy rules by using encryption methods and key management procedures.

iv. Load Balancing

Load Balancing is the distribution of the load over the servers so that the work can be easily done. Due to this, the workload demands can be distributed and managed. There are several advantages of load balancing and they are-

• Fewer chances of the server crash.
• Advanced security.
• Improvement in overall performance.

The load balancing techniques are easy to implement and less expensive. Moreover, the problem of sudden outages is diminished.

v. Cloud Analytics

Cloud analytics can become an interesting topic for researchers, as it has evolved from the diffusion of data analytics and cloud computing technologies . The Cloud analytics is beneficial for small as well as large organizations.

It has been observed that there is tremendous growth in the cloud analytics market. Moreover, it can be delivered through various models such as

• Community model

Analysis has a wide scope, as there are many segments to perform research. Some of the segments are  business intelligence tools , enterprise information management, analytics solutions, governance, risk and compliance, enterprise performance management, and complex event processing

vi. Scalability

Scalability can reach much advancement if proper research is done on it. Many limits can be reached and tasks such as workload in infrastructure can be maintained. It also has the ability to expand the existing infrastructure.

There are two types of scalability:

The applications have rooms to scale up and down, which eliminates the lack of resources that hamper the performance.

vii. Cloud Computing Platforms

Cloud Computing platforms include different applications run by organizations. It is a very vast platform and we can do many types of research within it. We can do research in two ways: individually or in an existing platform, some are-

• Amazon’s Elastic Compute Cloud
• IBM Computing
• Microsoft’s Azure
• Google’s AppEngine
• Salesforce.com

viii. Cloud Service Model

There are 3 cloud service models. They are:

• Platform as a Service (PaaS)
• Software as a Service (SaaS)
• Infrastructure as a Service (IaaS)

These are the vast topics for research and development as IaaS provides resources such as storage , virtual machines, and network to the users. The user further deploys and run software and applications. In software as a service , the software services are delivered to the customer.

The customer can provide various software services and can do research on it. PaaS also provides the services over the internet such as infrastructure and the customers can deploy over the existing infrastructure.

ix. Mobile Cloud Computing

In mobile cloud computing , the mobile is the console and storage and processing of the data takes outside of it. It is one of the leading Cloud Computing research topics.

The main advantage of Mobile Cloud Computing is that there is no costly hardware and it comes with extended battery life. The only disadvantage is that has low bandwidth and heterogeneity.

x. Big Data

Big data is the technology denotes the tremendous amount of data. This data is classified in 2 forms that are structured (organized data) and unstructured (unorganized).

Big data is characterized by three Vs which are:

• Volume – It refers to the amount of data which handled by technologies such as Hadoop.
• Variety –  It refers to the present format of data.
• Velocity – It means the speed of data (generation and transmission).

This can be used for research purpose and companies can use it to detect failures, costs, and issues. Big data along with Hadoop is one of the major topics for research.

xi. Cloud Deployment Model

Deployment model is one of the major Cloud Computing research topics, which includes models such as:

Public Cloud –  It is under the control of the third party. It has a benefit of pay-as-you-go.

Private Cloud – It is under a single organization and so it has few restrictions. We can use it for only single or a particular group of the organization.

Hybrid Cloud – The hybrid cloud comprises of two or more different models. Its architecture is complex to deploy.

Community Cloud

x. Cloud Security

Cloud Security is one of the most significant shifts in information technology. Its development brings revolution to the current business model. There is an open Gate when cloud computing as cloud security is becoming a new hot topic.

To build a strong secure cloud storage model and Tekken issues faced by the cloud one can postulate that cloud groups can find the issues, create a context-specific access model which limits data and preserve privacy.

In security research, there are three specific areas such as trusted computing, information-centric security, and privacy-preserving models.

Cloud Security protects the data from leakage, theft, disaster, and deletion. With the help of tokenization, VPNs, and firewalls, we can secure our data. Cloud Security is a vast topic and we can use it for more researches.

The number of organizations using cloud services is increasing. There are some security measures, which will help to implement the cloud security-

• Accessibility
• Confidentiality

So, this was all about Cloud Computing Research Topics. Hope you liked our explanation.

Hence, we can use Cloud Computing for remote processing of the application, outsourcing, and data giving quick momentum. The above Cloud Computing research topics can help a lot to provide various benefits to the customer and to make the cloud better.

With these cloud computing research, we can make this security more advanced. There are many high-level steps towards security assessment framework. This will provide many benefits in the future to cloud computing. Furthermore, if you have any query, feel free to ask in the comment section.

Did we exceed your expectations? If Yes, share your valuable feedback on Google

Tags: big data Cloud Analytics Cloud Computing Platforms cloud computing research Cloud Computing Research Topics Cloud Computing Topics Cloud Cryptography Cloud Deployment Model Cloud Scalability Cloud Security Cloud Service Model Edge Computing Green Cloud Computing Load Balancing Mobile Cloud Computing Research Topics on Cloud Computing

DataFlair Team

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15 Responses

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Dear, I wants to write a research paper on the cloud computing security, will also discuss the comparison of the present security shecks vs improvement suggested, I am thankful to you, as your paper helps me…

hay thanks for this valueable information dear i am just going to start my research in cloud computing from scratch i dnt now more about this field but i have to now work hard for this so plz give me idea how i start with effiecient manner

Hey Yaseen, Research is a great way to explore the entire topic. But it is recommended you master Cloud computing first, then start your research. Refer to our Free Cloud Computing Tutorial Series You can research on topics like Cloud Security, Optimization of resources, and Cloud cryptography.

Hi, Thank you for your article. I’m working on Cloud Computing Platforms research paper. Would you recommend any sources where I can get a real data or DB with numbers on cloud computing platforms. So, I can analyze it, create graphs, and draw a conclusion. Thank you

….or any sources with data on Cloud Service Models. Thank you

Can you please provide your contact details as I am also starting to research on Cloud Computing, Am a 11 years exp Consultant in an MNC working in Large Infrastructure. My email is partha.059@gmail .com so that we can communicate accordingly.

Can you please put some references you used, so that we can refer for more information? Thanks.

Hi, Very much pleased to know the latest topic for research. very informative, thanks for this i am interested in optimizing the resource here when i say resource it becomes too vast in terms of cloud computing components according to the definition of cloud computing. bit confused to hit the link.. could you plz.

hello iam searching for research gap in cloud computing I cant identify the problem please suggest me research topic on cloud computing

hello I am searching for research gap in cloud computing I cant identify the problem please suggest me research topic on cloud computing

we discuss optimization of resources, the gaps available

I want to do research in cloud databases,may i know the latest challenges in cloud databases?

I am a student of MS(computer science) and i am currently finding research topics in the area of cloud computing, Please let me know the topic of cloud computing and as well research gap so i will continue the research ahead with research gap.

Hi I am a student of MS(computer science) and i am currently finding research topics in the area of cloud computing, Please let me know the topic of cloud computing and as well research gap so I will continue the research.

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Latest Research Topics on Cloud Computing (2022 Updated)

Cloud computing is now a vital online technology that is used worldwide. The market size of cloud computing is expected to reach $832.1 billion by 2025 . Its demand will always increase in the future, and there are many major reasons behind it. It has acquired popularity because it is less expensive for companies rather than setting up their on-site server implementations.

In this article, we’ve covered the top 14 in-demand research topics on cloud computing that you need to know.

📌 These cloud Computing research topics are:

• Green cloud computing
• Edge computing
• Cloud cryptography
• Load balancing
• Cloud analytics
• Cloud scalability
• Mobile cloud computing
• Cloud deployment model
• Cloud security
• Cloud computing platforms
• Cloud service model
• Containerization

Top 14 Cloud Computing Research Topics For 2022

1. green cloud computing.

Due to rapid growth and demand for cloud, the energy consumption in data centers is increasing. Green Cloud Computing is used to minimize energy consumption and helps to achieve efficient processing and reduce the generation of E-waste.

 It is also called GREEN IT. The goal is to go paperless and decrease the carbon footprint in the environment due to remote working.

Power management, virtualization, sustainability, and environmental recycling will all be handled by green cloud computing. 

2. Edge Computing

A rapidly growing field where the data is processed at the network’s edge instead of being processed in a data warehouse is known as edge computing. The real-time computing capacity is driving the development of edge-computing platforms. The data is processed from the device itself to the point of origin without relying on a central location which also helps to increase the system’s security. It gives certain benefits such as cost-effectiveness, powerful performance, and new functionality which wasn’t previously available.

Some innovations are made with the help of cloud computing by increasing the ability of network edge capabilities and expanding wireless connections.

3. Cloud Cryptography

Cloud Cryptography is a strong layer of protection through codes that helps to give security to the cloud storage and breach of the data. It saves sensitive data content without delaying the transmission of information. It can turn plain text into unreadable code with the help of computers and algorithms and restrict the view of data being delivered.

The clients can use the cryptographic keys only to access this data. The user’s information is kept private, which results in fewer chances of cybercrime from the hackers. 

4. Load Balancing

The workload distribution over the server for soft computing is called load balancing. It helps distribute resources over multiple PCs, networks, and servers and allows businesses to manage workloads and application needs. Due to the rapid increase in traffic over the Internet, the server gets overloaded—two ways to solve the problem of overload of the servers: single-server and multiple-server solutions.

Keeping the system stable, boosting the system’s efficiency, and avoiding system failures are some reasons to use load balancing. It can be balanced by using software-based and hardware-based load balancers.

5. Cloud Analytics

Cloud analytics is a set of societal and analytical tools that analyze data on a private or public cloud to reduce data storage costs and management. It is specially designed to help clients get information from massive data. It is widely used in industrial applications such as genomics research, oil and gas exploration, business intelligence, security, and the Internet of Things (IoT).

It can help any industry improve its organizational performance and drive new value from its data. It is delivered through various models: public, private, hybrid, and community models. 

6. Cloud Scalability

Cloud scalability refers to the capacity to scale up or down IT resources as per the need for change in computing. Scalability is usually used to fulfill the static needs where the workload is handled linearly when resource deployment is persistent.

The types of scalability are vertical, horizontal, and diagonal. Horizontal scaling is regarded as a long-term advantage; on the other hand, vertical scaling is considered a short-term advantage. The benefits of cloud scalability are reliability, cost-effectiveness, ease, and speed. It is critical to understand how much those changes will cost and how they will benefit the company.

It can be applied to Disk I/O, Memory, Network I/O, and CPU. 

7. Mobile Cloud Computing

Mobile cloud computing helps to deliver applications to mobile devices through cloud computing. It allows different devices with different operating systems to have operating systems, computing tasks, and data storage. Mobile cloud helps speed and flexibility, resource sharing, and integrated data. Mobile Cloud Computing advantages are:

• Increased battery life
• Improvement in reliability and scalability
• Simple Integration
• Low cost and data storage capacity
• Processing power improvement

The only drawback is that the bandwidth and variability are limited. It has been chosen due to productivity and demand, increasing connectivity.

8. Big Data

Big data is a technology generated by large network-based systems with massive amounts of data produced by different sources. The data get classified through structured (organized data) and unstructured (unorganized data), and semi-structured forms. The data are analyzed through algorithms which may vary depending upon the data means. Its characteristics are Volume, Variety, Velocity, and Variability.

Organizations can make better decisions with the help of external intelligence, which includes improvements in customer service, evaluation of consumer feedback, and identification of any risks to the product/services.

9. Cloud Deployment Model

The way people use the cloud has evolved based on ownership, scalability, access, and the cloud’s nature and purpose. A cloud deployment model identifies a particular sort of cloud environment that determines the cloud infrastructure’s appearance.

Cloud computing deployment models are classified according to their geographical location. Deployment methods are available in public, private, hybrid, community, and multi-cloud models.

It depends on the firms to choose as per their requirements as each model has its unique value and contribution.

10. Cloud Security

Cloud security brings the revolution to the current business model through shifts in information technology. With the rapid increase in the number of cloud computing, the organization needs the security of the cloud, which has become a significant concern.

Cloud Security protects the data from any leakage or outflow, with the removal of theft and catastrophe. The cloud has public, private, and hybrid clouds for security purposes.

Cloud security is needed to secure clients’ data, such as secret design documents and financial records. Its benefits are lower costs, reduced ongoing operational and administrative expenses, increased data reliability and availability, and reduced administration.

11. Cloud Computing Platforms

In an Internet-based data center, a server’s operating system and hardware are referred to as a cloud platform. Cloud platforms work when a firm rents to access computer services, such as servers, databases, storage, analytics, networking, software, and intelligence. So the companies don’t have to set up their data centers or computing infrastructure; they need to pay for what they use. It is a very vast platform where we can do many types of research.

12. Cloud Service Model

The use of networks hosted on the Internet to store from remote servers used in managing and processing data, rather than from a local server or a personal computer. It has three models namely Infrastructure-as-a-Service (IaaS), Software-as-a-Service (SaaS),and Platform-as-a-Service (PaaS).Each type of cloud computing service provides different control, flexibility, and management levels to choose the right services for your requirements.

The ability to deliver applications and services increases an organization’s ability to evolve and improve products faster. This model helps the firms have their benefits more quickly and better than traditional software. In the DevOps approach, development and operations teams are integrated into a single unit, enabling them to develop diverse skills that aren’t limited to a particular task. The benefits of DevOps are rapidity, increase in frequency, reliability, scale, improved collaboration, and security.

It provides a wide range of tools and technologies to meet clients’ needs.

14. Containerization

Containerization is a popular software development technique that is rapidly evolving and can be used in addition to virtualization. It includes packaging software code and all of its components so that it may run consistently and uniformly across any infrastructure. The developers and operational teams see its benefit as it helps create and locate applications quickly and more securely. It benefits developers and development groups as it provides flexibility/ portability, the ability to move swiftly and efficiently, speed, fault isolation, efficiency, easily manageable, and security. 

Final Words

Hence, all the above are new technologies of cloud computing developed to benefit users worldwide. But there are some challenges that need to be overcome. People nowadays have become skeptical about whether their data is private, secure, or not. This research can make this security more advanced and help to provide innovations in cloud computing.

We hope this article helps you to know some best research topics on cloud computing and how they’re changing the world.

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Aims and scope

The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future. Comprehensive review and survey articles that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.

Published articles will impart advanced theoretical grounding and practical application of Clouds and related systems as are offered up by the numerous possible combinations of internet-based software, development stacks and database availability, and virtualized hardware for storing, processing, analysing and visualizing data. Where relevant, Clouds should be scrutinized alongside other paradigms such Peer to Peer (P2P) computing, Cluster computing, Grid computing, and so on. Thorough examination of Clouds with respect to issues of management, governance, trust and privacy, and interoperability, are also in scope. The Journal of Cloud Computing is indexed by the Science Citation Index Expanded/SCIE. SCI has subsequently merged into SCIE.  

Cloud Computing is now a topic of significant impact and, while it may represent an evolution in technology terms, it is revolutionising the ways in which both academia and industry are thinking and acting. The Journal of Cloud Computing, Advances, Systems and Applications (JoCCASA) has been launched to offer a high quality journal geared entirely towards the research that will offer up future generations of Clouds. The journal publishes research that addresses the entire Cloud stack, and as relates Clouds to wider paradigms and topics.

Chunming Rong, Editor-in-Chief University of Stavanger, Norway

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• DOI: 10.1109/SBES.2012.12
• Corpus ID: 15541874

Software Engineering for the Cloud: A Research Roadmap

• Elias Adriano Nogueira da Silva , D. Lucrédio
• Published in Brazilian Symposium on… 23 September 2012
• Computer Science, Engineering

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Research Advances in Cloud Computing

• © 2017
• Sanjay Chaudhary 0 ,
• Gaurav Somani 1 ,
• Rajkumar Buyya 2

School of Engineering and Applied Science, Ahmedabad University, Ahmedabad, India

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Department of Computer Science and Engineering, Central University of Rajasthan, Ajmer, India

School of computing and information systems, the university of melbourne, melbourne, australia.

• Presents detailed insights into the research that drives the future of cloud computing
• Focuses on open research problems
• Offers a comprehensive overview of the research areas and recent work
• Includes supplementary material: sn.pub/extras

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About this book

This book addresses the emerging area of cloud computing, providing a comprehensive overview of the research areas, recent work and open research problems. The move to cloud computing is no longer merely a topic of discussion; it has become a core competency that every modern business needs to embrace and excel at. It has changed the way enterprise and internet computing is viewed, and this success story is the result of the long-term efforts of computing research community around the globe. It is predicted that by 2026 more than two-thirds of all enterprises across the globe will be entirely run in cloud. These predictions have led to huge levels of funding for research and development in cloud computing and related technologies.

Accordingly, universities across the globe have incorporated cloud computing and its related technologies in their curriculum, and information technology (IT) organizations are accelerating their skill-set evolution in order to be better prepared to manage emerging technologies and public expectations of the cloud, such as new services.

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Front matter, serverless computing: current trends and open problems.

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Highly Available Clouds: System Modeling, Evaluations, and Open Challenges

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Big Data Analytics in Cloud—A Streaming Approach

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A Terminology to Classify Artifacts for Cloud Infrastructure

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Virtual Networking with Azure for Hybrid Cloud Computing in Aneka

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Building Efficient HPC Cloud with SR-IOV-Enabled InfiniBand: The MVAPICH2 Approach

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Resource Procurement, Allocation, Metering, and Pricing in Cloud Computing

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Dynamic Selection of Virtual Machines for Application Servers in Cloud Environments

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Improving the Energy Efficiency in Cloud Computing Data Centres Through Resource Allocation Techniques

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Recent Developments in Resource Management in Cloud Computing and Large Computing Clusters

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Resource Allocation for Cloud Infrastructures: Taxonomies and Research Challenges

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Many-Objective Optimization for Virtual Machine Placement in Cloud Computing

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Performance Modeling and Optimization of Live Migration of Virtual Machines in Cloud Infrastructure

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Identifying Evidence for Cloud Forensic Analysis

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An Access Control Framework for Secure and Interoperable Cloud Computing Applied to the Healthcare Domain

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Applications of Trusted Computing in Cloud Context

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Editors and Affiliations

Sanjay Chaudhary

Gaurav Somani

Rajkumar Buyya

About the editors

Dr. Sanjay Chaudhary is a Professor and Associate Dean of the School of Engineering and Applied Science, Ahmedabad University, Ahmedabad, India. His research areas are data analytics, cloud computing, and ICT applications in agriculture and rural development. He has authored four books, six book chapters, and published more than hundred research papers and ten literary articles in international conferences, workshops, and journals. He has served on the program committees of leading international conferences and workshops, and he is also a member of the review committees of leading journals. He holds a doctorate degree in computer science from Gujarat Vidyapeeth, Ahmedabad, India. Earlier, he worked as a Professor and Dean (Academics Programs) at DA-IICT. He has also worked on various large-scale software development projects for the corporate sector, co-operative sector, and government organizations. He is actively involved in various consultancy and enterprise application development projects.

Gaurav Somani is an Assistant Professor at the Department of Computer Science and Engineering at the Central University of Rajasthan (Ajmer), India. He has submitted his PhD in Computer Science and Engineering from MNIT, Jaipur, India. His research interests include distributed systems, network security, cloud computing, and open-source technologies. He has published number of papers in various conferences and journals of international repute and is a reviewer of many top journals. Some of his top papers are published in highly reputed journals such as Computer Networks, Annals of Telecommunications, Computer Communications, IEEE Cloud Computing, Computers and Electrical Engineering, FGCS, and IEEE Cloud. He has written a book on “Scheduling and Isolation in Virtualization” which is published by VDM Verlag Dr. Muller Publishers, Germany. This book is used as a text/reference book in some graduate-level programs across the globe. He is also a part of multiple international conferences across the globe where he has played a role of TPC member, session chair, and invited speaker. He was the keynote and the tutorial chair at the ICISS 2016. He is a member of IEEE and ACM.

Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor of Computer Science and Software Engineering and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He is also serving as the founding CEO of Manjrasoft, a spin-off company of the university, commercializing its innovations in cloud computing. He served as Future Fellow of the Australian Research Council during 2012–2016. He has authored over 525 publications and seven text books including ``Mastering Cloud Computing'' published by McGraw Hill, China Machine Press, and Morgan Kaufmann for Indian, Chinese, and international markets, respectively. He has also edited several books including ``Cloud Computing: Principles and Paradigms''(Wiley Press, USA, Feb 2011). He is one of the highly cited authors in computer science and software engineering worldwide (h-index=112, g-index=245, 63,900+citations). Microsoft Academic Search Index ranked Dr. Buyya as #1 author in the world (2005–2016) for both field rating and citations evaluations in the area of Distributed and Parallel Computing. Recently, Dr. Buyya is recognized as “2016 Web of Science Highly Cited Researcher” by Thomson Reuters.

Bibliographic Information

Book Title : Research Advances in Cloud Computing

Editors : Sanjay Chaudhary, Gaurav Somani, Rajkumar Buyya

DOI : https://doi.org/10.1007/978-981-10-5026-8

Publisher : Springer Singapore

eBook Packages : Computer Science , Computer Science (R0)

Copyright Information : Springer Nature Singapore Pte Ltd. 2017

Hardcover ISBN : 978-981-10-5025-1 Published: 31 January 2018

Softcover ISBN : 978-981-13-5296-6 Published: 09 December 2018

eBook ISBN : 978-981-10-5026-8 Published: 28 December 2017

Edition Number : 1

Number of Pages : XX, 465

Number of Illustrations : 45 b/w illustrations, 81 illustrations in colour

Topics : Computer Communication Networks , Computer Hardware , Systems and Data Security , Information Systems Applications (incl. Internet)

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The digital forecast: 40-plus cloud computing stats and trends to know in 2023

Blair Franklin

Contributing Writer, Google Cloud

Stay in the know and spark dialogue with the latest cloud computing insights from our live blog. Bonus: Every stat has a grab-and-go slide.

Why google cloud.

Get unmatched cloud technology built on Google’s infrastructure.

How are IT leaders changing their cloud strategies in times of uncertainty? What are the biggest barriers to achieving true corporate sustainability? What’s helping to reduce burnout on software and IT teams? Where does  Vint Cerf  get all of his stylish pocket squares? (We're still gathering data on that last one.) 

The cloud computing landscape is as dynamic as the weather. As the pace of innovation in the cloud and the availability of new tools and services continues to explode, Gartner®  forecasts  worldwide public cloud end-user spending to reach nearly $600 billion in 2023. It’s an exciting, promising, and sometimes dizzying space. 

To help the C-suite, IT, and business decision-makers keep up with industry-shaping trends, we’re kicking off this live blog to share the latest insights across topics that matter to today’s organizational leaders: business resilience, data analytics, artificial intelligence (AI) and machine learning (ML), cloud infrastructure, cybersecurity, corporate sustainability, and more.

Bonus: Every stat has a complementary visual slide available to download. We’ll be adding to this post each week, so bookmark it as a go-to resource for the latest cloud computing trends, statistics, and insights to shape decision-making in 2023.

Explore by category — new topics will be added regularly:

Business resilience

Artificial intelligence (AI) and machine learning (ML)  

Culture of innovation

Cloud infrastructure

Cloud security

Corporate sustainability

Financial resilience stats

1. IT leaders are looking to the cloud to help prepare for whatever lies ahead. 

Due to the current macroeconomic climate, cloud leaders say they are increasing their use of cloud-based services and products (41.4%), planning to migrate from legacy enterprise software to cloud-based tools (33.4%), and migrating on-premises workloads to the cloud (32.8%). Download slide Source: Google Cloud Brand Pulse Survey, Q4 2022. Learn more about how decision-makers are preparing for uncertainty .

2. Cloud decision-makers are prioritizing staffing efforts when it comes to cloud cost optimization.  

More than half of organizations are either hiring new staff or re-training existing staff to better optimize their cloud spend. Download slide Source: Forrester, 2022 Infrastructure Cloud Survey  

3. Most companies have yet to embrace cloud FinOps.  

In a 2022 survey of cloud FinOps practitioners, 37.1% of the 572 respondents who answered a question about the maturity level of their cloud FinOps efforts said they were in the “crawl” stage — getting the basics in place. Another 41.7% were in the “walk” stage, where practitioners have established practices but not yet perfected them, while just 19.5% of participants were at the leading edge of maturity, where cloud FinOps is business as usual (the “run” stage). The remaining respondents comprised a “pre-crawl” segment. Download slide Source: The State of FinOps 2022 , FinOps Foundation. Learn more about harnessing the power of FinOps .

4. Companies in every industry can capture substantial value from cloud. 

A detailed review of cloud cost-optimization levers and value-oriented business use cases foresees more than $1 trillion in run-rate EBITDA across Fortune 500 companies as up for grabs in 2030. Download slide Source: Cloud’s trillion-dollar prize is up for grabs , McKinsey, 2021

5. “Industry clouds” will increase organizational agility, speed innovation, and accelerate time to value. 

By 2027, more than 50% of enterprises will use industry cloud platforms to accelerate their business initiatives. Industry cloud platforms enable a shift from generic solutions to platforms designed to fit the specifics of the user’s industry. Download slide Source: Gartner® ebook, Gartner's 2023 Top Strategic Technology Trends , 2022. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

6. Automated cloud cost optimization policies can save time and reduce wasted spend. 

More than 40% of technical and business professionals are using automated policies to shut down workloads after hours and to rightsize underutilized instances. Automated cloud cost optimization policies can save time while ensuring organizations monitor their environments consistently to eliminate waste. Download slide Source: Flexera 2022 State of the Cloud Report

7. When it comes to a strategic cloud computing partner, decision-makers are looking for three specific characteristics. 

The majority (54%) of global tech and business leaders want a cloud service provider who helps them identify technology strategies to increase revenue or reduce costs. Further, 50% define a “strategic partner” as one who “understands where my industry is going and has solutions for future needs,” and 50% say it’s “having a services organization that helps implement and maintain my infrastructure.” Download slide Source: Internal data from the Google Cloud Brand Pulse Survey, Q3 2022

Artificial intelligence (AI) and machine learning (ML) stats

1. Get ready to reskill rather than just hiring new employees for AI skills.  

IDC research suggests organizations realize they can’t simply hire data scientists to solve AI talent issues and will invest internally in reskilling and AI-enabled augmentation of existing employees. Some 34% of worldwide AI service buyers chose “IT training or education” as a top service line for AI investment in the next 12 months (and for those in IT roles, the figure increased to 38%). Download slide Source: IDC FutureScape: Worldwide Artificial Intelligence and Automation 2023 Predictions , doc #US49748122, October 2022

2. AI/ML is a top workload requirement driving multicloud deployments. 

Today’s tech leaders need cloud infrastructure that can support AI/ML workloads, and they’ll use other cloud providers beyond their primary cloud provider to get what they need. According to Enterprise Strategy Group research, 39% cite AI/ML as a top workload and/or workload requirement leading to their use of other cloud providers in addition to their primary cloud provider. Application development and testing (39%), database clustering (33%), and global service delivery (31%) are some other top requirements. Download slide . Source: Enterprise Strategy Group eBook, Multicloud Application Deployment & Delivery Decision Making , February 2023

3. AI and computing advancements are helping to scale digital transformation and propel AI towards mainstream adoption. 

As AI adoption ramps up and the pressure to keep pace with demand for AI-based services and tools increases, most organizations will use codeless development tools for at least 30% of AI and automation initiatives by 2024. Download slide Source: IDC FutureScape: Worldwide Artificial Intelligence and Automation 2023 Predictions , doc #US49748122, October 2022

4. AI is finding its way into every layer of technology that organizations use to help drive automation. 

By 2026, AI-driven features will be embedded across business technology categories with 60% of organizations using them to drive better outcomes without relying on technical AI talent. Download slide Source: IDC FutureScape: Worldwide Artificial Intelligence and Automation 2023 Predictions , doc #US49748122, October 2022

5. AI has the potential to help organizations and people to be more productive. 

Trends show that by 2026, 85% of enterprises will combine human expertise with AI, ML, natural language processing (NLP), and pattern recognition to help augment foresight, increasing worker productivity by 25%. Download slide Source: IDC FutureScape: Worldwide Artificial Intelligence and Automation 2022 Predictions , doc #US48298421, October 2021

6. Organizations have not reached a level of maturity in their AI infrastructure.  

When it comes to AI/ML initiatives, survey results from the International Data Corporation (IDC) show that most organizations are still in the experimentation, evaluation and testing, or prototyping phases. Only 31% of respondents said they had AI in production — and just a third from that segment claimed to have reached a mature state of adoption, where the entire organization benefits from an enterprise-wide AI strategy. Download slide Source: IDC Press Release, IDC Survey Illustrates the Growing Importance of Purpose-built AI Infrastructure in the Modern Enterprise , February 2022. Read more: Build an effective AI strategy: Overcome four common adoption challenges

7. CxOs are leveraging AI to turn IT operations into a well-oiled machine.  

Nearly 40% of decision-makers are using AI to improve efficiencies in IT operations. CxOs also indicated this is their most common use case for AI. Download slide Source: Forrester 2022 Data & Analytics survey

8. Adaptive AI accelerates value and continuously keeps AI aligned to enterprise goals in real time.  

By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%. Adaptive AI systems use real-time feedback to learn dynamically and adjust, even for unforeseen real-world changes. Download slide Source: Gartner® ebook, Gartner's 2023 Top Strategic Technology Trends , 2022. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Culture of innovation stats

Source: Google Cloud Brand Pulse Survey, Q4 2022. Download the slide or  read the full article .

1. The meaning of digital transformation is changing. 

72% of cloud decision-makers view digital transformation as something more than a simple lift-and-shift exercise where systems are moved from data centers to the cloud. Download slide Source: Google Cloud Brand Pulse Survey, Q2 2022.  Read more about how the definition of digital transformation is changing .

2. Organizations plan to focus on investments towards innovation over the next five years. 

Some 75% of enterprises plan to invest in new technology platforms to facilitate innovation exchange. Other significant areas include investing in additional training programs on innovation (64%), evolving hiring policies to capture more diverse ideas and approaches (53%), and strengthening data gathering and analysis processes to support decision making (42%). Download slide Source: Create a Culture of Innovation , Google Cloud, 2022

3. Process optimization and customer experience are at the heart of digital transformations.  

Around 47% of cloud decision-makers say digital transformation means optimizing processes and becoming more operationally agile, and another 40% say it’s improving customer experience. Download slide  and bonus gif   Source: Google Cloud Brand Pulse Survey, Q2 2022.  Read more about how business leaders define digital transformation .

4. Culture has a significant effect on whether individuals struggle with burnout as a result of working remotely. 

Teams with a generative culture, composed of people who felt included and like they belonged on their team, were half as likely to experience burnout during the pandemic. This finding reinforces the importance of prioritizing team and culture. Teams that do better are equipped to weather more challenging periods that put pressure on both the team and on individuals. Download slide Source: 2021 State of DevOps Report , commissioned by the Google Cloud DORA Team

5. The experiences of diverse employees are leading to poor outcomes for individuals and employers. 

50% of employees are estimated to have left a job due to DEI shortcomings. Download slide Source: " It’s Time to Reimagine Diversity, Equity, and Inclusion ," Boston Consulting Group, May 2021

6. The use of cloud computing has a positive impact on overall organizational performance.  

IT leaders and practitioners that use cloud computing are 14% more likely to exceed organizational performance goals than peers that do not. Download slide Source: 2022 State of DevOps Report , commissioned by the Google Cloud DORA Team

Cloud infrastructure stats

1. Leading IT professionals embrace multicloud. In order to scale applications to meet the needs of their users, more and more organizations are managing their resources in distributed application environments.  

According to a recent survey by Enterprise Strategy Group, the majority of organizations deploy applications in 2+ on-premises data centers, 2+ colocation providers, 3+ IaaS providers, and 3+ PaaS providers. The age of multicloud is officially here, as 85% of organizations indicated they deploy applications on two or more IaaS providers.  Download slide Source: Enterprise Strategy Group eBook, Multicloud Application Deployment & Delivery Decision Making , February 2023

2. When it comes to selecting the right cloud provider, more groups are getting a seat at the table. 

For many, choosing a cloud provider used to be the sole responsibility of the IT department. But today, it is a highly strategic decision involving multiple members across IT, information security, the C-suite, and more. On average, 3.7 groups in an organization own cloud selection decisions. The top groups cited that have decision-making authority are IT Leadership (50%), Information Security, (47%), IT Infrastructure and Management (47%), and non-IT Executive Management/C-suite (44%). Download slide   Source: Enterprise Strategy Group eBook,  Multicloud Application Deployment & Delivery Decision Making , February 2023

3. Cloud-first is the dominant policy for deploying new applications. 

Across deployment strategies for net-new applications and workloads, 47% of organizations within various industries follow a cloud-first strategy by deploying new applications using public cloud services. Meanwhile, 27% of organizations consider both public cloud services and on-premises resources for new applications, while 26% are on-premises-first but still consider compelling cases to deploy in cloud. Download slide   Source: Enterprise Strategy Group eBook,  Multicloud Application Deployment & Delivery Decision Making , February 2023

4. The desire for flexibility fuels multicloud decision making, and the type of desired flexibility varies by industry. 

Performance flexibility (35%) is the top cited reason for using more than one public cloud infrastructure provider. Industry also plays a role in what type of prioritization IT leaders care about. For example, healthcare organizations (45%) lean more heavily towards cost flexibility. Retail (48%) and technology (45%) organizations want teams to be able to use their preferred clouds of choice. Finance organizations (43%) want to avoid vendor lock-in. Download slide   Source: Enterprise Strategy Group eBook,  Multicloud Application Deployment & Delivery Decision Making , February 2023

5. Organizations are doubling down on cloud and hybrid cloud, pushing even more applications out of on-premises environments. 

In 2022, 93% of technology leaders said they were “mostly cloud” in some form — up from 83% two years ago — and 48% said they were “mostly hybrid,” up from 40% two years ago. Meanwhile, the number of respondents who said they were “mostly on-premises'' dropped by half to 7%. Download slide Source: 2022 State of APIs and Applications

6. IT leaders say APIs give their business an edge. More than six in 10 (61%) say that APIs help build better digital experiences and products, and 54% say they accelerate innovation by facilitating collaboration with partners. Download slide . Source: 2022 State of APIs and Applications

7. Tools built by cloud providers are a preferred starting place for operations and management teams working in the cloud.

69% of IT leaders and decision-makers trust that cloud providers can build better tools to manage their own clouds. Download slide Source: “A Built-In Observability Tool Adoption Blueprint for Public Cloud: Driving Quantified Value for DevOps, Development, Operations, and SRE Teams,” IDC whitepaper sponsored by Google Cloud, 2022

8. Budgets are increasing across both internal private cloud and public, and across cloud workload types. 

In the 2022 Infrastructure Cloud Survey, respondents reported an increase in IT budget for both public cloud (75%) and internal private cloud (77%) during 2022. Download slide . Source: Forrester 2022 Infrastructure Cloud Survey

9. Multicloud and hybrid cloud use is on the rise. 

Some 26% of people reported using multiple public clouds in 2022, up from 21% in 2021. Hybrid cloud use also increased from 25% to 42.5%. Download slide . Source: 2022 State of DevOps Report , commissioned by the Google Cloud DORA Team

10. The use of cloud computing continues to accelerate. 

During 2022, 76% of people reported using the public cloud, including multiple clouds — up from 56% in 2021. Download slide . Source: 2022 State of DevOps Report , commissioned by the Google Cloud DORA Team

Cloud security stats

1. Cybersecurity is the No. 1 investment priority for organizations in 2023.

Approximately (31%) of 4,332 global enterprise cloud decision makers ranked “cybersecurity” as a top investment priority for their organization in 2023 over data management and/or data analytics (25%), AI&ML (20%), app and/or infrastructure modernization (12%), and productivity & collaboration (11%). Download slide Source: Google Cloud Brand Pulse Survey, Wave 5, 2022

2. When it comes to trusting a cloud provider, IT leaders say data protection and interoperability/openness are the two most important capabilities or provisions.

Globally, enterprise cloud decision makers feel that “strong capabilities for protecting and controlling my data in the cloud” (40%) and “working well with existing security solutions and other security vendors” (38%) are the top ways cloud providers can gain trust. Download slide Source: Google Cloud Brand Pulse Survey, Wave 5, 2022

3. Supply chains are growing as an attractive target that acts as an entry point to multiple vendors. 

Supply chain was identified as the initial infection vector — the first path attackers used to gain access to an environment — in 17% of security intrusions in 2021, compared to less than 1% in 2020. Download slide Source: M-Trends 2022 , Mandiant

4. Business and professional services and financial services are the top targeted industries across the globe. 

The top five industries favored by adversaries in 2021, based on Mandiant incident response engagements, include business and professional services, financial, healthcare, retail and hospitality, and high tech. Download slide Source: M-Trends 2022 , Mandiant

5. API security is affecting the pace of innovation for many organizations. 

More than half (53%) of organizations have delayed the rollout of a new service or application due to API security concerns. For those who have experienced an incident in the past 12 months, more than three quarters (77%) have delayed the rollout of a new service or application. Download slide . Source: API Security: Latest Insights & Key Trends

6. Companies are prioritizing being proactive with API security.

To stay ahead of security threats, many organizations look for solutions that allow them to be proactive while minimizing the burden on their security teams. Capabilities that proactively identify security threats (60%) and improve automation (57%) are at the top of most IT leaders’ wish lists. Download slide . Source: API Security: Latest Insights & Key Trends

7. Development teams that embrace security see significant value driven to the business. 

Teams who integrate security best practices throughout their development process are 1.6 times more likely to meet or exceed their organizational goals. Download slide Source: 2021 State of DevOps Report , commissioned by the Google Cloud DORA Team

8. The biggest predictor of an organization's software security practices is cultural, not technical. 

High-trust, low-blame cultures focused on performance were 1.6 times more likely to have above-average adoption of emerging security practices than low-trust, high-blame cultures focused on power or rules. Download slide Source: 2022 State of DevOps Report , commissioned by the Google Cloud DORA Team

9. Europe may surpass the United States as the most targeted region for ransomware. 

Ransomware continues to have a significant impact on businesses across the globe. While reports show that the U.S. is the country most targeted by ransomware attacks worldwide, small indicators show that ransomware activity is decreasing in the United States and growing in other regions. For instance, the number of European victims is on the rise, and if that increase continues, Europe will likely become the most targeted region in 2023. Download slide Source: Cybersecurity Forecast 2023 , Mandiant

Corporate sustainability stats

1. Technology innovation is the top utility executives believe will impact the sustainable growth of their organization.  

More than 91% of respondents agree that “technology makes it possible for our organization to be more sustainable.” Download slide Source: CEOs are Ready to Fund a Sustainable Transformation , The Harris Poll survey for Google Cloud, 2022

2. Increasingly, sustainable technology will be a must-have; not a nice-to-have. By 2025, 50% of CIOs will have performance metrics tied to the sustainability of the IT organization. 

Sustainable technology is a framework of digital solutions that can be used to enable ESG outcomes. Download slide Source: Gartner® ebook, Gartner's 2023 Top Strategic Technology Trends , 2022. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

3. Many organizations still struggle to overcome internal barriers to achieving corporate sustainability. 

When asked about the top barriers to achieving true environmental sustainability, executives identified the following as their biggest challenges: lack of investment in the right technology (36%), lack of understanding about the issue (36%), too much focus on growth and profit (34%), limited budget for sustainability measures (34%), and lack of regulatory incentives or political will (34%).  Download slide Source: CEOs are Ready to Fund a Sustainable Transformation , The Harris Poll survey for Google Cloud, 2022

4. Digital technologies have the potential to help minimize carbon emissions across the entire digital value chain. 

Digital solutions will play an enabling role for at least 20-25% of the reductions required to achieve a net-zero economy in Europe. Download slide Source: Digital Decarbonisation , Implement Consulting Group (ICG) study commissioned by Google, 2022

5. Digitalization is correlated with a higher degree of decoupling between economic growth and emissions. 

The most advanced digital economies in the EU reduced greenhouse gas emissions by 25% between 2003 and 2019 while increasing economic output by 30% in the same period. Download slide Source: Digital Decarbonization, Implement Consulting Group (ICG) study commissioned by Google, 2022

6. Authentically achieving sustainability is a big challenge. 

Only 36% of executives said that their organizations have measurement tools in place to quantify their sustainability efforts, and just 17% are using those measurements to optimize based on results. Download slide Source: CEOs are Ready to Fund a Sustainable Transformation , The Harris Poll survey for Google Cloud, 2022

7. Technology is key to transforming corporate sustainability. 

Nearly 80% of executives cite technology as critical for their future sustainability efforts, attesting that it helps transform operations, socialize their initiatives more broadly, and measure and report on the impact of their efforts. Download slide Source: CEOs are Ready to Fund a Sustainable Transformation , The Harris Poll survey for Google Cloud, 2022

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Cloud System and Software Analytics

In Microsoft, we build and operate several world leading complex and large-scale productivity clouds (Azure, Microsoft 365). The quality of cloud platforms, including reliability, performance, efficiency, security, sustainability, etc., has become immensely important. The distributed nature, massive scale, and high complexity of cloud platforms present huge challenges to build and operate such systems effectively and efficiently. Each independent service in cloud computing, such as computing virtualization, cloud storage service, distributed database, etc., is a complex distributed system. These services (including various services under the IaaS, PaaS, and SaaS models) together constitute the overall solution of cloud computing, and become a complex system (System of System). With understanding and analysis of such system architecture, we can optimize the cloud computing system and infrastructure, and to further improve the quality of cloud computing services.

Cloud systems and software analytics research has covered various topics of cloud system/infrastructure, software analytics and DevOps. Besides publishing 60+ papers in top conferences, the research team has delivered significant contributions in enhancing reliability, performance, capacity efficiency, productivity and sustainability for Microsoft cloud production. These general technologies can be expanded to other online services. Hence, we believe that ramping up our investments in cloud systems and software analytics research is crucial towards our long-term success.

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The goal is to synergize the related areas and advance state-of-the-art research in Systems and Software. Based on huge scale data, the team is building innovative technologies on Systems and software, intelligent Software Engineering, resource optimization, ML for systems, Cloud Intelligence and AIOps. You will be working together with world-class experts on exciting and impactful research projects, as well as publishing papers in top-tier conferences in Software, System, or AI areas.

We are looking for talents at different levels, Senior Researchers/Researchers/Senior RSDE/RSDE (Research SDE), in systems and software. Candidates have knowledge and experience in Systems, Software, or data mining as preferred.

Please contact us at [email protected] . Also welcome any enquires.

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Cloud Computing

The SEI studies cloud computing to help organizations develop and operate secure and cost-effective systems and deliver scalable capability to the network edge.

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Updated: 14 February 2024 Contributors: Stephanie Susnjara, Ian Smalley

Cloud computing is the on-demand access of computing resources—physical servers or virtual servers, data storage, networking capabilities, application development tools, software, AI-powered analytic tools and more—over the internet with pay-per-use pricing.

The cloud computing model offers customers greater flexibility and scalability compared to traditional on-premises infrastructure.

Cloud computing plays a pivotal role in our everyday lives, whether accessing a cloud application like Google Gmail, streaming a movie on Netflix or playing a cloud-hosted video game.

Cloud computing has also become indispensable in business settings, from small startups to global enterprises. Its many business applications include enabling remote work by making data and applications accessible from anywhere, creating the framework for seamless omnichannel customer engagement and providing the vast computing power and other resources needed to take advantage of cutting-edge technologies like generative AI and quantum computing . 

A cloud services provider (CSP) manages cloud-based technology services hosted at a remote data center and typically makes these resources available for a pay-as-you-go or monthly subscription fee.

Read how Desktop as a service (DaaS) enables enterprises to achieve the same level of performance and security as deploying the applications on-premises.

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Compared to traditional on-premises IT that involves a company owning and maintaining physical data centers and servers to access computing power, data storage and other resources (and depending on the cloud services you select), cloud computing offers many benefits, including the following:

Cloud computing lets you offload some or all of the expense and effort of purchasing, installing, configuring and managing mainframe computers and other on-premises infrastructure. You pay only for cloud-based infrastructure and other computing resources as you use them. 

With cloud computing, your organization can use enterprise applications in minutes instead of waiting weeks or months for IT to respond to a request, purchase and configure supporting hardware and install software. This feature empowers users—specifically DevOps and other development teams—to help leverage cloud-based software and support infrastructure.

Cloud computing provides elasticity and self-service provisioning, so instead of purchasing excess capacity that sits unused during slow periods, you can scale capacity up and down in response to spikes and dips in traffic. You can also use your cloud provider’s global network to spread your applications closer to users worldwide.

Cloud computing enables organizations to use various technologies and the most up-to-date innovations to gain a competitive edge. For instance, in retail, banking and other customer-facing industries, generative AI-powered virtual assistants deployed over the cloud can deliver better customer response time and free up teams to focus on higher-level work. In manufacturing, teams can collaborate and use cloud-based software to monitor real-time data across logistics and supply chain processes.

The origins of cloud computing technology go back to the early 1960s when  Dr. Joseph Carl Robnett Licklider  (link resides outside ibm.com), an American computer scientist and psychologist known as the "father of cloud computing", introduced the earliest ideas of global networking in a series of memos discussing an Intergalactic Computer Network. However, it wasn’t until the early 2000s that modern cloud infrastructure for business emerged.

In 2002, Amazon Web Services started cloud-based storage and computing services. In 2006, it introduced Elastic Compute Cloud (EC2), an offering that allowed users to rent virtual computers to run their applications. That same year, Google introduced the Google Apps suite (now called Google Workspace), a collection of SaaS productivity applications. In 2009, Microsoft started its first SaaS application, Microsoft Office 2011. Today,  Gartner predicts  worldwide end-user spending on the public cloud will total USD 679 billion and is projected to exceed USD 1 trillion in 2027 (link resides outside ibm.com).

The following are a few of the most integral components of today’s modern cloud computing architecture.

CSPs own and operate remote data centers that house physical or bare metal servers , cloud storage systems and other physical hardware that create the underlying infrastructure and provide the physical foundation for cloud computing.

In cloud computing, high-speed networking connections are crucial. Typically, an internet connection known as a wide-area network (WAN) connects front-end users (for example, client-side interface made visible through web-enabled devices) with back-end functions (for example, data centers and cloud-based applications and services). Other advanced cloud computing networking technologies, including load balancers , content delivery networks (CDNs) and software-defined networking (SDN) , are also incorporated to ensure data flows quickly, easily and securely between front-end users and back-end resources. 

Cloud computing relies heavily on the virtualization of IT infrastructure —servers, operating system software, networking and other infrastructure that’s abstracted using special software so that it can be pooled and divided irrespective of physical hardware boundaries. For example, a single hardware server can be divided into multiple virtual servers . Virtualization enables cloud providers to make maximum use of their data center resources. 

IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service), SaaS (Software-as-a-Service) and serverless computing are the most common models of cloud services, and it’s not uncommon for an organization to use some combination of all four.

IaaS (Infrastructure-as-a-Service) provides on-demand access to fundamental computing resources—physical and virtual servers, networking and storage—over the internet on a pay-as-you-go basis. IaaS enables end users to scale and shrink resources on an as-needed basis, reducing the need for high up-front capital expenditures or unnecessary on-premises or "owned" infrastructure and for overbuying resources to accommodate periodic spikes in usage. 

According to a  Business Research Company report  (link resides outside ibm.com), the IaaS market is predicted to grow rapidly in the next few years, growing to $212.34 billion in 2028 at a compound annual growth rate (CAGR) of 14.2%. 

PaaS (Platform-as-a-Service) provides software developers with an on-demand platform—hardware, complete software stack, infrastructure and development tools—for running, developing and managing applications without the cost, complexity and inflexibility of maintaining that platform on-premises. With PaaS, the cloud provider hosts everything at their data center. These include servers, networks, storage, operating system software, middleware  and databases. Developers simply pick from a menu to spin up servers and environments they need to run, build, test, deploy, maintain, update and scale applications.

Today, PaaS is typically built around  container s , a virtualized compute model one step removed from virtual servers. Containers virtualize the operating system, enabling developers to package the application with only the operating system services it needs to run on any platform without modification and the need for middleware.

Red Hat® OpenShift ® is a popular PaaS built around  Docker  containers and  Kubernetes , an open source container orchestration solution that automates deployment, scaling, load balancing and more for container-based applications.

SaaS (Software-as-a-Service) , also known as cloud-based software or cloud applications, is application software hosted in the cloud. Users access SaaS through a web browser, a dedicated desktop client or an API that integrates with a desktop or mobile operating system. Cloud service providers offer SaaS based on a monthly or annual subscription fee. They may also provide these services through pay-per-usage pricing. 

In addition to the cost savings, time-to-value and scalability benefits of cloud, SaaS offers the following:

• Automatic upgrades:  With SaaS, users use new features when the cloud service provider adds them without orchestrating an on-premises upgrade.
• Protection from data loss:  Because SaaS stores application data in the cloud with the application, users don’t lose data if their device crashes or breaks.

SaaS is the primary delivery model for most commercial software today. Hundreds of SaaS solutions exist, from focused industry and broad administrative (for example, Salesforce) to robust enterprise database and artificial intelligence (AI) software. According to an International Data Center (IDC) survey (the link resides outside IBM), SaaS applications represent the largest cloud computing segment, accounting for more than 48% of the $778 billion worldwide cloud software revenue.

Serverless computing , or simply serverless, is a cloud computing model that offloads all the back-end infrastructure management tasks, including provisioning, scaling, scheduling and patching to the cloud provider. This frees developers to focus all their time and effort on the code and business logic specific to their applications.

Moreover, serverless runs application code on a per-request basis only and automatically scales the supporting infrastructure up and down in response to the number of requests. With serverless, customers pay only for the resources used when the application runs; they never pay for idle capacity. 

FaaS, or Function-as-a-Service , is often confused with serverless computing when, in fact, it’s a subset of serverless. FaaS allows developers to run portions of application code (called functions) in response to specific events. Everything besides the code—physical hardware, virtual machine (VM) operating system and web server software management—is provisioned automatically by the cloud service provider in real-time as the code runs and is spun back down once the execution is complete. Billing starts when execution starts and stops when execution stops.

A  public cloud is a type of cloud computing in which a cloud service provider makes computing resources available to users over the public internet. These include SaaS applications, individual  virtual machines (VMs) , bare metal computing hardware, complete enterprise-grade infrastructures and development platforms. These resources might be accessible for free or according to subscription-based or pay-per-usage pricing models.

The public cloud provider owns, manages and assumes all responsibility for the data centers, hardware and infrastructure on which its customers’ workloads run. It typically provides high-bandwidth network connectivity to ensure high performance and rapid access to applications and data.

Public cloud is a  multi-tenant environment  where all customers pool and share the cloud provider’s data center infrastructure and other resources. In the world of the leading public cloud vendors, such as Amazon Web Services (AWS), Google Cloud, IBM Cloud®, Microsoft Azure and Oracle Cloud, these customers can number in the millions.

Most enterprises have moved portions of their computing infrastructure to the public cloud since public cloud services are elastic and readily scalable, flexibly adjusting to meet changing workload demands. The promise of greater efficiency and cost savings through paying only for what they use attracts customers to the public cloud. Still, others seek to reduce spending on hardware and on-premises infrastructure.  Gartner predicts  (link resides outside ibm.com) that by 2026, 75% of organizations will adopt a digital transformation model predicated on cloud as the fundamental underlying platform. 

A  private cloud is a cloud environment where all cloud infrastructure and computing resources are dedicated to one customer only. Private cloud combines many benefits of cloud computing—including elasticity, scalability and ease of service delivery—with the access control, security and resource customization of on-premises infrastructure.

A private cloud is typically hosted on-premises in the customer’s data center. However, it can also be hosted on an independent cloud provider’s infrastructure or built on rented infrastructure housed in an offsite data center.

Many companies choose a private cloud over a public cloud environment to meet their regulatory compliance requirements. Entities like government agencies, healthcare organizations and financial institutions often opt for private cloud settings for workloads that deal with confidential documents, personally identifiable information (PII), intellectual property, medical records, financial data or other sensitive data.

By building private cloud architecture according to  cloud-native  principles, an organization can quickly move workloads to a public cloud or run them within a hybrid cloud (see below) environment whenever ready.

A  hybrid cloud is just what it sounds like: a combination of public cloud, private cloud and on-premises environments. Specifically (and ideally), a hybrid cloud connects a combination of these three environments into a single, flexible infrastructure for running the organization’s applications and workloads. 

At first, organizations turned to hybrid cloud computing models primarily to migrate portions of their on-premises data into private cloud infrastructure and then connect that infrastructure to public cloud infrastructure hosted off-premises by cloud vendors. This process was done through a packaged hybrid cloud solution like Red Hat® OpenShift® or middleware and IT management tools to create a " single pane of glass ." Teams and administrators rely on this unified dashboard to view their applications, networks and systems.

Today, hybrid cloud architecture has expanded beyond physical connectivity and cloud migration to offer a flexible, secure and cost-effective environment that supports the portability and automated deployment of workloads across multiple environments. This feature enables an organization to meet its technical and business objectives more effectively and cost-efficiently than with a public or private cloud alone. For instance, a hybrid cloud environment is ideal for DevOps and other teams to develop and test web applications. This frees organizations from purchasing and expanding the on-premises physical hardware needed to run application testing, offering faster time to market. Once a team has developed an application in the public cloud, they may move it to a private cloud environment based on business needs or security factors.

A public cloud also allows companies to quickly scale resources in response to unplanned spikes in traffic without impacting private cloud workloads, a feature known as cloud bursting. Streaming channels like Amazon use cloud bursting to support the increased viewership traffic when they start new shows.

Most enterprise organizations today rely on a hybrid cloud model because it offers greater flexibility, scalability and cost optimization than traditional on-premises infrastructure setups. According to the  IBM Transformation Index: State of Cloud , more than 77% of businesses and IT professionals have adopted a hybrid cloud approach.

To learn more about the differences between public, private and hybrid cloud, check out “ Public cloud vs. private cloud vs. hybrid cloud: What’s the difference? ”

Watch the IBM hybrid cloud architecture video series.

Multicloud uses two or more clouds from two or more different cloud providers. A multicloud environment can be as simple as email SaaS from one vendor and image editing SaaS from another. But when enterprises talk about multicloud, they typically refer to using multiple cloud services—including SaaS, PaaS and IaaS services—from two or more leading public cloud providers. 

Organizations choose multicloud to avoid vendor lock-in, to have more services to select from and to access more innovation. With multicloud, organizations can choose and customize a unique set of cloud features and services to meet their business needs. This freedom of choice includes selecting “best-of-breed” technologies from any CSP, as needed or as they emerge, rather than being locked into offering from a single vendor. For example, an organization may choose AWS for its global reach with web-hosting, IBM Cloud for data analytics and machine learning platforms and Microsoft Azure for its security features.

A multicloud environment also reduces exposure to licensing, security and compatibility issues that can result from " shadow IT "— any software, hardware or IT resource used on an enterprise network without the IT department’s approval and often without IT’s knowledge or oversight.

Today, most enterprise organizations use a hybrid multicloud model. Apart from the flexibility to choose the most cost-effective cloud service, hybrid multicloud offers the most control over workload deployment, enabling organizations to operate more efficiently, improve performance and optimize costs. According to an  IBM® Institute for Business Value study , the value derived from a full hybrid multicloud platform technology and operating model at scale is two-and-a-half times the value derived from a single-platform, single-cloud vendor approach. 

Yet the modern hybrid multicloud model comes with more complexity. The more clouds you use—each with its own management tools, data transmission rates and security protocols—the more difficult it can be to manage your environment. With  over 97% of enterprises operating on more than one cloud  and most organizations running  10 or more clouds , a hybrid cloud management approach has become crucial. Hybrid multicloud management platforms provide visibility across multiple provider clouds through a central dashboard where development teams can see their projects and deployments, operations teams can monitor clusters and nodes and the cybersecurity staff can monitor for threats.

Learn more about hybrid cloud management.

Traditionally, security concerns have been the primary obstacle for organizations considering cloud services, mainly public cloud services. Maintaining cloud security demands different procedures and employee skillsets than in legacy IT environments. Some cloud security best practices include the following:

• Shared responsibility for security:  Generally, the cloud service provider is responsible for securing cloud infrastructure, and the customer is responsible for protecting its data within the cloud. However, it’s also essential to clearly define data ownership between private and public third parties.
• Data encryption:  Data should be encrypted while at rest, in transit and in use. Customers need to maintain complete control over security keys and hardware security modules.
• Collaborative management:  Proper communication and clear, understandable processes between IT, operations and security teams will ensure seamless cloud integrations that are secure and sustainable.
• Security and compliance monitoring:  This begins with understanding all regulatory compliance standards applicable to your industry and establishing active monitoring of all connected systems and cloud-based services to maintain visibility of all data exchanges across all environments, on-premises, private cloud, hybrid cloud and edge.

Cloud security is constantly changing to keep pace with new threats. Today’s CSPs offer a wide array of cloud security management tools, including the following:  

• Identity and access management (IAM):  IAM   tools and services that automate policy-driven enforcement protocols for all users attempting to access both on-premises and cloud-based services. 
• Data loss prevention (DLP): DLP services that combine remediation alerts data encryption and other preventive measures to protect all stored data, whether at rest or in motion.
• Security information and event management (SIEM) :   SIEM is a comprehensive security orchestration solution that automates threat monitoring, detection and response in cloud-based environments. SIEM technology uses artificial intelligence (AI)-driven technologies to correlate log data across multiple platforms and digital assets. This allows IT teams to successfully apply their network security protocols, enabling them to react to potential threats quickly.
• Automated data compliance platforms:   Automated software solutions provide compliance controls and centralized data collection to help organizations adhere to regulations specific to their industry. Regular compliance updates can be baked into these platforms so organizations can adapt to ever-changing regulatory compliance standards.

Learn more about cloud security.

Sustainability in business , a company’s strategy to reduce negative environmental impact from their operations in a particular market, has become an essential corporate governance mandate.  Moreover, Gartner predicts  (link resides outside ibm.com) that by 2025, the carbon emissions of hyperscale cloud services will be a top-three criterion in cloud purchase decisions.

As companies strive to advance their sustainability objectives, cloud computing has evolved to play a significant role in helping them reduce their carbon emissions and manage climate-related risks. For instance, traditional data centers require power supplies and cooling systems, which depend on large amounts of electrical power. By migrating IT resources and applications to the cloud, organizations only enhance operational and cost efficiencies and boost overall energy efficiency through pooled CSP resources.

All major cloud players have made net-zero commitments to reduce their carbon footprints and help clients reduce the energy they typically consume using an on-premises setup. For instance, IBM is driven by  sustainable procurement  initiatives to reach NetZero by 2030. By 2025, IBM Cloud worldwide data centers  will comprise energy procurement drawn from 75% renewable sources .

According to an  International Data Corporation (IDC) forecast  (link resides outside ibm.com), worldwide spending on the whole cloud opportunity (offerings, infrastructure and services) will surpass USD 1 trillion in 2024 while sustaining a double-digit compound annual growth rate (CAGR) of 15.7%. Here are some of the main ways businesses are benefitting from cloud computing: 

• Scale infrastructure:  Allocate resources up or down quickly and easily in response to changes in business demands.
• Enable business continuity and disaster recovery:  Cloud computing provides cost-effective redundancy to protect data against system failures and the physical distance required to apply disaster recovery strategies and recover data and applications during a local outage or disaster. All of the major public cloud providers offer Disaster-Recovery-as-a-Service (DRaaS) .
• Build and test cloud-native applications : For development teams adopting Agile,  DevOps  or  DevSecOps to streamline development, the cloud offers on-demand end-user self-service that prevents operations tasks, such as spinning up development and test servers, from becoming development bottlenecks.
• Support edge and IoT environments:  Address latency challenges and reduce downtime by bringing data sources closer to the edge . Support Internet of Things (IoT) devices (for example, patient monitoring devices and sensors on a production line) to gather real-time data.
• Leverage cutting-edge technologies:  Cloud computing supports storing and processing huge volumes of data at high speeds—much more storage and computing capacity than most organizations can or want to purchase and deploy on-premises. These high-performance resources support technologies like  blockchain , quantum computing and  large language models (LLMs ) that power generative AI platforms like customer service automation. 

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Let IBM Cloud manage your infrastructure while you manage your environment. Pay only for what you use.

Tackle large-scale, compute-intensive challenges and speed time to insight with hybrid cloud HPC solutions.

An industry-specific cloud, built to support your unique modernization and AI transformation needs.

Hybrid cloud integrates public cloud services, private cloud services and on-premises infrastructure into a single distributed computing environment.

DevOps speeds delivery of higher quality software by combining and automating the work of software development and IT operations teams.

Cloud migration is the process of relocating an organization’s data, applications, and workloads to a cloud infrastructure.

Although cloud computing is only a different way to deliver computer resources rather than a new technology, it has sparked a revolution in the way organizations provide information and service.

Determining the best cloud computing architecture for enterprise business is critical for overall success. That’s why it is essential to compare the different functionalities of private cloud versus public cloud versus hybrid cloud.

We're excited to introduce a three-part lightboarding video series that will delve into the world of hybrid cloud architecture. In this intro video, our guide, Sai Vennam, lays out the three major hybrid cloud architecture issues that we're going to cover: Connectivity, Modernization and Security.

Designed for industry, security and the freedom to build and run anywhere, IBM Cloud is a full stack cloud platform with over 170 products and services covering data, containers, AI, IoT and blockchain. Use IBM Cloud to build scalable infrastructure at a lower cost, deploy new applications instantly and scale up workloads based on demand.

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Top 22 Cloud Computing Project Ideas in 2024 [Source Code]

Home Blog Cloud Computing Top 22 Cloud Computing Project Ideas in 2024 [Source Code]

The simplest and most effective way to gain proficiency in a domain is to focus on getting hands-on experience. When you work on live projects, you face real issues, gain familiarity with the actual scenarios, and gain expert-level understanding. So, when you plan and start your career in the cloud industry, you should work on a cloud computing project. It will help you understand the industry better. Moreover, you learn about the future scope of cloud computing. Based on this experience, you can choose the certifications that can boost your career and help you fetch excellent job opportunities. The idea behind working on cloud computing projects is to understand the field and plan the professional journey to get fruitful results.  

In this article, we will discuss what is a cloud computing project, list of cloud computing project ideas based on skills, and a few examples for better understanding.  

List of Cloud Computing Projects Ideas in 2024

Here is a list of curated cloud computing projects for all level skills, one should know in 2024:

• Cloud-enabled attendance system
• Online blood bank system
• Online cloud-enabled bookstore system
• Data redundancy removal system
• Detecting data leaks using SQL injection
• Cloud-based bus pass system
• Making a chatbot
• Secure text transfer
• Bug tracking functionality

Top Cloud Computing Projects [Based on Levels]

Learning cloud computing starts with getting hands-on experience. Check out the and get started with the cloud: 

1. Cloud-enabled attendance system

We can use a cloud-enabled automatic attendance system to scan details. Also, all the scanned information can be directly synchronized and stored on the cloud in real-time. Detailed information like check-in time, check-out time, date, and total working hours, to name a few, can be stored and saved. Administrators must register new students/employees on the system and provide some personal information. 

Source Code:  Cloud-Enabled Attendance System

Advantages  Of a Cloud-Enabled Attendance System: 

• Data and Analytics: You can easily generate reports 
• Flexibility: You can track attendance in a variety of ways 
• Remote management: Cloud-based attendance systems make use of software that can be accessed from anywhere on any device that has Internet access. 

Disadvantages  Of a Cloud-Enabled Attendance System: 

• Not effective in monitoring buddy punching: This software is ineffective at detecting buddy punching. There is a greater possibility of malpractice occurring here. However, if it is equipped with biometric technology, it can be properly monitored. 
• Difficult to maintain and repair:nMaintaining and repairing software is difficult. Though it may be uncommon, once damaged, there will be costs associated with repairing it. 
• Ineffective when there is no power supply: Without a power supply, the software is of no use. The entire system is powered by electricity. This is not the case with the traditional method of taking attendance. 

2. Online blood bank system

Using cloud computing, we can create a central repository for numerous blood deposits, including blood details and depositor information. The blood details would include blood type, storage area, and storage date to help maintain and monitor the blood depositors. This cloud-based system would allow for greater transparency in determining the availability of the desired blood depositor. This system will also contain patient and contact information. 

Source Code : Online Blood Bank System

Advantages of Online Blood Bank System 

• Error probability is reduced to a minimum. 
• Easy and effective information retrieval. 
• The system shows the blood nearing expiry and those that have expired. Hence the unhealthy blood can easily be discarded. 

3. Online cloud-enabled bookstore system

This system can function as an internet bookstore by utilizing SQL and C#. The books would be divided into sections to help users find their desired book without becoming overwhelmed by a database. Additionally, the bookstore records additional information such as a brief synopsis of the books. A notification system is added to help users stay up to date on their eagerly anticipated books and their availability. 

Source Code: Online Cloud-Enabled Bookstore System

Advantages  of Online Cloud-Enabled Book Store System 

• Lower costs as users are not required to purchase a powerful computer or server to support the system's operation. 
• Lower barriers to use. uses the service through the user's browser, the overall interface will be clearer and clearer, and the display effect of each functional module will be more intuitive and adapt to the user’s device 
• Higher security as maintenance of the server is the responsibility of the system supplier. 

4. Data redundancy removal system

This project is focused on accurately removing unnecessary and redundant data in a short amount of time. It accomplishes this by classifying the test data as redundant or false positive. Also, the cloud-enabled system validates the newly-added data to keep the database free from duplicity. If the data is not found in the database, new data gets appended.

Source Code:  Data redundancy removal system

Advantages  of Data Redundancy Removal System 

• Alternative data backup method 
• Better data security 
• Faster data access and updates 
• Improved reliability 

5. Detecting data leaks using SQL injection

This cloud-enabled data leak detection system operates over the Internet and does not require any particular system configuration. The system aims to enhance security and provide measures against SQL injection hacking. By storing users’ information in AES 256 encryption form, it meets all the security needs. It injects SQL through a capability code and establishes a connection between the cloud server and the application itself; this system doubles the security against it.

Source Code:  Data Leakage Detection

Advantages  of This Project 

• Get 100% database security and detect data leakers effortlessly. 
• Distributors can easily identify counterfeit agents leaking their confidential data and take strict action against them. 

6. Cloud-based bus pass system

It is a cloud-based adaptation of purchasing tickets over the Internet. This solves many common problems, such as misplaced, stolen, or incorrectly priced tickets. In addition, if the load on a typical bus booking website is too high, the website chokes and stops working. However, an additional load can be handled by provisioning new servers in the computing. 

Source Code:  Cloud-based Bus Pass System

Advantages of Cloud-based Bus Pass System 

• Allows customers to check the availability of bus tickets before purchasing them 
• Secure. Passengers must first register with the system to verify their identity. After they have been verified, the system allows them to book passes for any route online. 
• Users can recharge using their credit/debit cards. 

7. Making a chatbot

A chatbot is an AI-enabled software designed to interact with users when they visit a website. These bots are assigned to websites to streamline user interaction when they land on the website for the first time. The goal is to provide real-time and immediate responses to customer inquiries. To work on the chatbot application, you can use retrieval-based or generative-based models. If you want to use the chatbot on a commercial website, you should pre-define the input patterns.

Source Code:  Chatbot

Advantages  of Chatbots 

• Seamless live communication 
• Reduced people-to-people interactions 
• Makes customer service available 24/7

8. Secure text transfer 

Encryption is essential to protect confidential data safe against unauthorized access or misuse. This encryption safeguards confidential information in a key-password combination. This combination employs Diffie-Hellman key exchange, which applies to private and public encryption concepts.

This project can be used to exchange text messages while maintaining maximum security and speed. This system can be modified and repurposed to work for image exchange. SQL databases to store all information for exchange strengthen the entire system.

Source Code:  Secure Text Transfer

Advantages of Secure Text Transfer System 

• Content is encrypted to prevent access by hackers and unauthorized people. 
• .NET framework simplifies the development process. 

9. Bug tracking functionality

Using cloud computing, developers could identify the type and origin of bugs by simply logging into the application. The project will be divided into three parts: customer, administrator, and staff. 

By entering a username and password, the customer will create an account. They can log in to the bug tracking application with their credentials and send a bug report with screenshots of the bugs they encountered. Staff can log in using their respective accounts to view bugs and determine whether they need to be fixed. And administrators can contact the user directly about the bugs they sent and quickly resolve them. Depending on the load of the reports, this can vary significantly. 

Source Code:  Bug Tracking System

Advantages  of Bug Tracking System 

• Deliver a high-quality product. 
• Better communication and connectivity. 
• Better customer service. 

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Cloud Computing Projects for Beginners

Are you new to the cloud and looking to explore your knowledge in cloud computing? There is no better way than trying some hands-on experience with a few basic projects. Here is a list of cloud computing projects for beginners that you must certainly give it a try. 

1. Attendance tracking 

This allows schools, colleges, institutions, and even offices to keep track of students' and employees' absences. Students and employees can mark their attendance by logging in, which is saved in the database and can later be checked by the institute's office. 

Source Code: Attendance Tracking

2. Bus ticketing 

Allow passengers to book bus tickets remotely. There will be no more hassles or concerns if the ticket is misplaced. Distributing tickets and passes to passengers can be done quickly and seamlessly. Also, passengers can use the bus ticketing app to check updates such as seat availability, schedules and timings, discounts, and much more. 

Source Code: Bus Ticketing

3. Automation of university or college data 

This project will assist you in creating a portal for a university or college. This portal allows them to register students, track their placements in various companies, and view their final results. 

While it provides separate login portals for teachers and students, it also serves as a liaison between staff, students, and companies to deliver necessary information, collect feedback, declares results, etc. 

Source Code: Automation of University

4. Personal cloud 

You can create a personal cloud server with this project. Raspberry Pi and a Micro SD card will be required to build a private cloud. The hard drive will be the primary cloud storage in this project, and it will help you understand how a cloud server works. 

Source Code: Personal Cloud

5. Android Offloading 

Installing and offloading the processing requirements of an application is strenuous and time-consuming. The android offloading project aims to solve the problem by making it easy for applications to overload the compute parts explicitly. Using static analysis, this framework enhances an app's functionality. Users can choose a process and files to be encrypted and stored in the cloud. Visit AWS Cloud Practitioner Essentials Certification Training and learn AWS from scratch.

Source Code: Android Offloading

Intermediate Cloud Computing Projects with Source Code

Suppose you have a basic understanding of the cloud basics and you are comfortable working with computing, storage, and security. In that case, you must try a step forward than the entry-level projects. Here is the list of intermediate cloud computing projects from GitHub with source code. Let us check each in detail: 

1. Online blood bank system 

This cloud-based application serves as a central information database for the various blood deposits, including the donor's name and blood type information. The cloud can also store information such as blood type, storage data, blood type availability in a given area, etc. This facilitates quick access to blood in an emergency. 

GitHub Source Code: Online Blood Bank System  

2. Information Chatbot 

Most companies have implemented chatbots on their websites to improve customer service and increase efficiency. In this project, you will create a chatbot in Python that will interact with users, answer their questions, and collect data that you will save in a cloud database. 

GitHub Source Code: Information Chatbot  

3. Online bookstore 

This application can keep a catalog of books with the title, author, price, and even the ability to read them online. For the convenience of the customers, the books can be classified according to several criteria, such as author, genre, year of publication, and so on. 

GitHub Source Code: Online Bookstore  

4. E-learning 

Online education platforms are nothing new to today's generation. These platforms have their advantages, resources, and time and cost flexibility and thus rank among the most popular learning mediums. Converting the project to a cloud project can drastically reduce costs. A learning space where study materials and relevant videos are kept for the learner's benefit. They are available for students to access and use as needed. 

GitHub Source Code: E-learning  

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Advanced Cloud Computing Project Ideas with Source Code

If you are a professional and have a sound understanding of cloud technologies, then you must opt for advanced cloud computing projects to elevate your skills to the next level. Here are a few hard-to-crack cloud computing projects with source code: 

1. Bug tracking 

Bug tracking is a project aimed at detecting and tracking the type and location of a bug on a website or app. Some common real-world applications designed using this concept include Backlog and Zoho bug tracker. 

GitHub Source Code: Bug tracking  

2. File storage system using hybrid cryptography

The project's goal is to secure the files using hybrid cryptography. Such applications are used in banking applications and systems to protect information and data sets. 

You can encrypt the files with Blowfish because it is accurate and fast. Use symmetric algorithms for decryption. Even in remote servers, the hybrid technique can provide exceptional cloud security. With this project, you can add data security to your skill set, which is in high demand due to the increased frequency of security risks and attacks. Cryptography will be used to convert the data sets into unreadable forms. 

GitHub Source Code: File storage system

3. Rural banking 

This cloud project aims to create a cloud-based banking system for rural areas where banking facilities and amenities are inadequate to provide people with banking convenience.

GitHub Source Code: Rural banking

4. Data leaks 

SQL injection refers to data leakage in the database as a common business problem. It is an excellent portal for anyone working or planning to work as an e-commerce platform. The primary aim of SQL injectors is to safeguard data and secure the privacy of the information from scammers. Developers employ standard encryption technology to create this SQL injection system

GitHub Source Code: Data leaks

Best Platforms to Work on Cloud Computing Project   

Cloud offers different platforms on which you can run your projects. These platforms provide specific features based on which you can handle projects where you need to manage those particular aspects. Some of the cloud computing project platforms are:  

• Microsoft Azure:  Azure provides a wide range of services, making it the most accessible platform in the cloud environment. Any organization with any requirements can opt for Microsoft Azure as it will cater to all of them. It would be fair to say that Microsoft Azure is a dependable option for enterprises.  
• Google Cloud:  This platform provides new-age companies with a trustworthy, user-friendly, and protective cloud environment to the organizations. You get enough services in Google Cloud to cater to all the IaaS or PaaS requirements.  
• IBM Cloud:  The three models that IBM Cloud primarily focuses on are IaaS (infrastructure as a service), SaaS (software as a service), and PaaS (platform as a service). It is a cost-effective platform where you can make an adjustment to reduce the overall expense.  

Importance of Cloud Computing Projects

Whether you a professional getting started with cloud computing or an experienced folk with experience in the cloud, these projects will help you streamline your learning process in many ways. Check out the importance of cloud computing projects and why it is a must for you: 

• Cloud computing applications cover many domains, technologies, scales, and applications. Cloud computing mini projects or real-time cloud computing projects will provide adequate exposure and experience with cloud technologies. 
• With the massive expansion of both technologies, virtualization and cloud computing projects are in high demand. Cloud computing has several applications in terms of programming languages and frameworks. Java cloud computing projects, Android cloud computing projects, PHP cloud computing projects, and other popular programming languages can be developed. 
• Cloud computing projects for students have many applications in their academic careers. Cloud delivery and deployment models can be used to develop cloud computing projects for final-year engineering or cloud computing projects for MTech. Cloud computing projects are used in entertainment, education, healthcare, retail, banking, marketing, and other industrial and business domains. 

Factors Affecting Cloud Computing

Cloud computing based on the pay-as-you-go model is affected by a number of factors. Let us discuss each in brief: 

• Cost:  The developers must keep in mind that it must be cost-effective and allow the company to achieve cost-saving benefits. Most businesses choose Cloud Computing because it is less expensive. 
• Application in the future:  Its potential applications should be designed so that they not only benefit the company in terms of current needs but are also adaptable enough to benefit the organization in the future as changes occur. 
• Mobility:  It is essential to design a Cloud Computing project to be easily moved between private and public clouds to check and access resources or data. 
• Security:  Security is the top priority when considering the entire aspect of data and resources. As a result, data security should be prioritized while a project is being developed. 
• Increased bandwidth:  When working in the cloud, it is important to consider increased bandwidth. Increased bandwidth significantly reduces transfer times, especially when handling big chunks of data.

I hope, we have covered the top cloud computing projects along with source code. Cloud is a high-demand domain with an increasing number of opportunities. Companies are switching to cloud environments because of the accessibility and data safety features. So, it would be fruitful to consider planning a career in this domain. If you can gain proficiency and prove your worth in the market, you can enjoy a monetarily sound and secure professional career. Start by getting all the information about this industry and find projects that can give you the right kind of experience. You can also join Cloud Computing certification courses that can train you in the right tools and techniques to help you establish a promising professional career in the cloud. If you plan everything strategically, your dream job is not far-fetched.

Frequently Asked Questions (FAQs)

These are the projects one must do to know how the notions of cloud computing can be applied in the real world. 

Here are some cloud computing projects for beginners that you can build to learn more about the technology while also having fun: 

 A human-interfaced cloud-based student data chatbot. 

Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

The father of cloud computing is American computer scientist J.C.R. Licklider.

The cost considerations in a cloud computing project include predicting the cost of cloud service. Furthermore, the cost of tools and the expense of individual resources also get included in cost consideration. 

The security considerations in a cloud computing project include network security risks. Furthermore, the cloud relies on shared resources, so you should consider separation and segmentation. 

The common challenges in implementing a cloud computing project include data security and privacy issues, multi-cloud environments, and high network dependencies. 

Kingson Jebaraj

Kingson Jebaraj is a highly respected technology professional, recognized as both a Microsoft Most Valuable Professional (MVP) and an Alibaba Most Valuable Professional. With a wealth of experience in cloud computing, Kingson has collaborated with renowned companies like Microsoft, Reliance Telco, Novartis, Pacific Controls UAE, Alibaba Cloud, and G42 UAE. He specializes in architecting innovative solutions using emerging technologies, including cloud and edge computing, digital transformation, IoT, and programming languages like C, C++, Python, and NLP. 

Avail your free 1:1 mentorship session.

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Computer Science > Software Engineering

Title: cloud native software engineering.

Abstract: Cloud compute adoption has been growing since its inception in the early 2000's with estimates that the size of this market in terms of worldwide spend will increase from \$700 billion in 2021 to \$1.3 trillion in 2025. While there is a significant research activity in many areas of cloud computing technologies, we see little attention being paid to advancing software engineering practices needed to support the current and next generation of cloud native applications. By cloud native, we mean software that is designed and built specifically for deployment to a modern cloud platform. This paper frames the landscape of Cloud Native Software Engineering from a practitioners standpoint, and identifies several software engineering research opportunities that should be investigated. We cover specific engineering challenges associated with software architectures commonly used in cloud applications along with incremental challenges that are expected with emerging IoT/Edge computing use cases.

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arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

• Algorithms & data structures
• Artificial intelligence ( AI )
• Computer networking
• Database systems
• Human-computer interaction
• Information security (IS)
• Software engineering
• Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

• An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
• A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
• An evaluation of machine learning algorithms used for recommender systems in streaming services
• A review of approximation algorithm approaches for solving NP-hard problems
• An analysis of parallel algorithms for high-performance computing of genomic data
• The influence of data structures on optimal algorithm design and performance in Fintech
• A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
• A comparison of streaming algorithm performance for the detection of elephant flows
• A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
• Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
• Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
• A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
• A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
• Exploring the feasibility of applying information theory to feature extraction in retail datasets.
• Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

• Applying deep learning algorithms for speech recognition in speech-impaired children
• A review of the impact of artificial intelligence on decision-making processes in stock valuation
• An evaluation of reinforcement learning algorithms used in the production of video games
• An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
• An analysis of the ethical and social implications of artificial intelligence-based automated marking
• The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
• An examination of the use of artificial intelligence in orthopaedic surgery
• The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
• An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
• A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

• An analysis of the impact of 5G technology on internet penetration in rural Tanzania
• Assessing the role of software-defined networking (SDN) in modern cloud-based computing
• A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
• Exploring the influence of cloud computing on security risks in fintech.
• An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
• Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
• An evaluation of the challenges and opportunities in 6G wireless network adoption
• The role of network congestion control algorithms in improving network performance on streaming platforms
• An analysis of network coding-based approaches for data security
• Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Topics & Ideas: Database Systems

• An analysis of big data management systems and technologies used in B2B marketing
• The impact of NoSQL databases on data management and analysis in smart cities
• An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
• Exploring the role of data warehousing and business intelligence in global consultancies
• An analysis of the use of graph databases for data modelling and analysis in recommendation systems
• The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
• An examination of the challenges and opportunities of distributed databases in supply chain management
• Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
• An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
• Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

• An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
• An exploration of how artificial intelligence is changing human-computer interaction patterns in children
• An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
• Assessing the influence of virtual and augmented reality on consumer purchasing patterns
• An examination of the use of gesture-based interfaces in architecture
• Exploring the impact of ease of use in wearable technology on geriatric user
• Evaluating the ramifications of gamification in the Metaverse
• A systematic review of user experience (UX) design advances associated with Augmented Reality
• A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
• Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Topics & Ideas: Information Security

• A bibliometric review of current trends in cryptography for secure communication
• An analysis of secure multi-party computation protocols and their applications in cloud-based computing
• An investigation of the security of blockchain technology in patient health record tracking
• A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
• A systematic review of secure data storage solutions used for cloud computing in the fintech industry
• An analysis of intrusion detection and prevention systems used in the healthcare sector
• Assessing security best practices for IoT devices in political offices
• An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
• A comparative study of digital signature schemes adoption in property transfers
• An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

• A study of agile software development methodologies and their impact on project success in pharmacology
• Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
• A study of the impact of DevOps practices on software development and delivery in the healthcare sector
• An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
• A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
• An investigation of software testing techniques and methodologies for subscription-based offerings
• A review of software security practices and techniques for protecting against phishing attacks from social media
• An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
• Exploring the impact of software development outsourcing on project success in multinational contexts
• An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

• An array-based optimization framework for query processing and data analytics (Chen, 2021)
• Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
• Embedding constructural documentation in unit tests (Nassif, 2019)
• PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
• Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
• Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
• Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
• Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
• Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
• Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
• Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
• A state-based approach to context modeling and computing (Yue, 2019)
• A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
• HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

10 Comments

Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

Steps on getting this project topic

I want to work with this topic, am requesting materials to guide.

Information Technology -MSc program

It’s really interesting but how can I have access to the materials to guide me through my work?

That’s my problem also.

Investigating the impacts of software refactoring techniques and tools in blockchain-based developments is in my favour. May i get the proper material about that ?

BLOCKCHAIN TECHNOLOGY

I NEED TOPIC

Database Management Systems

Can you give me a Research title for system

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Support engineering in the age of cloud computing: navigating challenges and embracing opportunities.

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Mukul Garg is the Head of Support Engineering at PubNub , which powers apps for virtual work, play, learning and health.

The rapid ascent of cloud computing has fundamentally reshaped IT landscapes across the globe. As organizations transition to cloud-based systems and services, the role of support engineering is undergoing a significant transformation. Support engineers are now faced with a set of unique challenges but also have unprecedented opportunities to enhance their service offerings. This article explores the intricacies of support engineering in the cloud era, providing insights into how professionals can navigate the complexities and leverage emerging opportunities.

Unique Challenges In Cloud-Based Support Engineering

Complexity of cloud architectures.

Cloud environments are inherently complex due to their multi-layered nature and the interplay between various services and platforms. For instance, managing an application on Amazon Web Services (AWS) involves a multitude of components such as EC2 instances, RDS databases and S3 storage. Each of these elements operates within a broader ecosystem, and issues in one area can have cascading effects on others. Support engineers must possess a deep understanding of these components and their interactions. Resources like AWS’s Documentation Overview provide extensive details, but mastering this complexity remains a significant challenge.

Multi-Tenancy And Isolation

Cloud platforms operate on a multi-tenant model where multiple customers share the same physical infrastructure while maintaining logical separation. This model offers efficiency but raises concerns about data isolation and performance interference.

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For example, a performance issue with one tenant's application on Microsoft Azure could potentially impact other tenants if not managed correctly. Engineers must use sophisticated tools and techniques to ensure that support interventions do not inadvertently affect other customers. Azure’s Service Health Dashboard helps in tracking such issues but requires precise handling.

Security And Compliance

Security is a paramount concern in cloud computing. While cloud providers like Google Cloud Platform (GCP) offer robust security features, the onus of configuring and managing these tools often falls on support engineers. They must navigate complex compliance requirements, such as GDPR or HIPAA, and ensure that their cloud environments adhere to these standards. For instance, implementing proper encryption and access controls on Google Cloud’s Security Command Center is crucial for maintaining compliance and security.

Opportunities For Enhancement

Automation and ai integration.

Cloud computing introduces significant opportunities for leveraging automation and artificial intelligence (AI) in support engineering. Automation tools can streamline routine tasks, such as ticket management and initial diagnostics.

For example, ServiceNow’s Virtual Agent uses AI to handle common support queries, allowing engineers to focus on more complex issues. Similarly, AI-driven analytics can predict potential problems before they escalate, enabling proactive support and minimizing downtime. Tools like ServiceNow AI exemplify these advancements.

Global Reach And Scalability

The global nature of cloud computing allows support teams to operate across different time zones, enhancing service availability and collaboration. Companies like IBM use their global support infrastructure to provide 24/7 support for their cloud services. This distributed model not only improves response times but also enables support engineers to leverage diverse expertise, which can be particularly beneficial for addressing complex issues. IBM’s Cloud Support offers insights into how global support teams operate.

Data Analytics And Insight

Cloud environments provide advanced data analytics capabilities that can significantly enhance support operations. For example, Google Cloud’s BigQuery enables support engineers to analyze large datasets to identify trends and recurring issues. By leveraging these insights, support teams can develop more effective strategies for issue resolution and process improvement. BigQuery’s Data Analytics capabilities showcase how data can be used to drive better support outcomes.

Real-World Examples

Netflix’s resilience engineering.

Netflix exemplifies effective support engineering in a cloud environment through its resilience engineering practices. The company employs tools like Chaos Monkey to test the robustness of its cloud infrastructure by intentionally causing failures. This proactive approach helps ensure that their support systems are resilient and capable of handling unexpected issues without impacting user experience. The company goes into more detail about its approach in its Engineering Blog .

Salesforce’s AI-Driven Support

Salesforce has integrated AI into its support operations through its Einstein platform . Einstein automates routine support tasks and provides engineers with actionable insights into customer issues. This integration not only speeds up issue resolution but also enhances customer satisfaction by addressing complex problems more effectively.

The shift to cloud computing presents both challenges and opportunities for support engineering. While the complexity of cloud environments, multi-tenancy issues and security concerns pose significant hurdles, advancements in automation, AI and global collaboration offer valuable tools for overcoming these challenges. By embracing these opportunities and adapting to new technologies, support engineers can enhance their service capabilities and drive success in the cloud-driven world.

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An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective

ISBN: 978-1-119-57491-0

October 2020

Wiley-IEEE Computer Society Pr

Digital Evaluation Copy

Danny Weyns

A concise and practical introduction to the foundations and engineering principles of self-adaptation

Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems.

It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems.

The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as:

• An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems
• End-of-chapter exercises at four different levels of complexity and difficulty
• An accompanying author-hosted website with slides, selected exercises and solutions, models, and code

Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.

DANNY WEYNS, P H D, is a Professor at Katholieke Universiteit (KU) Leuven, Department of Computer Science, Leuven, Belgium. He obtained his doctorate from KU Leuven. He focuses on software engineering of trustworthy self-adaptive systems, exploiting design models and verification techniques at runtime.