case study on cloud computing

Airline evolves customer experience with IBM public cloud platform and services.

UBank shrinks time to market — builds a loan app virtual assistant on IBM Cloud platform.

Filter by Industry

The American Association of Insurance Services partnered with IBM to create an open blockchain network that streamlines regulatory reporting. The network provides new insights for insurers, while also enhancing timeliness, accuracy and value for regulators.

With IBM Cloud bare metal server infrastructure hosted worldwide and the Veeam on IBM Cloud backup and restore service, Movius provides its multiline offering to enterprises around the globe.

To transform its service desk operations, banking group Creval deployed a virtual assistant, powered by IBM Watson technology, that reduced service desk calls by 80 percent and allowed staff to focus on high-value tasks that drive customer service excellence.

To help ensure clients can access the latest pricing and execute trades rapidly and accurately, online broker ActivTrades migrated its primary trading platforms from on-premises infrastructure to IBM Cloud for VMware solutions.

Allianz wanted a mobile assistant solution that worked across platforms to better serve customers. Using IBM Cloud and IBM Watson Assistant, the company created an AI-powered virtual assistant that can field 80 percent of its most frequent customer requests — for real help in real time.

IBM is helping American Airlines migrate some of its critical applications to the IBM Cloud while using new methodology to create innovative applications quickly and improve the customer experience.

To help its clients focus on strategic activities rather than low-value tasks, Contextor teamed up with IBM to augment its robotic process automation solutions with artificial intelligence capabilities.

To help state healthcare agencies address new regulations, Deloitte teamed with IBM to develop the Medicaid Enterprise Solution (MES) HealthInteractive Platform, running on IBM Cloud technology. With MES, state Medicaid programs can keep IT up to date with less effort and expense, while also aligning with federal guidance.

A Japanese airline has become the first among its competitors to develop a web-based chatbot proof of concept, generating real dialogs with 90 percent of users and confirming the company’s vision for broader cognitive applications with IBM Watson Assistant (formerly IBM Watson Conversation) and Watson Natural Language Classifier services.

Active International used the IBM Cloud to develop applications that optimize its media buying cycle and help it identify new business prospects more effectively.

Anthem partnered with IBM to drive its digital transformation and deliver an enhanced digital experience for its nearly 40 million consumers.

Assima helps employees work smarter by arming them with an intelligent application overlay hosted in the IBM Cloud and delivering AI capabilities with IBM Watson technology.

To help small and midsized businesses with liquidity management and planning, Asteria created a smart cashflow service running on scalable IBM Cloud infrastructure. With its IBM Cloud solution, the company can work in a flexible, open-source development framework while also addressing customer needs for security-rich data hosting.

Buzz Radar created a platform called the Cognitive Command Center — a digital marketing monitoring, analytics and visualization platform that harnesses IBM Watson technologies and runs in the IBM Cloud.

After working with IBM to build a cloud data warehouse and analytics architecture, Constance Hotels, Resorts & Golf can now gain data-driven insights from across its nine properties.

Building on a long track record of service innovation, ExxonMobil engaged an IBM iX team to help design and launch ExxonMobilRewards+, the industry’s first smartphone app for digital payment at the pump. The solution’s IBM Cloud public hosting platform reduces operating costs for the app by 40 percent and scales effortlessly as its user base continues to grow.

LogDNA saw a clear need to address data sprawl in the modern, cloud-native development stack. Its innovative software-as-a-service (SaaS) platform built on Kubernetes caught the attention of the IBM Cloud team, which wove it into its global framework. As both an IBM Business Partner and a client, LogDNA was able to grow and strengthen its DevOps capabilities.

Ricoh migrated its Unified Communication System operations to IBM Cloud bare metal servers, taking advantage of near-limitless scalability and capacity. This allowed the company to ensure smooth sound and vision for its rapidly expanding customer base.

UBank launched new initiatives in an IBM Cloud Platform environment, including a virtual assistant that incorporates IBM Watson technology to support the bank’s online home loan application.

Cloud Case Studies

Learn how ClearScale customers are leveraging our services to drive innovation by designing, building, deploying, and managing sophisticated cloud applications and infrastructure on AWS

• Advertising and Marketing
• Agriculture
• Architecture and Engineering
• Consumer Services
• Financial Services
• Healthcare and Life Sciences
• Manufacturing
• Media and Entertainment
• Software and Internet
• Telecommunications
• Application Development
• Application Modernization
• Business Applications
• Data and Analytics
• Google Cloud
• Managed Services
• Microsoft Azure
• Mobile and Web
• Windows Workloads
• ACR - Landing Zone
• ACR - Data Lake
• ADCO Electrical Corporation
• AdvisoryCloud
• Axiom Cloud
• BresoTec Inc
• Canoe Intelligence
• CareCentrix
• Center for Advanced Defense Studies
• Cloud Agronomics
• ComissionTrac
• CompoSecure
• Conserve With Us
• Core Group Resources
• CPS - App Development
• CPS - Machine Learning
• Criteria Corp
• DealerSocket
• Decisiv - AWS Infrastructure
• Decisiv - Machine Learning
• Decisiv - Security
• DiscoverX Corporation
• Dollar Tree
• Education.com
• eTeamSponsor
• FieldRoutes
• Fifty Flowers
• First Street Foundation
• Franklin Young
• Gaia Online
• GK Data Solutions
• Globe and Mail
• Hawthorne Effect
• Health-e-MedRecord
• Influence Health
• In Touch EMR
• J.J.Keller & Associates
• Jonas Fitness
• Kohn Pedersen Fox Associates
• MaiaLearning
• Media Company
• Public Broadcasting Service
• QMI Manufacturing
• Quik! - Data Management
• Quik! - MSP
• Quik! - SOC 2 Audit
• RF-SMart - Serverless Computing
• RF-Smart - Disaster Recovery
• ROI Solutions
• San Jose Water Company
• SavvyMoney - Cloud Modernization
• SavvyMoney - MSP
• SavvyMoney - App Modernization
• Shinola Detroit
• Sierra Club
• Spark Networks SE
• Spartan Capital Intelligence
• Spoke Safety
• Terror Films
• The Responsible Minerals Initiative
• The Salvation Army - Mobile App
• The Salvation Army - App Modernization
• Track Revenue
• TriFin Labs
• USA Baseball
• VisualizeHR
• Willamette Dental Group
• World Wildlife Fund
• Young, Black, and Fabulous
• Your OneSource Solution
• Zeta Interactive

Headquarters

50 California Street Suite 1500 San Francisco, CA 94111

O: 800-591-0442

5450 Thornwood Dr. Suite #L San Jose, CA 95123

O: 1-800-591-0442

7887 East Belleview Avenue Suite 1100 Denver, CO 80111

O: 1-303-209-9966

2942 N 24th St. Suite 114 Phoenix, AZ 85016

O: 1-602-560-1198

165 Broadway 23rd Floor New York, NY 10006

O: 1-646-759-3656

11757 Katy Fwy Suite 1300 Houston, TX 77079

O: 1-281-854-2088

100 King St. West Suite 5600 Toronto, Ontario M5X 1C9

O: 1-416-479-5447

Kraków, Poland

Kącik 4 30-549 Kraków Poland

Cloud case studies

From cloud migration to harnessing cloud for innovation, we create 360° value for our clients.

Minna Bank: Japan’s first digital bank

Japan’s digital native consumers don t need a brick and mortar banking experience, so Minna Bank built a different bank for them in the cloud. 

Additional cloud case studies

AXA's claims in the cloud

Building cutting-edge AWS insurance capabilities.

AXA Bank Belgium

Flight path

Future-forward learning and media company

Bold and forward-thinking leaders

Taking silicon to the cloud

MSRB: A people-first approach to cloud

Knowing, improving, rewarding

Modernizing payments via cloud migration

Nationwide Building Society migrates its payments capability to Form3 and AWS to improve its customer experience and minimize downtime.

Carlsberg brews innovation with cloud

Our journey to living in the cloud

West Midlands Police: Serve and protect with cloud

Global jeweler Pandora: Going for cloud

WSIB: Grounded in cloud

Connecting online and offline retail

MONETA Money Bank: Taking the digital lead

• Skip to content
• Skip to search
• Skip to footer

Cisco Cloud and Computing Case Studies

Real customers. Real business transformation with Cisco Compute solutions.

• Search case studies

Contact Cisco

• Get a call from Sales

Call Sales:

• 1-800-553-6387
• US/CAN | 5am-5pm PT
• Product / Technical Support
• Training & Certification

Interstates, Riot Games, and City of Rockingham

Interstates: Escaping chassis refresh cycles

Interstates makes its infrastructure future ready and sustainable with Cisco UCS X-Series servers and Cisco Intersight.

Riot Games: Breaking traditional broadcast molds

Riot Games revolutionizes sports, media, and entertainment with Cisco Compute and Data Center Network technologies.

City of Rockingham: Modernizing IT structure for growth

With IT talent in short supply, City of Rockingham finds new ways to expand its infrastructure and services.

Executive perspectives

NterOne establishes a cloud-operating model with on-premises systems.

E.On scales its data center without scaling staff and operations.

Calvary Health Care

Driving efficiency and innovation in the aged care industry, Calvary Health Care is ready for more growth with Cisco HyperFlex and Cisco Intersight.

Geographic Solutions

Cisco UCS Servers managed with Cisco Intersight helped Geographic Solutions to rapidly scale up its infrastructure.

Cisco distributed IT computing solutions has enabled Riot Games to manage all of its e-sports servers around the world using a single pane of glass.

Kaleida Health

Cisco Intersight fuels efficiencies for a Kaleida data center modernization effort.

All case studies

Sorry, no results matched your search criteria(s). Please try again.

• About   General Information Permissions Company Collaboration Case Competitions Best Case Award Press Releases Access Options Submission Guidelines

Berkeley Haas Case Series

The Berkeley Haas Case Series is a collection of business case studies created by UC Berkeley faculty

• Innovation and technology

The Cloud Computing Industry

Learning objectives.

Pub Date: February 1, 2021

Discipline: Innovation and technology

Subjects: Innovation (342), Internet (347), Business models (256), Computer Software (10241), Computer networks (2337), Applications (3094)

Product #: B5968-PDF-ENG

Industry: Technology

Geography: Silicon Valley, Seattle, United States

Length: 9 page(s)

Recommended

A new collection of business case studies from Berkeley Haas

The aim of the Berkeley Haas Case Series is to incite business innovation by clarifying disruptive trends and questioning the status quo.

10 Important Cloud Migration Case Studies You Need to Know

Aug 1, 2019 | Engineering

For most businesses considering cloud migration, the move is filled with promise and potential. Scalability, flexibility, reliability, cost-effectiveness, improved performance and disaster recovery, and simpler, faster deployment — what’s not to like? 

It’s important to understand that cloud platform benefits come alongside considerable challenges, including the need to improve availability and latency, auto-scale orchestration, manage tricky connections, scale the development process effectively, and address cloud security challenges. While advancements in virtualization and containerization (e.g., Docker, Kubernetes) are helping many businesses solve these challenges, cloud migration is no simple matter. 

That’s why, when considering your organization’s cloud migration strategy, it’s beneficial to look at case studies and examples from other companies’ cloud migration experiences. Why did they do it? How did they go about it? What happened? What benefits did they see, and what are the advantages and disadvantages of cloud computing for these businesses? Most importantly, what lessons did they learn — and what can you learn from them? 

With that in mind, Distillery has put together 10 cloud migration case studies your business can learn from. While most of the case studies feature companies moving from on-premise, bare metal data centers to cloud, we also look at companies moving from cloud to cloud, cloud to multi-cloud, and even off the cloud. Armed with all these lessons, ideas, and strategies, you’ll feel readier than ever to make the cloud work for your business.

Challenges for Cloud Adoption: Is Your Organization Ready to Scale and Be Cloud-first?

We examine several of these case studies from a more technical perspective in our white paper on Top Challenges for Cloud Adoption in 2019 . In this white paper, you’ll learn:

• Why cloud platform development created scaling challenges for businesses
• How scaling fits into the big picture of the Cloud Maturity Framework
• Why advancements in virtualization and containerization have helped businesses solve these scaling challenges
• How companies like Betabrand, Shopify, Spotify, Evernote, Waze, and others have solved these scaling challenges while continuing to innovate their businesses and provide value to users

#1 Betabrand : Bare Metal to Cloud

Betabrand (est. 2005) is a crowd-funded, crowd-sourced retail clothing e-commerce company that designs, manufactures, and releases limited-quantity products via its website. 

Migration Objective 

The company struggled with the maintenance difficulties and lack of scalability of the bare metal infrastructure supporting their operations. 

Planning for and adding capacity took too much time and added costs. They also needed the ability to better handle website traffic surges.

Migration Strategy and Results 

In anticipation of 2017’s Black Friday increased web traffic, Betabrand migrated to a Google Cloud infrastructure managed by Kubernetes (Google Kubernetes Engine, or GKE). They experienced no issues related to the migration, and Black Friday 2017 was a success. 

By Black Friday 2018, early load testing and auto-scaling cloud infrastructure helped them to handle peak loads with zero issues. The company hasn’t experienced a single outage since migrating to the cloud.

Key Takeaways

• With advance planning, cloud migration can be a simple process. Betabrand’s 2017 on-premise to cloud migration proved smooth and simple. In advance of actual migration, they created multiple clusters in GKE and performed several test migrations, thereby identifying the right steps for a successful launch.
• Cloud streamlines load testing. Betabrand was able to quickly create a replica of its production services that they could use in load testing. Tests revealed poorly performing code paths that would only be revealed by heavy loads. They were able to fix the issues before Black Friday. 
• Cloud’s scalability is key to customer satisfaction. As a fast-growing e-commerce business, Betabrand realized they couldn’t afford the downtime or delays of bare metal. Their cloud infrastructure scales automatically, helping them avoid issues and keep customers happy. This factor alone underlines the strategic importance of cloud computing in business organizations like Betabrand. 

#2 Shopify : Cloud to Cloud

Shopify (est. 2006) provides a proprietary e-commerce software platform upon which businesses can build and run online stores and retail point-of-sale (POS) systems. 

Shopify wanted to ensure they were using the best tools possible to support the evolution needed to meet increasing customer demand. Though they’d always been a cloud-based organization, building and running their e-commerce cloud with their own data centers, they sought to capitalize on the container-based cloud benefits of immutable infrastructure to provide better support to their customers. Specifically, they wanted to ensure predictable, repeatable builds and deployments; simpler and more robust rollbacks; and elimination of configuration management drift. 

By building out their cloud with Google, building a “Shop Mover” database migration tool, and leveraging Docker containers and Kubernetes, Shopify has been able to transform its data center to better support customers’ online shops, meeting all their objectives. For Shopify customers, the increasingly scalable, resilient applications mean improved consistency, reliability, and version control.

• Immutable infrastructure vastly improves deployments. Since cloud servers are never modified post-deployment, configuration drift — in which undocumented changes to servers can cause them to diverge from one another and from the originally deployed configuration — is minimized or eliminated. This means deployments are easier, simpler, and more consistent.
• Scalability is central to meeting the changing needs of dynamic e-commerce businesses. Shopify is home to online shops like Kylie Cosmetics, which hosts flash sales that can sell out in 20 seconds. Shopify’s cloud-to-cloud migration helped its servers flex to meet fluctuating demand, ensuring that commerce isn’t slowed or disrupted.

#3 Spotify: Bare Metal to Cloud

Spotify (est. 2006) is a media services provider primarily focused on its audio-streaming platform, which lets users search for, listen to, and share music and podcasts.

Spotify’s leadership and engineering team agreed: The company’s massive in-house data centers were difficult to provision and maintain, and they didn’t directly serve the company’s goal of being the “best music service in the world.” They wanted to free up Spotify’s engineers to focus on innovation. They started planning for migration to Google Cloud Platform (GCP) in 2015, hoping to minimize disruption to product development, and minimize the cost and complexity of hybrid operation. 

Spotify invested two years pre-migration in preparing, assigning a dedicated Spotify/Google cloud migration team to oversee the effort. Ultimately, they split the effort into two parts, services and data, which took a year apiece. For services migration, engineering teams moved services to the cloud in focused two-week sprints, pausing on product development. For data migration, teams were allowed to choose between “forklifting” or rewriting options to best fit their needs. Ultimately, Spotify’s on-premise to cloud migration succeeded in increasing scalability while freeing up developers to innovate. 

• Gaining stakeholder buy-in is crucial. Spotify was careful to consult its engineers about the vision. Once they could see what their jobs looked like in the future, they were all-in advocates. 
• Migration preparation shouldn’t be rushed. Spotify’s dedicated migration team took the time to investigate various cloud strategies and build out the use case demonstrating the benefits of cloud computing to the business. They carefully mapped all dependencies. They also worked with Google to identify and orchestrate the right cloud strategies and solutions. 
• Focus and dedication pay huge dividends. Spotify’s dedicated migration team kept everything on track and in focus, making sure everyone involved was aware of past experience and lessons already learned. In addition, since engineering teams were fully focused on the migration effort, they were able to complete it more quickly, reducing the disruption to product development.

#4 Evernote : Bare Metal to Cloud

Evernote (est. 2008) is a collaborative, cross-platform note-taking and task management application that helps users capture, organize, and track ideas, tasks, and deadlines.

Evernote, which had maintained its own servers and network since inception, was feeling increasingly limited by its infrastructure. It was difficult to scale, and time-consuming and expensive to maintain. They wanted more flexibility, as well as to improve Evernote’s speed, reliability, security, and disaster recovery planning. To minimize service disruption, they hoped to conduct the on-premise to cloud migration as efficiently as possible. 

Starting in 2016, Evernote used an iterative approach : They built a strawman based on strategic decisions, tested its viability, and rapidly iterated. They then settled on a cloud migration strategy that used a phased cutover approach, enabling them to test parts of the migration before committing. They also added important levels of security by using GCP service accounts , achieving “encryption at rest,” and improving disaster recovery processes. Evernote successfully migrated 5 billion notes and 5 billion attachments to GCP in only 70 days. 

• Cloud migration doesn’t have to happen all at once. You can migrate services in phases or waves grouped by service or user. Evernote’s phased cutover approach allowed for rollback points if things weren’t going to according to plan, reducing migration risk. 
• Ensuring data security in the cloud may require extra steps. Cloud security challenges may require extra focus in your cloud migration effort. Evernote worked with Google to create the additional security layers their business required. GCP service accounts can be customized and configured to use built-in public/private key pairs managed and rotated daily by Google.
• Cloud capabilities can improve disaster recovery planning. Evernote wanted to ensure that they would be better prepared to quickly recover customer data in the event of a disaster. Cloud’s reliable, redundant, and robust data backups help make this possible. 

#5 Etsy : Bare Metal to Cloud

Etsy (est. 2005) is a global e-commerce platform that allows sellers to build and run online stores selling handmade and vintage items and crafting supplies.

Etsy had maintained its own infrastructure from inception. In 2018, they decided to re-evaluate whether cloud was right for the company’s future. In particular, they sought to improve site performance, engineering efficiency, and UX. They also wanted to ensure long-term scalability and sustainability, as well as to spend less time maintaining infrastructure and more time executing strategy.

Migration Strategy and Results

Etsy undertook a detailed vendor selection process , ultimately identifying GCP as the right choice for their cloud migration strategy . Since they’d already been running their own Kubernetes cluster inside their data center, they already had a partial solution for deploying to GKE. They initially deployed in a hybrid environment (private data center and GKE), providing redundancy, reducing risk, and allowing them to perform A/B testing. They’re on target to complete the migration and achieve all objectives. 

Key Takeaways 

• Business needs and technology fit should be periodically reassessed. While bare metal was the right choice for Etsy when it launched in 2005, improvements in infrastructure as a service (IaaS) and platform as a service (PaaS) made cloud migration the right choice in 2018.
• Detailed analysis can help businesses identify the right cloud solution for their needs. Etsy took a highly strategic approach to assessment that included requirements definition, RACI (responsible, accountable, consulted, informed) matrices, and architectural reviews. This helped them ensure that their cloud migration solution would genuinely help them achieve all their goals.
• Hybrid deployment can be effective for reducing cloud migration risk. Dual deployment on their private data center and GKE was an important aspect of Etsy’s cloud migration strategy. 

#6 Waze : Cloud to Multi-cloud

Waze (est. 2006; acquired by Google in 2013) is a GPS-enabled navigation application that uses real-time user location data and user-submitted reports to suggest optimized routes.

Though Waze moved to the cloud very early on, their fast growth quickly led to production issues that caused painful rollbacks, bottlenecks, and other complications. They needed to find a way to get faster feedback to users while mitigating or eliminating their production issues.  

Waze decided to run an active-active architecture across multiple cloud providers — GCP and Amazon Web Services (AWS) — to improve the resiliency of their production systems. This means they’re better-positioned to survive a DNS DDOS attack, or a regional or global failure. An open source continuous delivery platform called Spinnaker helps them deploy software changes while making rollbacks easy and reliable. Spinnaker makes it easy for Waze’s engineers to deploy across both cloud platforms, using a consistent conceptual model that doesn’t rely on detailed knowledge of either platform .  

• Some business models may be a better fit for multiple clouds. Cloud strategies are not one-size-fits-all. Waze’s stability and reliability depends on avoiding downtime, deploying quick fixes to bugs, and ensuring the resiliency of their production systems. Running on two clouds at once helps make it all happen. 
• Your engineers don’t necessarily have to be cloud experts to deploy effectively. Spinnaker streamlines multi-cloud deployment for Waze such that developers can focus on development, rather than on becoming cloud experts. 

Deploying software more frequently doesn’t have to mean reduced stability/reliability. Continuous delivery can get you to market faster, improving quality while reducing risk and cost.

#7 AdvancedMD : Bare Metal to Cloud

AdvancedMD (est. 1999) is a software platform used by medical professionals to manage their practices, securely share information, and manage workflow, billing, and other tasks. 

AdvancedMD was being spun off from its parent company, ADP; to operate independently, it had to move all its data out of ADP’s data center. Since they handle highly sensitive, protected patient data that must remain available to practitioners at a moment’s notice, security and availability were top priorities. They sought an affordable, easy-to-manage, and easy-to-deploy solution that would scale to fit their customers’ changing needs while keeping patient data secure and available.

AdvancedMD’s on-premise to cloud migration would avoid the need to hire in-house storage experts, save them and their customers money, ensure availability, and let them quickly flex capacity to accommodate fluctuating needs. It also offered the simplicity and security they needed. Since AdvancedMD was already running NetApp storage arrays in its data center, it was easy to use NetApp’s Cloud Volumes ONTAP to move their data to AWS. ONTAP also provides the enterprise-level data protection and encryption they require.

• Again, ensuring data security in the cloud may require extra steps. Though cloud has improved or mitigated some security concerns (e.g., vulnerable OS dependencies, long-lived compromised servers), hackers have turned their focus to the vulnerabilities that remain. Thus, your cloud migration strategy may need extra layers of controls (e.g., permissions, policies, encryption) to address these cloud security challenges.
• When service costs are a concern, cloud’s flexibility may help. AdvancedMD customers are small to mid-sized budget-conscious businesses. Since cloud auto-scales, AdvancedMD never pays for more cloud infrastructure than they’re actually using. That helps them keep customer pricing affordable.

#8 Dropbox : Cloud to Hybrid

Dropbox (est. 2007) is a file hosting service that provides cloud storage and file synchronization solutions for customers.

Dropbox had developed its business by using the cloud — specifically, Amazon S3 (Simple Storage Service) — to house data while keeping metadata housed on-premise. Over time, they began to fear they’d become overly dependent on Amazon: not only were costs increasing as their storage needs grew, but Amazon was also planning a similar service offering, Amazon WorkDocs. Dropbox decided to take back their storage to help them reduce costs, increase control, and maintain their competitive edge. 

While the task of moving all that data to an in-house infrastructure was daunting, the company decided it was worth it — at least in the US (Dropbox assessed that in Europe, AWS is still the best fit). Dropbox designed in-house and built a massive network of new-breed machines orchestrated by software built with an entirely new programming language, moving about 90% of its files back to its own servers . Dropbox’s expanded in-house capabilities have enabled them to offer Project Infinite, which provides desktop users with universal compatibility and unlimited real-time data access.

• On-premise infrastructure may still be right for some businesses. Since Dropbox’s core product relies on fast, reliable data access and storage, they need to ensure consistently high performance at a sustainable cost. Going in-house required a huge investment, but improved performance and reduced costs may serve them better in the long run. Once Dropbox understood that big picture, they had to recalculate the strategic importance of cloud computing to their organization.  
• Size matters. As Wired lays out in its article detailing the move , cloud businesses are not charities. There’s always going to be margin somewhere. If a business is big enough — like Dropbox — it may make sense to take on the difficulties of building a massive in-house network. But it’s a huge risk for businesses that aren’t big enough, or whose growth may stall.

#9 GitLab : Cloud to Cloud

GitLab (est. 2011) is an open core company that provides a single application supporting the entire DevOps life cycle for more than 100,000 organizations. 

GitLab’s core application enables software development teams to collaborate on projects in real time, avoiding both handoffs and delays. GitLab wanted to improve performance and reliability, accelerating development while making it as seamless, efficient, and error-free as possible. While they acknowledged that Microsoft Azure had been a great cloud provider, they strongly believed that GCP’s Kubernetes was the future, calling it “a technology that makes reliability at massive scale possible.” 

In 2018, GitLab migrated from Azure to GCP so that GitLab could run as a cloud-native application on GKE. They used their own Geo product to migrate the data, initially mirroring the data between Azure and GCP. Post-migration, GitLab reported improved performance (including fewer latency spikes) and a 61% improvement in availability.    

• Containers are seen by many as the future of DevOps. GitLab was explicit that they view Kubernetes as the future. Indeed, containers provide notable benefits, including a smaller footprint, predictability, and the ability to scale up and down in real time. For GitLab’s users, the company’s cloud-to-cloud migration makes it easier to get started with using Kubernetes for DevOps.
• Improved stability and availability can be a big benefit of cloud migration. In GitLab’s case, mean-time between outage events pre-migration was 1.3 days. Excluding the first day post-migration, they’re up to 12 days between outage events. Pre-migration, they averaged 32 minutes of downtime weekly; post-migration, they’re down to 5. 

#10 Cordant Group : Bare Metal to Hybrid

The Cordant Group (est. 1957) is a global social enterprise that provides a range of services and solutions, including recruitment, security, cleaning, health care, and technical electrical.

Over the years, the Cordant Group had grown tremendously, requiring an extensive IT infrastructure to support their vast range of services. While they’d previously focused on capital expenses, they’d shifted to looking at OpEx, or operational expenses — which meant cloud’s “pay as you go” model made increasing sense. It was also crucial to ensure ease of use and robust data backups.

They began by moving to a virtual private cloud on AWS , but found that the restriction to use Windows DFS for file server resource management was creating access problems. NetApp Cloud ONTAP, a software storage appliance that runs on AWS server and storage resources, solved the issue. File and storage management is easier than ever, and backups are robust, which means that important data restores quickly. The solution also monitors resource costs over time, enabling more accurate planning that drives additional cost savings. 

• Business and user needs drive cloud needs. That’s why cloud strategies will absolutely vary based on a company’s unique needs. The Cordant Group needed to revisit its cloud computing strategy when users were unable to quickly access the files they needed. In addition, with such a diverse user group, ease of use had to be a top priority.
• Cloud ROI ultimately depends on how your business measures ROI. The strategic importance of cloud computing in business organizations is specific to each organization. Cloud became the right answer for the Cordant Group when OpEx became the company’s dominant lens. 

Which Cloud Migration Strategy Is Right for You?

As these 10 diverse case studies show, cloud strategies are not one-size-fits all. Choosing the right cloud migration strategy for your business depends on several factors, including your:

• Goals. What business results do you want to achieve as a result of the migration? How does your business measure ROI? What problems are you trying to solve via your cloud migration strategy? 
• Business model. What is your current state? What are your core products/services and user needs, and how are they impacted by how and where data is stored? What are your development and deployment needs, issues, and constraints? What are your organization’s cost drivers? How is your business impacted by lack of stability or availability? Can you afford downtime? 
• Security needs. What are your requirements regarding data privacy, confidentiality, encryption, identity and access management, and regulatory compliance? Which cloud security challenges pose potential problems for your business?
• Scaling needs. Do your needs and usage fluctuate? Do you expect to grow or shrink? 
• Disaster recovery and business continuity needs. What are your needs and capabilities in this area? How might your business be impacted in the event of a major disaster — or even a minor service interruption? 
• Technical expertise. What expertise do you need to run and innovate your core business? What expertise do you have in-house? Are you allocating your in-house expertise to the right efforts? 
• Team focus and capacity. How much time and focus can your team dedicate to the cloud migration effort? 
• Timeline. What business needs constrain your timeline? What core business activities must remain uninterrupted? How much time can you allow for planning and testing your cloud migration strategy? 

Of course, this list isn’t exhaustive. These questions are only a starting point. But getting started — with planning, better understanding your goals and drivers, and assessing potential technology fit — is the most important step of any cloud migration process. We hope these 10 case studies have helped to get you thinking in the right direction. 

While the challenges of cloud migration are considerable, the right guidance, planning, and tools can lead you to the cloud strategies and solutions that will work best for your business. So don’t delay: Take that first step to helping your business reap the potential advantages and benefits of cloud computing. 

Ready to take the next step on your cloud journey? As a Certified Google Cloud Technology Partner , Distillery is here to help. Download our white paper on top challenges for cloud adoption to get tactical and strategic about using cloud to transform your business.  

Recent Posts

• Distillery’s Unsung Heroes: Fran Maurici
• The Future of Fintech Development: Trends CTOs Can’t Afford to Ignore
• 10 Must-Haves for Building a Fintech Software Development Team
• Shopify vs Magento: Choosing the Right E-commerce Platform for Your Business
• Building a Winning Mobile App Strategy for Your Travel Business

Recent Comments

Ending the confusion in cloud transformations: The dashboards and metrics everyone needs

The promise and peril of cloud is a common refrain in many C-suites: huge economic potential and regularly underperforming reality. What’s much less clear, however, is what to do about it.

Out of the more than 80 enterprises McKinsey profiled for its CloudSights database, 40 percent have found limited value in their cloud programs. 1 CloudSights is a database made up of more than 80 interviews conducted in North America and Europe with cloud leaders from companies of various sizes and industries. In addition, half of companies five or more years into their cloud journey still have not achieved 20 percent cloud adoption. The underlying causes are often hard to pinpoint and articulate, or are simply caught too late to stop the damage. Even for companies that are well on their way to achieving value from cloud, it is often difficult to communicate progress to stakeholders and make a credible case, based on clear ROI data, for substantial new investments.

Given the significant resources of time, money, and people that companies invest in cloud transformations, it’s surprising how poor the metrics and objectives and key results (OKRs) used to track progress often are. For example, some companies will exclusively use point-in-time metrics (for example, number of applications migrated by a given date) to understand where their cloud program is. These metrics, however, frequently fail to accurately capture the full picture of progress over time. Other cloud programs will set their OKRs without involvement from the business side and, as a result, struggle to actually measure and articulate the enterprise value cloud is creating. In many cases, cloud teams will also lack clarity over who is accountable for which metrics and how they are being reported and used. The difficulty often boils down to lack of clarity about what is important to measure and lack of rigor in implementing a tracking program.

Well-designed dashboards and central governance drive transparency and increase data-backed decision making in effectively identifying roadblocks and resolving them. Great dashboards help visualize trends and issues over time to identify when and where leaders should intervene. OKRs reflect the enterprise vision to ensure cloud is truly supporting top-line business goals, and they are consistently and clearly tracked with key owners and stakeholders for each set of metrics.

Creating value beyond the hype

Let’s deliver on the promise of technology from strategy to scale.

In our experience, there are eight dimensions that are important to almost any cloud transformation, and each has a corresponding dashboard (exhibit). Different metrics will take precedence with different stakeholders, and it is important to tailor each dashboard to an organization’s specific cloud program and stakeholders.

For a subset of these dashboards—dimensions C, D, and H, highlighted in gray in the exhibit—we have drafted examples of what their appropriate metrics might look like and what would be needed to set them up. Each dashboard example is focused on achieving one or more of the cloud program’s objectives and includes metrics that help track progress toward the relevant key results (KR).

Dimension C: Cost performance

How are we tracking costs against our program’s projected budget and savings.

As cloud programs require large investments, there must be a clear, up-front financial case made for cloud to ensure that the investment pays off and costs don’t balloon. A cost performance dashboard tracks the projected (actual plus forecast) costs and savings against the budget developed for the program, allowing leaders to dig into which areas are overspending and where teams can achieve greater savings based on learned experience.

Key stakeholders: CIO, CFO, head of procurement

Frequency of stakeholder review: Monthly

Examples of metrics: Monthly infrastructure and application costs, business case projected savings and value, contracts database, procurement team’s usage data, enterprise resource planning (ERP) general ledger, financial planning and analysis (FP&A) tooling (for example, Anaplan)

It is often senior leadership who must approve cloud budgets and business cases (and changes to them), so it is important to provide digestible, relevant cost information to track progress and create opportunities for intervention, such as renegotiation of a contract or changes to a migration plan. A global automotive supplier was struggling to understand and achieve financial progress during a multiyear cloud journey. When it put in place monthly dashboards and metrics to increase visibility in this area, it soon realized that it was missing out on a number of important cost initiatives, including avoidance of capital expenditures on decommissioning servers. The team worked with IT finance to determine which servers’ decommissioning would generate the most savings and tracked this closely over time, avoiding more than $500,000 of capital expenditures within six months.

Dimension D. Application and data migration

What proportion of our applications and data have we migrated to the cloud.

As the value of cloud relies on transitioning applications and their accompanying data at scale, a core transformation dimension is understanding progress against this migration. An application and data migration dashboard is used to understand the overall scope, progress, and velocity of the migration (and any corresponding application or system retirements), potentially broken down by business units, application portfolios, and/or application owners. Since many applications will require some level of modernization (as opposed to simply lifting and shifting them to cloud) to reap cloud’s full benefits, applications should also be tracked by progress toward their final disposition. This type of dashboard will help identify the migration and modernization outliers and allow for refinement of the overall process as future waves of workloads are migrated or retired.

Key stakeholders: CIO, chief data officer, head of infrastructure, application portfolio leads

Frequency of stakeholder review: Weekly to monthly

Examples of metrics: Configuration management database (CMDB), application information, native cloud service provider tools, target disposition and migration plans, system integrator timeline, cloud business cases

A clear dashboard with changes over time will allow the cloud team to quickly intervene on migration delays and manage changes to the overall timeline and business case as needed. At a European logistics organization, the cloud program office put in place weekly readouts of progress, including dashboards and metrics, measuring workload migration. When the head of cloud noticed that a particular team was consistently behind migration targets, he intervened, providing the team with additional resources and support that allowed them to catch up to the migration timeline within the next month.

Dimension H. People, products, and operating model

Do i have the right people, products, and operating model to successfully execute my cloud transformation and adopt our new ways of working.

In addition to all the technical changes cloud brings, organizations will need to change the way they work—their people, products, and operating model— to get cloud’s full benefits. Tracking common operating metrics, such as those from DevOps research and assessment (DORA), allows leadership to see the benefits coming from cloud or intervene where value is falling short. Part of improving cloud operations requires putting the right talent in place through both internal upskilling and external hires.

Key stakeholders: Heads of recruiting, learning, human resources (HR), and product

Examples of metrics: HR workforce software, recruiting tools, employee training and certification logs

Since people-based objectives often require people-based interventions, this type of dashboard will greatly improve leadership’s ability to make targeted interventions through activities such as increasing recruitment activity, implementing new training incentive programs, or making changes to the product team structure.

Cloud by McKinsey

For any company beginning or resetting its cloud-metrics journey, it is important to begin with a clear vision based on business objectives and define metrics and initiatives to support them. As cloud programs and value tracking mature, individuals should be assigned to “own” metric targets on the dashboards, report against them, and look for opportunities to automate the data tracking. A central governance team or cloud adoption office can regularly review progress against these metrics, flag risks and roadblocks, and coordinate interventions, such as assigning extra cloud resources to a struggling business unit. Organizations can set up a standard cadence to meet with key stakeholders to ensure that the cloud transformation is getting the desired visibility.

Implementing the technology and processes to support tracking cloud value capture is a significant challenge. Compiling data from multiple parties and data sources often requires development and maintenance of a dedicated resource.

A pharmaceutical company faced this issue during its cloud modernization program. Multiple parties were providing progress updates in their own formats, making it difficult to judge and compare progress or to have a view of the overall program. To address this issue, the team brought in a dedicated data modeling and visualization expert to develop a consolidated reporting dashboard. The team focused on creating standards for reporting to be used by all parties and automating the delivery of reports that tracked progress against objectives across workstreams, which went directly to program leadership and accountable parties every week or month. This approach made it much easier for workstream owners to track their progress, increasing their accountability. In one case, the team realized that a set of reports that focused on application migration did not include orphan-server shutdowns once apps were migrated, and, as a result, the full value of the migration effort wasn’t clear. The team added reporting on the status of 2,000 servers that would no longer be needed, shut them down promptly, and realized $30 million in savings.

Program governance teams can utilize reporting tools like Power BI, Tableau, and Qlik, which can pull data using different connection methods (such as manual Excel/CSV uploads, ODBC, REST API) and any additional data workflow automation tools available to support automated refreshes, data cleansing, and data normalization.

The cloud transformation journey is difficult and often doesn’t go according to the initial road map and business case. Through improved tracking, companies can better understand and de-risk their progress, manage stakeholders, and focus their efforts toward driving business value through cloud.

Chhavi Arora is a partner in McKinsey’s Seattle office, Emily Wu is a principal lead for cloud delivery in the Southern California office, Hamilton Williams is an alumnus of the Atlanta office, and Isabelle Tamburro is a consultant in the Chicago office.

Explore a career with us

Related articles.

In search of cloud value: Can generative AI transform cloud ROI?

The state of cloud computing in Europe: Increasing adoption, low returns, huge potential

From legacy to cloud: Lessons learned

• Español – América Latina
• Português – Brasil

Spotify: The future of audio. Putting data to work, one listener at a time.

About Spotify

A Google Cloud customer since 2016, Spotify is the most popular global audio streaming subscription service with 248m users, including 113m subscribers, across 79 markets. Spotify is the largest driver of revenue to the music business today.

Spotify exemplifies the new era of scaling a business. It launched a music-streaming service in late 2008, surpassed 1 million customers in early 2011, and today offers 248 million monthly active users in 79 markets access to more than 50 million songs and podcasts.

That’s technology-driven hypergrowth by anyone’s standard. Equally striking, though, is the way Spotify has continued to innovate its offering, while adhering to the enduring principles for growing and sustaining a successful business: Pay attention to the customer. Find new ways to delight them. Use your comparative advantage, doubling down on the things you are best at, and find good partners to handle other work. Focus on scaling your culture even as you scale your technology.

Those old truths may be even more urgent in the digital age. Streaming audio is a competitive business, requiring fast product development, customer understanding, and powerful tools for things like recommendation, music discovery, and connecting people. Besides helping people find new music and podcasts, Spotify helps artists connect with fans and collaborate with each other.

Google Cloud is proud to support Spotify’s increasing diversification and success. In 2016 we worked together to move 1200 online services and data processing DAGs (directed acyclic graphs) as well as 20,000 daily job executions, affecting more than 100 Spotify teams, from Spotify’s data centers to the cloud. Today, Spotify’s customers listen to billions of daily plays of music and podcasts leveraging Google Cloud’s global network.

By employing automated, developer-friendly services on Google Cloud, Spotify’s teams could focus better on its core business, while gaining access to services, like data analytics, on which it could grow.

“Google Cloud removes a lot of the operational complexity from our ecosystem. That frees up time,” said Tyson Singer, vice president of technology and platform at Spotify. “We can iterate quicker on key needs, like data insights and machine learning. Having infrastructure managed for us, with the lower-value details taken away, streamlines our ability to concentrate on what’s important to our users and give them the experiences they know and love about Spotify.”

Spotify, not surprisingly, has a very engineering-driven culture, with almost half of its staff focused on building, launching, and maintaining its products. With major research and development offices in Boston, Gothenburg, London, New York, and Stockholm, the size of its workforce matches the global scale of its business. That requires a culture of collaboration and swift execution. In the fourth quarter of 2019, Spotify reported 271 million monthly users and 124 million Premium subscribers, a record, continuing its history of global growth.

Effective data use that preserves customer privacy even as the services scale is another core part of the process. Some of that increase is from a growing user base, but even more is from effective understanding of the customer experience on Spotify. The engineering brilliance that matches data-driven insights with improved customer experiences is increasingly easier and faster on the cloud.

Robust building blocks that exist on top of core data storage, computing, and network services help take away much of the backend hassle on the way to new product creation. Spotify’s technology leaders point to the particular importance of BigQuery, the Google Cloud data analysis tool, as well as Pub/Sub, for faster software application development. Dataflow, for real-time and historical data analysis, has also been particularly useful.

Much of that data goes towards solving the tricky issue of personalization in new ways. Data privacy is at the core of Spotify’s development activities as it seeks to offer music lovers new ways to find the sounds they love and connect with artists. Podcasting, a recent groundbreaking effort, relies even more on robust discovery to discern things like topics, creators, and user interest levels.

For artists, the ability to find and connect with fans, or work on new material with other musicians, is another dimension of data-driven discovery. Artists on Spotify have access to dashboards that let them gain knowledge about their fans and other artists, which helps them make better-informed decisions about everything from where to plan their upcoming tour to when to drop their next release.

Ultimately, it is great user experiences that powers a business. In the past year alone, the number of Spotify’s premium subscribers has grown by 29 percent . The company credits growth in new markets, as well as innovative new products, for the increase.

Underlying Spotify's growth is its commitment to experimentation and innovation. Being able to go faster and to more efficiently test a wide spectrum of new features and ideas means Spotify will be able to focus its DNA of creativity and excellence on even more innovative experiences for its happy listeners.

Tell us your challenge. We're here to help.

• Reach out to our team to see how Google Cloud can help your business.

• Cloud Computing

AWS Case Studies: Services and Benefits in 2024

Home Blog Cloud Computing AWS Case Studies: Services and Benefits in 2024

With its extensive range of cloud services, Amazon Web Services (AWS) has completely changed the way businesses run. Organisations demonstrate how AWS has revolutionized their operations by enabling scalability, cost-efficiency, and innovation through many case studies. AWS's computing power, storage, database management, and artificial intelligence technologies have benefited businesses of all sizes, from startups to multinational corporations. These include improved security, agility, worldwide reach, and lower infrastructure costs. With Amazon AWS educate program it helps businesses in various industries to increase growth, enhance workflow, and maintain their competitiveness in today's ever-changing digital landscape. So, let's discuss the AWS cloud migration case study   and its importance in getting a better understanding of the topic in detail.

What are AWS Case Studies, and Why are They Important?

The   AWS case   studies comprehensively explain how companies or organizations have used Amazon Web Services (AWS) to solve problems, boost productivity, and accomplish objectives. These studies provide real-life scenarios of Amazon Web Services (AWS) in operation, showcasing the wide range of sectors and use cases in which AWS can be successfully implemented. They offer vital lessons and inspiration for anyone considering or already using AWS by providing insights into the tactics, solutions, and best practices businesses use the AWS Cloud Engineer program . The Amazon ec2 case study   is crucial since it provides S's capabilities, assisting prospective clients in comprehending the valuable advantages and showcasing AWS's dependability, scalability, and affordability in fostering corporate innovation and expansion.

What are the Services Provided by AWS, and What are its Use Cases?

The   case study on AWS in Cloud Computing provided and its use cases mentioned:

Elastic Compute Cloud (EC2) Use Cases

Amazon Elastic Compute Cloud (EC2) enables you to quickly spin up virtual computers with no initial expenditure and no need for a significant hardware investment. Use the AWS admin console or automation scripts to provision new servers for testing and production environments promptly and shut them down when not in use.

AWS EC2 use cases consist of:

• With options for load balancing and auto-scaling, create a fault-tolerant architecture.
• Select EC2 accelerated computing instances if you require a lot of processing power and GPU capability for deep learning and machine learning.

Relational Database Service (RDS) Use Cases

Since Amazon Relational Database Service (Amazon RDS) is a managed database service, it alleviates the stress associated with maintaining, administering, and other database-related responsibilities.

AWS RDS uses common cases, including:

• Without additional overhead or staff expenditures, a new database server can be deployed in minutes and significantly elevate dependability and uptime. It is the perfect fit for complex daily database requirements that are OLTP/transactional.
• RDS should be utilized with NoSQL databases like Amazon OpenSearch Service (for text and unstructured data) and DynamoDB (for low-latency/high-traffic use cases).

AWS Workspaces

AWS offers Amazon Workspaces, a fully managed, persistent desktop virtualization service, to help remote workers and give businesses access to virtual desktops within the cloud. With it, users can access the data, apps, and resources they require from any supported device, anywhere, at any time.

AWS workspaces use cases

• IT can set up and manage access fast. With the web filter, you can allow outgoing traffic from a Workspace to reach your chosen internal sites.
• Some companies can work without physical offices and rely solely on SaaS apps. Thus, there is no on-premises infrastructure. They use cloud-based desktops via AWS Workspaces and other services in these situations.

AWS Case Studies

Now, we'll be discussing different case studies of AWS, which are mentioned below: -

Case Study - 1: Modern Web Application Platform with AWS

American Public Media, the programming section of Minnesota Public Radio, is one of the world's biggest producers and distributors of public television. To host their podcast, streaming music, and news websites on AWS, they worked to develop a proof of concept.

After reviewing an outdated active-passive disaster recovery plan, MPR decided to upgrade to a cloud infrastructure to modernize its apps and methodology. This infrastructure would need to be adaptable to changes within the technology powering their apps, scalable to accommodate their audience growth, and resilient to support their disaster recovery strategy.

MPR and AWS determined that MPR News and the public podcast websites should be hosted on the new infrastructure to show off AWS as a feasible choice. Furthermore, AWS must host multiple administrative apps to demonstrate its private cloud capabilities. These applications would be an image manager, a schedule editor, and a configuration manager.

To do this, AWS helped MPR set up an EKS Kubernetes cluster . The apps would be able to grow automatically according to workload and traffic due to the cluster. AWS and MPR developed Elasticsearch at Elastic.co and a MySQL instance in RDS to hold application data.

Business Benefits

Considerable cost savings were made possible by the upgraded infrastructure. Fewer servers would need to be acquired for these vital applications due to the decrease in hardware requirements. Additionally, switching to AWS made switching from Akamai CDN to CloudFront simple. This action reduced MPR's yearly expenses by thousands.

Case Study - 2: Platform Modernisation to Deploy to AWS

Foodsby was able to proceed with its expansion goals after receiving a $6 million investment in 2017, but it still needed to modernize its mobile and web applications. For a faster time to launch to AWS, they improved and enhanced their web, iOS, and Android applications.

Sunsetting technology put this project on a surged timeline. Selecting the mobile application platform required serious analysis and expert advice to establish consensus across internal stakeholders.

Improving the creation of front-end and back-end web apps that separated them into microservices to enable AWS hosting, maximizing scalability. Strengthening recommended full Native for iOS and Android and quickly creating and implementing that solution.

Case Study - 3: Cloud Platform with Kubernetes

SPS Commerce hired AWS to assist them with developing a more secure cloud platform, expanding their cloud deployment choices through Kubernetes, and educating their engineers on these advanced technologies.

SPS serves over 90,000 retail, distribution, grocery, and e-commerce businesses. However, to maintain its growth, SPS needs to remove obstacles to deploying new applications on AWS and other cloud providers in the future. They wanted a partner to teach their internal development team DevOps principles and reveal them to Kubernetes best practices, even though they knew Kubernetes would help them achieve this.

To speed up new project cycle times, decrease ramp-up times, and improve the team's Kubernetes proficiency, it assisted with developing a multi-team, Kubernetes-based platform with a uniform development method. The standards for development and deployment and assisted them in establishing the deployment pipeline.

Most teams can plug, play, and get code up and running quickly due to the streamlined deployment interface. SPS Commerce benefits from Kubernetes' flexibility and can avoid vendor lock-in, which they require to switch cloud providers.

Case Study - 4: Using Unified Payment Solutions to Simplify Government Services

The customer, who had a portfolio of firms within its authority, needed to improve experience to overcome the difficulty of combining many payment methods into a single, unified solution.

Due to the customers' varied acquisitions, the payment system landscape became fragmented, making it more difficult for clients to make payments throughout a range of platforms as well as technologies. Providing a streamlined payment experience could have been improved by this lack of coherence and standardization.

It started developing a single, cloud-based payment system that complies with the customers' microservices-based reference design. CRUD services were created after the user interface for client administration was set at the beginning of the project.

With this, the customer can streamline operations and increase efficiency by providing a smooth payment experience.

The new system demonstrated a tremendous improvement over the old capability, demonstrating the ability to handle thousands of transactions per second.

Maintaining system consistency and facilitating scalability and maintenance were made more accessible by aligning with the reference architecture.

Case Study - 5: Accelerated Data Migration to AWS

They selected improvements to create   an   AWS cloud migration case study cloud platform to safely transfer their data from a managed service provider to AWS during the early phases of a worldwide pandemic.

Early in 2020, COVID-19 was discovered, and telemedicine services were used to lessen the strain on hospital infrastructure. The number of telehealth web queries increased dramatically overnight, from 5,000 to 40,000 per minute. Through improvement, Zipnosis was able to change direction and reduce the duration of its AWS migration plan from six to three months. The AWS architecture case study includes HIPAA, SOC2, and HITRUST certification requirements. They also wanted to move their historic database smoothly across several web-facing applications while adhering to service level agreements (SLAs), which limited downtime.

Using Terraform and Elastic Kubernetes Service, the AWS platform creates a modern, infrastructure-as-code, HIPAA-compliant, and HITRUST-certified environment. With the help of serverless components, tools were developed to roll out an Application Envelope, enabling the creation of a HIPAA-compliant environment that could be activated quickly.

Currently, Zipnosis has internal platform management. Now that there is more flexibility, scaling up and down is more affordable and accessible. Their services are more marketable to potential clients because of their scalable, secure, and efficient infrastructure. Their use of modern technologies, such as Kubernetes on Amazon EKS, simplifies hiring top people. Zipnosis is in an excellent position to move forward.

Case Study - 6: Transforming Healthcare Staffing

The customer's outdated application presented difficulties. It was based on the outdated DBROCKET platform and needed an intuitive user interface, testing tools, and extensibility. Modernizing the application was improving the job and giving the customer an improved, scalable, and maintainable solution.

Although the customer's old application was crucial for predicting hospital staffing needs, maintenance, and improvements were challenging due to its reliance on the obscure DBROCKET platform. Hospitals lost money on inefficient staff scheduling due to the application's lack of responsiveness and a mobile-friendly interface.

Choosing Spring Boot and Groovy for back-end development to offer better maintainability and extensibility throughout the improved migration of the application from DBROCKET to a new technology stack. Unit tests were used to increase the reliability and standard of the code.

Efficiency at Catalis increased dramatically when the advanced document redaction technology was put in place. They were able to process papers at a significantly higher rate because the automated procedure cut down the time and effort needed for manual redaction.

Catalis cut infrastructure costs by utilizing serverless architecture and cloud-based services. They saved a significant amount of money because they were no longer required to upgrade and maintain on-premises servers.

The top-notch Knowledgehut best Cloud Computing courses that meet different demands and skill levels are available at KnowledgeHut. Through comprehensive curriculum, hands-on exercises, and expert-led instruction, attendees may learn about and gain practical experience with cloud platforms, including AWS, Azure, Google Cloud, and more. Professionals who complete these courses will be efficient to succeed in the quickly developing sector of cloud computing.

Finally,   a   case study of   AWS retail case studies offers a range of features and advantages. These studies show how firms in various industries use AWS for innovation and growth, from scalability to cost efficiency. AWS offers a robust infrastructure and a range of technologies to satisfy changing business needs, whether related to improving customer experiences with cloud-based solutions or streamlining processes using AI and machine learning. These case studies provide substantial proof of AWS's influence on digital transformation and the success of organizations.

Frequently Asked Questions (FAQs)

From the case study of Amazon web services, companies can learn how other businesses use AWS services to solve real-world problems, increase productivity, cut expenses, and innovate. For those looking to optimize their cloud strategy and operations, these case studies provide insightful information, optimal methodologies, and purpose. 

You can obtain case studies on AWS through the AWS website, which has a special section with a large selection of case studies from different industries. In addition, AWS releases updated case studies regularly via various marketing platforms and on its blog.

The case study of Amazon web services, which offers specific instances of how AWS services have been successfully applied in various settings, can significantly assist in the decision-making process for IT initiatives. Project planning and strategy can be informed by the insights, best practices, and possible solutions these case studies provide.

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.

Something went wrong

Upcoming Cloud Computing Batches & Dates

Systematic Literature Review of Cloud Computing Research Between 2010 and 2023

• Conference paper
• First Online: 21 May 2024
• Cite this conference paper

• Shailaja Jha 10 &
• Devina Chaturvedi   ORCID: orcid.org/0009-0004-1242-2099 11  

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 508))

Included in the following conference series:

• Workshop on e-Business

We present a meta-analysis of cloud computing research in information systems. The study includes 152 referenced journal articles published between January 2010 to June 2023. We take stock of the literature and the associated research themes, research frameworks, the employed research methodology, and the geographical distribution of the articles. This review provides holistic insights into trends in cloud computing research based on themes, frameworks, methodology, geographical focus, and future research directions. The results indicate that the extant literature tends to skew toward themes related to business issues, which is an indicator of the maturing and widespread use of cloud computing. This trend is evidenced in the more recent articles published between 2016 to 2023.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

The conference proceedings were primarily used to assess the year-on-year numerical trends in publications, and they have not been used for detailed analysis.

Abdalla Mikhaeil, C., James, T.L.: Examining the case of French hesitancy toward IDaaS solutions: technical and social contextual factors of the organizational IDaaS privacy calculus. Inform. Manage. 60 (4), 103779 (2023)

Google Scholar  

Allen, B., et al.: Software as a service for data scientists. Commun. ACM 55 (2), 81–88 (2012)

Andrade-Rojas, M.G., Kathuria, A., Lee, H.-H.: Multilevel synergy of IT operational integration: competition networks and operating performance. Prod. Oper. Manage. (forthcoming) (2024)

Andrade-Rojas, M.G., Saldanha, T., Kathuria, A., Khuntia, J., Boh, W.F.: How IT overcomes deficiencies for innovation in SMEs: closed innovation versus open innovation. Inform. Syst. Res. (forthcoming) (2024)

Anthes, G.: Security in the cloud. Commun. ACM 53 , 16–18 (2010)

Armbrust, M., et al.: A view of cloud computing. Commun. ACM 53 , 50–58 (2010)

August, T., Niculescu, M.F., Shin, H.: Cloud implications on software network structure and security risks. Inform. Syst. Res. 25 , 489–510 (2014)

Bandara, W., Furtmueller, E., Gorbacheva, E., Miskon, S., Beekhuyzen, J.: Achieving rigor in literature reviews: insights from qualitative data analysis and tool-support. Commun. Assoc. Inform. Syst. 37 (8), 154–204 (2015). http://aisel.aisnet.org/cais/vol37/iss1/8

Benlian, A.: Is traditional, open-source, or on-demand first choice? Developing an AHP-based framework for the comparison of different software models in office suites selection. Eur. J. Inform. Syst. 20 , 542–559 (2011)

Benlian, A., Kettinger, W.J., Sunyaev, A., Winkler, T.J.: Special section: the transformative value of cloud computing: a decoupling, platformization, and recombination theoretical framework. J. Manage. Inform. Syst. 35 , 719–739 (2018)

Benlian, A., Koufaris, M., Hess, T.: The role of SaaS service quality for continued SaaS use: Empirical insights from SaaS using firms (2010)

Bhattacherjee, A., Park, S.C.: Why end-users move to the cloud: a migration-theoretic analysis. Eur. J. Inform. Syst. 23, 357–372 (2014)

Chaturvedi, D., Kathuria, A., Andrade, M., Saldanha, T.: Navigating the Paradox of IT Novelty and Strategic Conformity: The Moderating Role of Industry Dynamism (2023)

Chen, F., Lu, A., Wu, H., Li, M.: Compensation and pricing strategies in cloud service SLAs: considering participants’ risk attitudes and consumer quality perception. Electron. Commerce Res. Appl. 56 , 101215 (2022)

Cheng, H.K., Li, Z., Naranjo, A.: Research note—cloud computing spot pricing dynamics: latency and limits to arbitrage. Inform. Syst. Res. 27 , 145–165 (2016)

Choudhary, V., Vithayathil, J.: The impact of cloud computing: should the IT department be organized as a cost center or a profit center? J. Manage. Inform. Syst. 30 , 67–100 (2013)

Choudhary, V., Zhang, Z.: Research note—patching the cloud: the impact of SaaS on patching strategy and the timing of software release. Inform. Syst. Res. 26 , 845–858 (2015)

Dasgupta, A., Karhade, P., Kathuria, A., Konsynski, B.: Holding space for voices that do not speak: design reform of rating systems for platforms in GREAT economies (2021)

Demirkan, H., Cheng, H.K., Bandyopadhyay, S.: Coordination strategies in an SaaS supply chain. J. Manage. Inform. Syst. 26 , 119–143 (2010)

Demirkan, H., Delen, D.: Leveraging the capabilities of service-oriented decision support systems: putting analytics and big data in cloud. Decis. Support Syst. 55 , 412–421 (2013)

Dierks, L., Seuken, S.: Cloud pricing: the spot market strikes back. Manage. Sci. 68 (1), 105–122 (2022)

Article   Google Scholar  

Ding, S., Xia, C., Wang, C., Desheng, Wu., Zhang, Y.: Multi-objective optimization based ranking prediction for cloud service recommendation. Decis. Support. Syst. 101 , 106–114 (2017)

Dong, L., Shu, W., Sun, D., Li, X., Zhang, L.: Pre-alarm system based on real-time monitoring and numerical simulation using internet of things and cloud computing for tailings dam in mines. IEEE Access 5 , 21080–21089 (2017)

Xin, Du., Tang, S., Zhihui, Lu., Gai, K., Jie, Wu., Hung, P.C.K.: Scientific workflows in IoT environments: a data placement strategy based on heterogeneous edge-cloud computing. ACM Trans. Manage. Inform. Syst. 13 (4), 1–26 (2022)

Ermakova, T., Fabian, B., Kornacka, M., Thiebes, S., Sunyaev, A.: Security and privacy requirements for cloud computing in healthcare: elicitation and prioritization from a patient perspective. ACM Trans. Manage. Inform. Syst. 11 (2), 1–29 (2020)

Garrison, G., Kim, S., Wakefield, R.L.: Success factors for deploying cloud computing. Commun. ACM 55 (9), 62–68 (2012)

Giessmann, A., Legner, C.: Designing business models for cloud platforms. Inf. Syst. J. 26 (5), 551–579 (2016). https://doi.org/10.1111/isj.12107

Gray, A.: Conflict of laws and the cloud. Comput. Law Secur. Rev. 29 (1), 58–65 (2013)

Hosseini, L., Tang, S., Mookerjee, V., Sriskandarajah, C.: A switch in time saves the dime: a model to reduce rental cost in cloud computing. Inform. Syst. Res. 31 (3), 753–775 (2020)

Huang, K.-W., Sundararajan, A.: Pricing digital goods: discontinuous costs and shared infrastructure. Inf. Syst. Res. 22 (4), 721–738 (2011)

Iosup, A., Ostermann, S., Yigitbasi, M.N., Prodan, R., Fahringer, T., Epema, D.H.J.: Performance analysis of cloud computing services for many-tasks scientific computing. IEEE Trans. Parallel Distrib. Syst. 22 , 931–945 (2011)

Iyer, B., Henderson, J.C.: Preparing for the future: understanding the seven capabilities cloud computing. MIS Q. Exec. 9 , 2 (2010)

Jha, S. and Kathuria, A. Size Matters for Cloud Capability and Performance (2022)

Jha, S., Kathuria, A.: How firm age and size influence value creation from cloud computing (2023)

Joe-Wong, C., Sen, S.: Harnessing the power of the cloud: revenue, fairness, and cloud neutrality. J. Manage. Inf. Syst. 35 , 813–836 (2018)

Joint, A., Baker, E.: Knowing the past to understand the present–issues in the contracting for cloud based services. Comput. Law Secur. Rev. 27 (4), 407–415 (2011)

Karhade, P., Kathuria, A.: Missing impact of ratings on platform participation in India: a call for research in GREAT domains. Commun. Assoc. Inf. Syst. 47 (1), 19 (2020)

Karhade, P., Kathuria, A., Dasgupta, A., Malik, O., Konsynski, B.R.: Decolonization of digital platforms: a research agenda for GREAT domains. In: Garimella, A., Karhade, P., Kathuria, A., Liu, X., Xu, J., Zhao, K. (eds.) The Role of e-Business during the Time of Grand Challenges. LNBIP, vol. 418, pp. 51–58. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79454-5_5

Chapter   Google Scholar  

Karhade, P., Kathuria, A., Konsynski, B.: When choice matters: assortment and participation for performance on digital platforms (2021)

Kathuria, A., Karhade, P.P., Konsynski, B.R.: In the realm of hungry ghosts: multi-level theory for supplier participation on digital platforms. J. Manag. Inf. Syst. 37 (2), 396–430 (2020)

Kathuria, A., Mann, A., Khuntia, J., Saldanha, T.J.V., Kauffman, R.J.: A strategic value appropriation path for cloud computing. J. Manage. Inf. Syst. 35 (3), 740–775 (2018). https://doi.org/10.1080/07421222.2018.1481635

Kaur, J., Kaur, P.D.: CE-GMS: A cloud IoT-enabled grocery management system. Electron. Commer. Res. Appl. 28 , 63–72 (2018)

Kepes, B.: 30% of servers are sitting “Comatose” according to research. Forbes https://forbes.com/sites/benkepes/2015/06/03/30-of-servers-are-sitting-comatose-according-to-research (2015)

Khokhar, R.H., Fung, B.C.M., Iqbal, F., Alhadidi, D., Bentahar, J.: Privacy-preserving data mashup model for trading person-specific information. Electron. Commer. Res. Appl. 17 , 19–37 (2016)

Khuntia, J., Kathuria, A., Andrade-Rojas, M.G., Saldanha, T., Celly, N.: How foreign and domestic firms differ in leveraging IT-enabled supply chain information integration in BOP markets: the role of supplier and client business collaboration. J. Assoc. Inf. Syst. 22 (3), 6 (2021)

King, W.R., He, J.: Understanding the role and methods of meta-analysis in IS Research. Commun. Assoc. Inf. Syst. 16, 665–686 (2005)

Krancher, O., Luther, P., Jost, M.: Key affordances of Platform-as-a-Service: self-organization and continuous feedback. J. Manage. Inf. Syst. 35 , 776–812 (2018)

Kumar, C., Marston, S., Sen, R., Narisetty, A.: Greening the cloud: a load balancing mechanism to optimize cloud computing networks. J. Manage. Inf. Syst. 39 ,, 513–541 (2022)

Kung, L., Cegielski, C.G., Kung, H.-J.: An integrated environmental perspective on software as a service adoption in manufacturing and retail firms. J. Inf. Technol. 30 , 352–363 (2015)

Lansing, J., Benlian, A., Sunyaev, A.: Unblackboxing” decision makers’ interpretations of IS certifications in the context of cloud service certifications. J. Assoc. Inf. Syst. 19 (11), 1064–1096 (2018)

Lansing, J., Siegfried, N., Sunyaev, A., Benlian, A.: Strategic signaling through cloud service certifications: Comparing the relative importance of certifications’ assurances to companies and consumers. J. Strateg. Inf. Syst. 28 , 101579 (2019)

Lansing, J., Sunyaev, A.: Trust in cloud computing. ACM SIGMIS Database DATABASE Adv. Inform. Syst. 47 , 58–96 (2016)

Lee, J., Cho, D., Lim, G.: Design and validation of the bright internet. J. Assoc. Inform. Syst. 19 , 63–85 (2018)

Lee, M.H., Han, S.P., Park, S., Oh, W.: Positive demand spillover of popular app adoption: implications for platform owners’ management of complements. Inf. Syst. Res. 34 (3), 961–995 (2023)

Li, S., Chen, W., Chen, Y., Chen, C. and Zheng, Z.: Makespan-minimized computation offloading for smart toys in edge-cloud computing. Electron. Commerce Res. Appl. 37 , 100884 (2019)

Li, S., Cheng, H.K., Duan, Y., Yang, Y.-C.: A study of enterprise software licensing models. J. Manag. Inf. Syst. 34 (1), 177–205 (2017)

Lins, S., Schneider, S., Szefer, J., Ibraheem, S., Ali, A.: Designing monitoring systems for continuous certification of cloud services: deriving meta-requirements and design guidelines. Commun. Assoc. Inf. Syst. 44 (1), 460–510 (2019)

Liu, Y., Sheng, X., Marston, S.R.: The impact of client-side security restrictions on the competition of cloud computing services. Int. J. Electron. Comm. 19 (3), 90–117 (2015)

Ma, D., Seidmann, A.: Analyzing software as a service with per-transaction charges. Inf. Syst. Res. 26 , 360–378 (2015)

Malik, O., Jaiswal, A., Kathuria, A., Karhade, P.: Leveraging BI systems to overcome infobesity: a comparative analysis of incumbent and new entrant firms (2022)

Mani, D., Srikanth, K., Bharadwaj, A.: Efficacy of R&D work in offshore captive centers: an empirical study of task characteristics, coordination mechanisms, and performance. Inf. Syst. Res. 25 (4), 846–864 (2014)

Mann, A., Kathuria, A., Khuntia, J., Saldanha, T.: Cloud-integration and business flexibility: the mediating role of cloud functional capabilities (2016)

Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., Ghalsasi, A.: Cloud computing — the business perspective. Decis. Support. Syst. 51 (1), 176–189 (2011)

Mell, P.M., Grance, T.: The NIST definition of cloud computing. National Institute of Standards and Technology (2011)

Metz, C.: The epic story of dropboxs exodus from the amazon cloud empire (2016)

Mithas, R., Sambamurthy,: How information management capability influences firm performance. MIS Q. 35 (1), 237 (2011)

Mithas, T., Bardhan, G.: Information technology and firm profitability: mechanisms and empirical evidence. MIS Q. 36 (1), 205 (2012)

Muhic, M., Bengtsson, L., Holmström, J.: Barriers to continuance use of cloud computing: evidence from two case studies. Inf. Manage. 60 , 103792 (2023)

Mukherjee, A., Sundarraj, R.P., Dutta, K.: Time-preference-based on-spot bundled cloud-service provisioning. Decis. Support. Syst. 151 , 113607 (2021)

Müller, S.D., Holm, S.R., Søndergaard, J.: Benefits of cloud computing: literature review in a maturity model perspective. Commun. Assoc. Inform. Syst. 37 , 851–878 (2015)

Ojala, A.: Business models and opportunity creation: how IT entrepreneurs create and develop business models under uncertainty. Inf. Syst. J. 26 , 451–476 (2015)

Oliveira, T., Thomas, M., Espadanal, M.: Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Inf. Manage. 51 , 497–510 (2014)

Owens, D. Securing elasticity in the cloud. Communications of the ACM , 53, 6 (2010/06 2010), 46–51 (2010)

Pang, M.-S., Tanriverdi, H.: Strategic roles of IT modernization and cloud migration in reducing cybersecurity risks of organizations: the case of U.S. federal government. J. Strat. Inf. Syst. 31 , 101707 (2022)

Park, J., Han, K., Lee, B.: Green cloud? An empirical analysis of cloud computing and energy efficiency. Manage. Sci. 69 , 1639–1664 (2023)

Parno, B., Howell, J., Gentry, C., Raykova, M.: Pinocchio. Commun. ACM 59 , 103–112 (2016)

Pye, J., Rai, A., Dong, J.Q.: Business value of information technology capabilities: an institutional governance perspective. Inf. Syst. Res. 35 , 28–44 (2023)

Ramakrishnan, T., Kathuria, A., Khuntia, J., Konsynski, B.: IoT value creation through supply chain analytics capability (2022)

Retana, G., Forman, C., Narasimhan, S., Niculescu, M.F., Wu, D.J.: Technical support, knowledge transfer, and service demand: evidence from the cloud. SSRN Electron. J. (2012)

Rodrigues, J., Ruivo, P., Oliveira, T.: Mediation role of business value and strategy in firm performance of organizations using software-as-a-service enterprise applications. Inf. Manag. 58 (1), 103289 (2021)

Saldanha, T.J., Andrade-Rojas, M.G., Kathuria, A., Khuntia, J., Krishnan, M.: How the locus of uncertainty shapes the influence of CEO long-term compensation on IT capital investments. MIS Q. (2023)

Sambhara, C., Rai, A., Xu, S.X.: Configuring the enterprise systems portfolio: the role of information risk. Inf. Syst. Res. 33 (2), 446–463 (2022)

Sarker, S., Chatterjee, S., Xiao, X., Elbanna, A.: The sociotechnical axis of cohesion for the IS discipline: its historical legacy and its continued relevance. MIS Q. 43 (3), 695–720 (2019)

Schlagwein, D., Thorogood, A., Willcocks, L.P.: How commonwealth bank of Australia gained benefits using a standards-based, multi-provider cloud model. MIS Q. Exec. 13 (4), 209–222 (2014)

Schneider, S., Sunyaev, A.: Determinant factors of cloud-sourcing decisions: reflecting on the IT outsourcing literature in the era of cloud computing. J. Inf. Technol. 31 (1), 1–31 (2016). https://doi.org/10.1057/jit.2014.25

Schneider, S., Wollersheim, J., Krcmar, H., Sunyaev, A.: How do Requirements evolve over Time? A case study investigating the role of context and experiences in the evolution of enterprise software requirements. J. Inf. Technol. 33 (2), 151–170 (2018)

Schniederjans, D.G., Hales, D.N.: Cloud computing and its impact on economic and environmental performance: a transaction cost economics perspective. Decis. Support. Syst. 86 , 73–82 (2016)

Schreieck, M., Wiesche, M., Krcmar, H.: Capabilities for value co-creation and value capture in emergent platform ecosystems: a longitudinal case study of SAP’s cloud platform. J. Inf. Technol. 36 (4), 365–390 (2021)

Shiau, W.-L., Chau, P.Y.K.: Understanding behavioral intention to use a cloud computing classroom: a multiple model comparison approach. Inf. Manag. 53 (3), 355–365 (2016)

Singh, V.K., Shivendu, S., Dutta, K.: Spot instance similarity and substitution effect in cloud spot market. Decis. Support. Syst. 159 , 113815 (2022)

Soh, F., Setia, P.: The impact of dominant IT infrastructure in multi-establishment firms: the moderating role of environmental dynamism. J. Assoc. Inf. Syst. 23 (6), 1603–1633 (2022)

Son, I., Lee, D., Lee, J.-N., Chang, Y.B.: Market perception on cloud computing initiatives in organizations: an extended resource-based view. Inf. Manag. 51 (6), 653–669 (2014)

Srinivasan, S.: Is security realistic in cloud computing? J. Int. Technol. Inf. Manag. 22 (4), 3 (2013). https://doi.org/10.58729/1941-6679.1020

Article   MathSciNet   Google Scholar  

Sun, T., Shi, L., Viswanathan, S., Zheleva, E.: Motivating effective mobile app adoptions: evidence from a large-scale randomized field experiment. Inf. Syst. Res. 30 (2), 523–539 (2019)

Templier, M., Paré, G.: Transparency in literature reviews: an assessment of reporting practices across review types and genres in top IS journals. Eur. J. Inf. Syst. 27 (5), 503–550 (2017). https://doi.org/10.1080/0960085X.2017.1398880

Trenz, M., Huntgeburth, J., Veit, D.: Uncertainty in cloud service relationships: uncovering the differential effect of three social influence processes on potential and current users. Inf. Manage. 55, 971–983 (2018)

van de Weerd, I., Mangula, I.S., Brinkkemper, S.: Adoption of software as a service in Indonesia: examining the influence of organizational factors. Inf. Manage. 53 (7), 915–928 (2016)

Venkatesh, V., Bala, H., Sambamurthy, V.: Implementation of an information and communication technology in a developing country: a multimethod longitudinal study in a Bank in India. Inf. Syst. Res. 27 (3), 558–579 (2016)

Venkatesh, V., Sykes, T.A.: Digital divide initiative success in developing countries: a longitudinal field study in a Village in India. Inf. Syst. Res. 24 (2), 239–260 (2013)

Venters, W., Whitley, E.A.: A critical review of cloud computing: researching desires and realities. J. Inf. Technol. 27 (3), 179–197 (2012)

Wang, N., Huigang Liang, Yu., Jia, S.G., Xue, Y., Wang, Z.: Cloud computing research in the IS discipline: a citation/co-citation analysis. Decis. Support. Syst. 86 , 35–47 (2016)

Wang, X., Wang, X.: Multimedia data delivery based on IoT clouds. Commun. ACM 64 (8), 80–86 (2021)

Winkler, T.J., Benlian, A., Piper, M., Hirsch, H.: Bayer healthcare delivers a dose of reality for cloud payoff mantras in multinationals. MIS Q. Exec. 13 , 4 (2014)

Winkler, T.J., Brown, C.V.: Horizontal allocation of decision rights for on-premise applications and Software-as-a-Service. J. Manage. Inf. Syst. 30 (3), 13–48 (2013)

Wright, R.T., Roberts, N., Wilson, D.: The role of context in IT assimilation: a multi-method study of a SaaS platform in the US nonprofit sector. Eur. J. Inf. Syst. 26 (5), 509–539 (2017). https://doi.org/10.1057/s41303-017-0053-2

Wulf, F., Lindner, T., Strahringer, S., Westner, M.: IaaS, PaaS, or SaaS? The why of cloud computing delivery model selection: vignettes on the post-adoption of cloud computing. In: The Proceedings of Proceedings of the 54th Hawaii International Conference on System Sciences, pp. 6285–6294 (2021)

Xiong, Hu., Wang, Yi., Li, W., Chen, C.-M.: Flexible, efficient, and secure access delegation in cloud computing. ACM Trans. Manage. Inf. Syst. 10 (1), 1–20 (2019)

Yang, H., Tate, M.: A descriptive literature review and classification of cloud computing research. Commun. Assoc. Inf. Syst. 31 (1), 2 (2012)

Yaraghi, N., Du, A.Y., Sharman, R., Gopal, R.D., Ramesh, R.: Health Information exchange as a multisided platform: adoption, usage, and practice involvement in service co-production. Inf. Syst. Res. 26 (1), 1–18 (2015)

Yuan, S., Sanjukta Das, R., Ramesh, C.Q.: Service agreement trifecta: backup resources, price and penalty in the availability-aware cloud. Inf. Syst. Res. 29 (4), 947–964 (2018)

Zhang, G., Ravishankar, M.N.: Exploring vendor capabilities in the cloud environment: a case study of Alibaba cloud computing. Inf. Manage. 56 , 343–355 (2019)

Zhang, X., Yue, W.: Integration of on-premises and cloud-based software: the product bundling perspective. J. Assoc. Inform. Syst. 21 , 1507–1551 (2020)

Zorrilla, M., García-Saiz, D.: A service oriented architecture to provide data mining services for non-expert data miners. Decis. Support. Syst.. Support. Syst. 55 (1), 399–411 (2013). https://doi.org/10.1016/j.dss.2012.05.045

Download references

Author information

Authors and affiliations.

SP Jain Institute of Management and Research, Mumbai, India

Shailaja Jha

Indian School of Business, Hyderabad, India

Devina Chaturvedi

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Devina Chaturvedi .

Editor information

Editors and affiliations.

#6104, Indian School of Business, Hyderabad, Telangana, India

Abhishek Kathuria

Chinese University of Hong Kong, Sha Tin District, Hong Kong

Prasanna P. Karhade

University of North Carolina at Charlotte, Charlotte, NC, USA

Indian School of Business, Hyderabad, Telangana, India

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Cite this paper.

Jha, S., Chaturvedi, D. (2024). Systematic Literature Review of Cloud Computing Research Between 2010 and 2023. In: Kathuria, A., Karhade, P.P., Zhao, K., Chaturvedi, D. (eds) Digital Transformation in the Viral Age. WeB 2022. Lecture Notes in Business Information Processing, vol 508. Springer, Cham. https://doi.org/10.1007/978-3-031-60003-6_5

Download citation

DOI : https://doi.org/10.1007/978-3-031-60003-6_5

Published : 21 May 2024

Publisher Name : Springer, Cham

Print ISBN : 978-3-031-60002-9

Online ISBN : 978-3-031-60003-6

eBook Packages : Computer Science Computer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

TechRepublic

Cloud and Hybrid Cloud: Differences and Use Cases

Account Information

Share with your friends.

Your email has been sent

Modern digital infrastructures, where companies run business-critical operations, are possible thanks to cloud computing.

There are different types of cloud computing; they might be private or public, or combine edge and cloud technologies. These classifications can often lead to confusion about what a cloud computing infrastructure is and how it differs from a hybrid cloud operation.

This analysis, written by Ray Fernandez for TechRepublic Premium, will do a deep dive into cloud and hybrid cloud technologies, explaining their differences and use cases.

Featured text from the download:

THE DIFFERENT TYPES OF HYBRID CLOUDS

Hybrid clouds also have different kinds of models. Let’s look at what tiered hybrid, edge hybrid and cloud bursting are.

Tiered hybrid: In this type of hybrid cloud, frontend applications are deployed on public clouds; usually, these are customer-facing, while backend applications run on on-premises or private clouds. This type of cloud is deployed to increase efficiency, security, ownership and reliability.

Edge hybrid: Edge hybrid clouds are deployed when a company needs to bring the data closer to the user to reduce latency or prevent downtime of business-critical operations in case there is no internet connection. These can be deployed, for example, in ocean logistics operations, factories, power plants or point of sales.

Cloud bursting: The cloud bursting model involves using a private computing environment for the baseline load and bursting the cloud temporarily when extra capacity is needed. These types of hybrid models are commonly used by companies or organizations that experience peak surges in traffic and use public cloud resources to meet those demands.

Enhance your cloud knowledge with our in-depth nine-page PDF. This is available for download at just $9. Alternatively, enjoy complimentary access with a Premium annual subscription. Click here to find out more.

TIME SAVED: Crafting this content required 18 hours of dedicated writing, editing and research.

Subscribe to the TechRepublic Premium Exclusives Newsletter

Save time with the latest TechRepublic Premium downloads, including customizable IT & HR policy templates, glossaries, hiring kits, features, event coverage, and more. Exclusively for you! Delivered Tuesdays and Thursdays.

Resource Details

* Sign up for a TechRepublic Premium subscription for $299.99/year, and download this content as well as any other content in our library. Cancel anytime. Details here .

Create a TechRepublic Account

Get the web's best business technology news, tutorials, reviews, trends, and analysis—in your inbox. Let's start with the basics.

* - indicates required fields

Sign in to TechRepublic

Lost your password? Request a new password

Reset Password

Please enter your email adress. You will receive an email message with instructions on how to reset your password.

Check your email for a password reset link. If you didn't receive an email don't forgot to check your spam folder, otherwise contact support .

Welcome. Tell us a little bit about you.

This will help us provide you with customized content.

Want to receive more TechRepublic news?

You're all set.

Thanks for signing up! Keep an eye out for a confirmation email from our team. To ensure any newsletters you subscribed to hit your inbox, make sure to add [email protected] to your contacts list.

Billing Information

Payment information.

Your total Single Purchase Charges

• USD $ 99.00 Subtotal
• USD $ 0.00 Tax, GST, or VAT
• USD $ 0.00 Discount

Upgrade To A Subscription And Save

• USD $ 299.00 Subtotal

A credit card or PayPal account is required for purchase. You will be billed the total shown above and you will receive a receipt via email once your payment is processed.

A credit card or PayPal account is required to activate your subscription. You will be billed $299.00/year and you will receive a receipt via email once your payment is processed. You may cancel your subscription with at least 10 business days notice prior to the expiration of your current subscription by accessing the Premium tab in your TechRepublic Profile and selecting "Cancel Subscription."

TechRepublic Premium is the fastest, smartest way to solve the toughest IT problems. Subscribe to access our full library of resources and gain benefits from:

Quick access to expert analysis from IT leaders, original research and surveys, comprehensive guides on hot topics, and eBooks from TechRepublic.

Ready-to-go policies and initiatives, downloadable templates and forms you can customize, and hundreds of time-saving tools, calculators and kits.

More From Forbes

The new cloud era of data-platform-hosted apps.

• Share to Facebook
• Share to Twitter
• Share to Linkedin

Vanja Josifovski is the Co-Founder and CEO of Kumo AI.

The 2000s spurred a new era in computing—the cloud era. Large companies needed to process massive amounts of data, and at a certain point, buying mainframe computers to do so became simply too expensive. As explained in a TechTarget article (gated), around that time, “Amazon, Google and Microsoft were building vast data centers to accommodate the rapid growth of online commerce and applications.” Then AWS started the infrastructure as a service (IaaS) industry “as an outgrowth of previous efforts to create its Amazon marketplace for third-party retailers.” After developing the framework for the marketplace, “some at the company realized that they had unused capacity—particularly outside peak shopping periods—that could be rented on demand.” Not long after, according to TechTarget, Microsoft and Google introduced cloud services of their own.

Today, it’s common for companies to buy computing power and storage from cloud providers like Amazon and Google. While their business models are largely centered on computing and storage, some cloud providers also sell tools that enable customers to build their own applications. An issue with that, however, is that it’s up to users to understand how to locate, store and process the data needed to build applications. It requires that companies find the people with the right skills to do so and can be a time-consuming, costly endeavor—and on top of that, they have to solve the security and compliance issues that come with having multiple copies of data.

The Data Storage Wars

Today, data processing is moving toward where the data is. New companies have entered the data storage wars. These companies enable their customers to go beyond storing and analyzing their data; they enable them to quickly and seamlessly build applications in ecosystems directly where their data is housed. Essentially, these data-platform-hosted apps are akin to an app store for data applications.

Customers who use these platforms don’t have to extract their data, deal with security and compliance issues, worry about making multiple backups of the data, and so forth. Additionally, these data-platform-hosted apps provide primitives for accessing and processing large amounts of data, including distributed data. These platforms tend to buy computing and storage in bulk from cloud providers, and with one click, customers can have their data stored in multiple places.

Apple Brings Back iPhone 14 Pro For First Time—At Lower Price, Refurbished

Trump lashes out at robert de niro after actor calls him a tyrant outside courthouse, elon musk is the world s richest person again thanks to his new ai startup, the pros and cons of using data-platform-hosted apps.

A major advantage of using these new data-platform-hosted apps is that customers can increase their speed of deploying new solutions. Using these data-platform-hosted apps, they can iterate and innovate, building and testing new solutions for the market faster than before. Moreover, they can try new technologies and more quickly determine if it’s the right path for them—before investing too much time and money. Then there’s the lowering of overhead costs. Companies that turn to these new data platform providers won’t have to spend as much time and money on finding developers to write code. Other advantages include lowering the costs of copying data, having built-in data sharing capabilities and having more robust security and compliance.

However, it’s unclear how the economics of this nascent ecosystem will play out in the long term. There could very well be increased costs. When you have a middle party involved—in this case, these data-platform-hosted apps are acting as an intermediary between customers and cloud storage providers—someone is going to take a bigger cut of the profits. Customers might find themselves paying more for basic storage and compute. Another disadvantage is the shifting balance of power between the different players. Whenever there’s an intermediary in the picture, you lose some of the control that you otherwise would have had dealing with the other party yourself.

To mitigate these risks, companies should avoid repeating the patterns we see in the traditional cloud world, such as adding more jobs, pipelines and data transformations, which raises costs. Instead, they should use data-platform-hosted apps in a measured way.

The Age Of Data Platforms

Moving forward, I predict that complex applications will be built on top of data platforms with higher-level abstractions rather than built from basic components over storage and compute. This is akin to the move from languages like C to languages like Java that abstracted some common tasks, such as memory management. The net result in this will be better, more secure apps that will require less data manipulation and management. Additionally, artificial intelligence, such as predictive analytics, can help customers do more with the data at their fingertips. As data-platform-hosted apps integrate AI, I expect their usage to rise in the market.

We are in the middle of the biggest transformation of cloud computing since it began in the 2000s. The old way of customers having to build complex systems and then painstakingly manage the many different pieces of those systems is reaching an end. Data will be able to flow more fluidly, simplifying the building of new applications. And to prepare for this future, SaaS providers should start restructuring their offerings to integrate with these new data-platform-hosted apps—lest they be left behind like the companies that didn’t move to cloud-first designs.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

• Editorial Standards
• Reprints & Permissions