Covid-19 and cloud technologies: All-Cloud IT Operating Model for pandemic management – Part 2
Dr. Petar Radanliev and Professor Dave De Roure, Department of Engineering Sciences, University of Oxford, England, UK
The Covid-19 pandemic has overwhelmed healthcare systems globally, but if global technology policy is supportive, Covid-19 could trigger a digital healthcare transformation suitable for the new digital age. Global pandemics require fast and flexible healthcare systems that promote global collaboration. This could be an opportunity to rethink how healthcare systems operate globally. In the process of digital transformation, health tech start-ups are crucial in discovering new solutions, but it also requires a new mind-set. A mind-set where transformation from capital-intensive IT operations evolves into flexible, low-asset, all-cloud digital IT operations. In this article, we analyze new opportunities of cloud technologies for Covid-19 health tech start-ups.
1 Digital transformations for Covid-19 management
1.1 Operational mobility for health tech in Covid-19 healthcare systems
One of the greatest advantages of cloud technologies is the development of IT operations strategies built upon on-demand cloud computing platforms. This includes flexibility to expand and reduce operations and add/remove new technologies when required by the market demand. Cloud technologies eliminate the need for retrofitting legacy healthcare systems, which is a key cyber-risk factor. In addition, cloud technologies can eradicate the need for enhancements essential for reducing overall costs of healthcare and the implementation of new, fast-changing technologies. It is becoming difficult to justify significant investments in IT infrastructure and specialized personnel, knowing that a comprehensive cloud healthcare service (with state-of-the-art infrastructure—Figure 1) can be rented for a much lower cost.
The cost justification is even worse for Covid-19 start-up healthcare services without established patients and markets. Health tech companies have become the ‘center stage’ in response to Covid-191, but start-ups are high-risk, high-reward operations. With on-demand cloud computing platforms, if the start-up does not prove profitable, there is no significant capital loss from withdrawing operations. In other words, cloud technologies assist health tech start-ups engaging in developing solutions for Covid-19 since the risk of failure, and the financial cost of failure, is much easier to accept, and there is no significant initial capital investment. In the digital era, on-demand cloud computing platforms provide almost instant compliance with constantly increasing regulations. This option for secured compliance with changing regulations provides not only a peace of mind for health tech start-ups, but also serves as an insurance policy against significant data privacy fines, such as GDPR2.
1.2 Cost of cloud platforms for Covid-19 health tech start-ups
The availability of cloud solutions, options for cloud migrations, scaling resources, deploying patches/updates, and completing related tasks make it very easy for health tech start-ups to spend a lot of money. This involves composing a plan to implement cloud technologies into Covid-19 health tech start-ups, choosing cloud consumption strategies, and setting allocations. In other words, managing the start-ups unwanted and unknowing misuse of resources.
1.3 Automation and high-skilled jobs in Covid-19 health tech start-ups IT operations
The IT operations in Covid-19 health tech start-ups cloud infrastructure resembles, to a high degree, application development and programming. While the demand for IT admins and operation managers is decreasing, the demand for skills in scripting and configuration languages (e.g. Python) is increasing. The traditional role of IT operations manager in health tech start-ups will diminish and evolve with the increase of all-cloud solutions. Some traditional IT operations will remain as is (i.e., monitoring security alerts), but these tasks are increasingly becoming automated. The IT operation managers need to diversify their skillsets into gathering telemetry data from remote services – including IoT, consolidating and analyzing data from multiple sources, using analytic software to create actionable dashboards, using scripting and automation tools to eliminate repetitive tasks, etc3. In other words, by adopting cloud services, health tech companies are not losing IT intellectual property, only the IT infrastructure.
As an effect, health tech IT operation managers are gaining more responsibilities and becoming more specialized. Starting from managing patients, users, data, and regulatory controls to becoming more specialized and sophisticated in terms of controlling data movement, encryption, storage allocation, and access controls. The health tech IT operation managers need to enforce regulatory requirements with the evolving cloud security and its related identity and access configurations, e.g. NIST cybersecurity functions in Cloud computing4. Finally, one major task that will predominate health tech IT operations in the near term is the integration of cloud services with existing patient data directories. Since all-cloud subscription seems to be the future, health tech IT operations need to be prepared for this digital transformation.
2 Options for cloud strategies of Covid-19 health tech start-ups?
2.1 Covid-19 cloud IT operating models with AWS
The amazon web services (AWS) healthcare cloud5 presents an on-demand, pay-as-you-go set of infrastructure services, such as computing power, storage options, networking and databases, etc. These services represent building blocks that can be customized, and new services can be added without capital expenditure. While large healthcare providers and the public healthcare sector can hugely benefit from such services, the biggest benefits are for Covid-19 health tech start-ups with limited upfront capital. The security certification and accreditation are stronger (Figure 2) than a data centre on the premise with data encryption at rest and in-transit.
The built-in capabilities for controlling, auditing, and managing identity, configuration, and usage enable an easier process of ensuring compliance, governance, and regulatory requirements. The Amazon EC2 enables resizable compute capacity, and the AWS Auto Scaling enables automatic capacity adjustment. This combination enables balanced optimization of performance and cost.
2.2 Covid-19 cloud IT operating models with IBM cloud
The IBM cloud healthcare6 offers similar solutions as the AWS, but with more focus on valuable solutions vs. lower prices. Since IBM cloud arrived at a much later stage in the cloud-computing market, their strategy is different. For example, IBM offers the IBM Gravitant, a new platform for cloud brokerage and management that enables the comparison of cost and performance from various cloud providers and manages cloud infrastructure across different providers, or in a hybrid configuration.
2.3 Other Cloud options for All-Cloud IT Operations
The Google healthcare cloud7 provides specific Covid-19 services and differentiates through their core competencies in powerful big-data analytics. Products like BigQuery provide managed-data warehousing with fast queries on petabyte-scale datasets. The Microsoft Azure also provides Covid-19 support through an open research dataset8, and differentiates with more comprehensive compliance coverage, including GDPR and intellectual property protection. There are more cloud computing providers (e.g. Adobe, VMware, Oracle Cloud, Verizon Cloud, etc.), and each provider is trying to differentiate and provide specialized services. However, the key products are, in effect, quite similar. To simplify this, all cloud computing products and services for Covid-19 health tech start-ups can be categorized into Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
The health tech start-ups’ cloud capacity manager role requires experience with PaaS and IaaS. Such experience would enable the candidate to identify services tailored to the needs of Covid-19 health tech applications. This would ensure the necessary capacity and reduce spending, but does not necessarily mean managing operations of applications in terms of usage or storage. It is more about the allocation of requirements for operations on one or more cloud providers to ensure deployment. Cloud healthcare technologies (e.g., Google healthcare API9, AWS cloud healthcare5, DXC cloud healthcare10) provide tools to set up roles in the cloud platform and for the cloud capacity manager to control the usage. Some useful tools include the monthly spending and security settings, and the health tech employee access to resources. However, there and many other useful tools for service delivery decisions.
- Martinez-Millana, Antonio., Ibanez-Sanchez, Gema., and Traver, Vicente, “Cloud and Internet of Things Technologies for Supporting In-House Informal Caregivers: A Conceptual Architecture,” in Intelligent Systems Reference Library, vol. 170, Springer Science and Business Media Deutschland GmbH, 2020, pp. 1–28.
- Sehgal, Naresh Kumar., Bhatt, Pramod Chandra P., Acken, John M., Sehgal, Naresh Kumar., Bhatt, Pramod Chandra P., and Acken, John M., “Cloud Computing Pyramid,” in Cloud Computing with Security, Springer International Publishing, 2020, pp. 49–59.
Petar Radanliev is a Post-Doctoral Research Associate at the University of Oxford. He obtained his Ph.D at University of Wales in 2014 and continued with Postdoctoral research at Imperial College London, University of Cambridge, MIT and the University of Oxford. His current research focusses on artificial intelligence, internet of things, cyber risk analytics and social machines.
David De Roure is a Professor of e-Research at University of Oxford. He obtained his PhD at University of Southampton in 1990 and went on to hold the post of Professor of Computer Science, later directing the UK Digital Social Research programme. His current research focusses on social machines, Internet of Things and cybersecurity. He is a Fellow of the British Computer Society and the Institute of Mathematics and its Applications.
Mubashir Husain Rehmani , (M’14-SM’15) received the B.Eng. degree in computer systems engineering from Mehran University of Engineering and Technology, Jamshoro, Pakistan, in 2004, the M.S. degree from the University of Paris XI, Paris, France, in 2008, and the Ph.D. degree from the University Pierre and Marie Curie, Paris, in 2011. He is currently working as an Assistant Lecturer in the Department of Computer Science, Cork Institute of Technology, Ireland. Prior to this, he worked as Post Doctoral Researcher at the Telecommunications Software and Systems Group (TSSG), Waterford Institute of Technology (WIT), Waterford, Ireland. He also served for five years as an Assistant Professor at COMSATS Institute of Information Technology, Wah Cantt., Pakistan. He is currently an Area Editor of the IEEE Communications Surveys and Tutorials. He served for three years (from 2015 to 2017) as an Associate Editor of the IEEE Communications Surveys and Tutorials. He is also serving as Column Editor for Book Reviews in IEEE Communications Magazine. Currently, he serves as Associate Editor of IEEE Communications Magazine, Elsevier Journal of Network and Computer Applications (JNCA), and the Journal of Communications and Networks (JCN). He is also serving as a Guest Editor of Elsevier Ad Hoc Networks Journal, Elsevier Future Generation Computer Systems journal, the IEEE Transactions on Industrial Informatics, and Elsevier Pervasive and Mobile Computing journal. He has authored/ edited two books published by IGI Global, USA, one book published by CRC Press, USA, and one book with Wiley, U.K. He received “Best Researcher of the Year 2015 of COMSATS Wah” award in 2015. He received the certificate of appreciation, “Exemplary Editor of the IEEE Communications Surveys and Tutorials for the year 2015” from the IEEE Communications Society. He received Best Paper Award from IEEE ComSoc Technical Committee on Communications Systems Integration and Modeling (CSIM), in IEEE ICC 2017. He consecutively received the research productivity award in 2016-17 and also ranked # 1 in all Engineering disciplines from the Pakistan Council for Science and Technology (PCST), Government of Pakistan. He received Best Paper Award in 2017 from the Higher Education Commission (HEC), Government of Pakistan. He is the recipient of the Best Paper Award in 2018 from Elsevier Journal of Network and Computer Applications.