Implementing a cloud strategy can no longer be called optional; it is a necessary step to keep up with technological advances and remain competitive in the market. This is even more important for SMEs, which risk falling behind larger competitors. In recent years, a large number of tech companies have begun to take advantage of these opportunities and switched to cloud solutions (at least with SaaS models).
Unfortunately, this is also a technology that is very difficult to implement, for example, because it is often misjudged (overestimated or underestimated), there is a lack of talent, and its impact can be very large both technologically and organizationally.
Catching up is necessary, but far from obvious. Companies often lack the necessary knowledge, and the absorptive capacity to integrate research results and market or open-source alternatives into their operations. This often results in a hasty solution that allows a company to move to the cloud, but then has to spend a very large amount of time/effort/money to address outstanding challenges. In many cases, the listed challenges are a direct result of the lack of cloud knowledge at companies. This lack of knowledge also typically results in less cost-efficient use of cloud technologies, which is also identified as one of the top cloud initiatives by companies.

To better formalize this, we identified the following challenges to tackle:

  1. The observation of the usage of research data, new developments leading to new services, applications and product development, but especially where engagement in cloud technology is an absolute necessity in the exploitation of the applications and innovations.
  2. The understanding that there are, even among open-source solutions, a proliferation of opportunities to develop, manage and improve cloud solutions.
  3. The realisation that companies do not always have the ability to fully understand the evolutions in Cloud technologies and sometimes make unfounded choices that can have far-reaching
    consequences (e.g. in terms of vendor lock-in and/or licensing costs).
  4. The observation that even ICT innovators are struggling with a lack of sufficient internal practical knowledge and the lack of sufficient resources (this challenge is even greater in small and medium-sized companies).

The OpenCloudification project positions itself in the value chain to provide guidance and expertise needed for the responsible implementation of cloud solutions. This is seen by moving along with the following categories:

  • Basic Level – Help companies that have not yet moved to the cloud. It will be mainly achieved by providing knowledge, guidelines and tips. This is also helpful for companies that have already moved to the cloud and can be able to improve or compare with the current solutions available.
  • Intermediate Level – Guide companies to improve their cloud experience. It can be mostly achieved in two separate phases: by removing potential bottlenecks, such as incorrect approaches (regarding technologies, IT stack, data, people, and so on), lack of integration or lack of knowledge about new opportunities and introducing new procedures, better practices, standards, new technologies, etc.
  • Advanced Level –Bring state-of-the-art research, solutions, and innovations to tech companies. This will lead to an increase in their impact and their knowledge and an improvement of their cloud environments and, in perspective, their impact to direct and indirect customers.

While the first two levels are the starting point of the project, the latter is the central focus of it. Through translation research and cloud knowledge building, we want to give technology companies faster access to modern cloud knowledge. Also, a more approachable use of cloud technology will be pursued, by allowing hands-on experience with building up technology (e.g., via tools and sandbox environments) and, where necessary, offering customized components which, with limited commissioning are quickly deployable for the companies.
Innovation can be achieved by adopting suggested technologies, such as for example, the transition from Virtual Machines to containerized solutions (Kubernetes as the de-facto standard for open-source container orchestration, see image below) and newer trends within cloud research such as vendor-neutral serverless solutions.

Small/Medium Businesses use of container tools. Source: Flexera, State of the Cloud 2022

For many companies, this is a big leap in the dark. However, provided proper guidance, companies can be correctly informed about Cloud opportunities and which technologies are better avoided at this point in time. All this should lead to a further appreciation of the possibilities of cloud (and edge) processing, and the absorption of modern Cloud developments/innovations. Thus, companies innovate and gain knowledge.

Biggest benefits and Challenges for companies after adopting serverless solutions. O’Reilly, serverless survey 2019.

Approach and implementation

The objective of OpenCloudification is to impart the necessary knowledge regarding innovative/modern/advanced Cloud aspects with the aim of improving the use of new Cloud technologies by tech companies. This project aims to solve this by focusing strongly on the following core activities:

  • Business modelling, cost modelling, use cases – inspiration seminars
  • Networking and stimulating cooperation
  • Translation research
  • Development of customized open-source components
  • Documented Knowledge Transfer (use cases, white papers, training, etc.)
  • Demonstrators and learning environments to support knowledge dissemination
  • Workshops and hands-on collaboration.

Translation research is an important pillar to ensure that research conducted in our knowledge institutions can be delivered in an understandable way to the industry. The focus here is to keep up with the rapidly evolving field of cloud developments, to be kept up to date by the participating companies, and to alert them of potentially interesting evolutions in this area. The dissemination of translation research should also allow companies to access (new) research collaborations with knowledge institutions.

A second pillar is knowledge dissemination, consisting of a wide range of both inspiration seminars and
technical workshops. For example, the inspiration seminars are aimed more at a broad public, including management and middle management, whereas the technical workshops are mainly aimed at more technical profiles. The difference between the two is that inspiration seminars primarily aim to inspire relevant stakeholders and make them aware of the opportunities and challenges of cloud technology, modern possibilities (traceability, orchestration), etc. Inspiration seminars are therefore more likely to target a business audience (business leaders, marketing, business development), while the technical workshops will focus instead in detail on specific technical topics, such as container orchestration solutions, service mesh, tracing, serverless technology, APIs, VM and container registries, etc. Therefore, the technical workshops are aimed more at developers, architects, engineering, CTO/CIOs, etc. The advantage of this approach is that it allows the project to strongly differentiate according to the intended target groups.

A third pillar is the development of both components based on open-source and demonstrators/learning environments. To prevent the delivered knowledge from remaining too abstract (and too “academic”), it should be tailored as concretely as possible to use cases and examples that are recognizable to the target companies. In the project, this alignment is integrated into all the project activities. For example, during the seminars and workshops, feedback from the target group companies will be used to further refine the content. A setup will also be set up for demonstration purposes so that processes and technical methods can be concretely applied to this demonstrator. In addition to demonstrators, a learning/sandbox environment will also be built, allowing users to gain hands-on experience with key technologies covered in the workshops (e.g., serverless technology and cloud-edge orchestration). Such demonstrators and sandbox can be an accelerator for companies to continue working on a particular technology themselves since the required knowledge leap is significantly reduced thanks to the activities in this project.

It is also important to emphasize that most of the project activities can run in parallel. They can be carried out without continuous prior steps and are therefore not completely dependent on possible difficulties arising from individual tasks.

Translating the state-of-the-art research

Cloud computing cannot be seen as a static solution; on the contrary, it is a dynamic environment that is constantly evolving, with highly active research that makes improvements and can change its shape it can change. For example, in [1] the authors describe the various changes within the concept of cloud computing, starting with a client-server model, moving to Grid computing, then cluster computing, XaaS models, and finally ending with the architectures we know today, such as cloud and edge computing. This is why the research translation is crucial to the project: not only to introduce and implement state-of-the-art solutions within these companies but also to predict future trends and evolutions so that they can be quickly applied within a business innovation journey.
The field of cloud computing is broad and covers multiple sectors. Therefore, another important step of the research will be to filter and select only those topics that are in line with the scope of the project and the target audience. This is also described in the scientific literature such as in [2], where conducted research is analyzed and future challenges of cloud computing are presented, or in [3], with a focus on the future of edge cloud and edge computing solutions for IoT applications. Future directions and challenges are presented along with innovative and ready-to-use applications, for example in [4], where a system for high-performance serverless processing is presented or in [5], with the migration of applications from monolithic structures to microservices architectures.

To summarize the research aspects, this project will start providing new research findings and examples of:

a) Research on cloud-edge use cases (where there needs to be a thorough integration of edge devices with the cloud backend, in order to dynamically exchange processing tasks and data between edge hardware and the cloud backend)

b) Research on VM and container orchestration (e.g., how to schedule cost-effectively)

c) Research on multi-cloud operations (CI/CD and Infrastructure-as-Code among others)

d) Research on scalable management of cloud environments

e) Research on monitoring cloud solutions (how to build traceability in microservice-based applications)

f) Research on solutions for serverless technology on Kubernetes.

[1] Sukhpal Singh Gill et al. “Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges”, Internet of Things, Volume 8, 2019, 100118, ISSN 2542-6605,
[2] Prince Kwame Senyoa et al. “Cloud computing research: A review of research themes, frameworks, methods and future research directions”, International Journal of Information Management, Volume 38, Issue 1, 2018, Pages 128-139, ISSN 0268-4012,
[3] J. Pan and J. McElhannon, “Future Edge Cloud and Edge Computing for Internet of Things Applications,” in IEEE Internet of Things Journal, vol. 5, no. 1, pp. 439-449, Feb. 2018,
[4] Akkus et al., “SAND: Towards High-Performance Serverless Computing”, 2018, Usenix Annual Technical Conference (USENIX ATC 18), pp. 923–935, 2018
[5] Zhongshan Ren et al. “Migrating Web Applications from Monolithic Structure to Microservices Architecture”. In Proceedings of the Tenth Asia-Pacific Symposium on Internetware (Internetware ’18). Association for Computing Machinery, 2018, New York, NY, USA, Article 7, 1–10.

OpenCloudification Asks

Which Open Cloud Technologies are you using or considering to use?