# Multi-formalism Models for Performance Engineering
## 1 Introduction  
In 2017, the Economist designated the growing diffusion of data as the _the new oil_ emergency [1], quoting the profit reached in the first quarter of the year generated by the main market actors equal to 25 billion dollars. Although the remark was not exactly original (the same perspective had already been shared by the mathematician [PERSON] in 2006 [2]) and was far from being an obvious analogy [3], it highlighted how applications and services could be characterized to maximize benefit from this new commodity: (i) network access (the ability to grant a broad range of devices access to the Internet); (ii) service metering (a user is billed according to how much service is consumed); (iii) shared architecture (the capability of providing shared resources and infrastructures to all sort of users); and (iv) provisioning according to demand (the need to provide dynamically the requested services). All these requirements converged in a model called _cloud computing_. In Gartner's 2018 Hype Cycle for Cloud Computing (see [[https://www.gartner.com/en/documents/3884671](https://www.gartner.com/en/documents/3884671)]([https://www.gartner.com/en/documents/3884671](https://www.gartner.com/en/documents/3884671))), it is reported that \"Cloud computing has reached the Slope of Enlightenment\" and Forbes announced it is _the new kid in the block_ ([[https://www.forbes.com/sites/forbestechcouncil/2019/11/15/the-next-evolutionary-step-for-cloud-computing/#3e04c1646](https://www.forbes.com/sites/forbestechcouncil/2019/11/15/the-next-evolutionary-step-for-cloud-computing/#3e04c1646) dd7]([https://www.forbes.com/sites/forbestechcouncil/2019/11/15/the-next-evolutionary-step-for-cloud-computing/#3e04c1646](https://www.forbes.com/sites/forbestechcouncil/2019/11/15/the-next-evolutionary-step-for-cloud-computing/#3e04c1646) dd7)), 5G giving a boost to cloud technology in different market areas, such as autonomous cars, virtual reality, healthcare, and smart homes. It is more and more evident that the capacity to offer services such as servers, databases, and storage has become a powerful attractor for the main tech players in the world market, including Amazon, Microsoft, Google, IBM, and Oracle, to name a few. An additional aspect concerns security,chiefy the ability to shield data in the cloud from any kind of malicious intrusion (ranging from hacking to theft) by properly configuring firewalls and VPNs initially and establishing specific policies. Moreover, to guarantee an efficient usage of the cloud architecture, it is necessary to define a Quality of Service (QoS) policy. In [4], quality is defined as consideration of a few key indicators, among others: (i) flexibility (managing a functionality without affecting the system); (ii) maintainability; (iii) performance; and (iv) scalability. The authors stressed the level of difficulty hidden in the choice of a process able to provision a valid QoS agreement for cloud computing architectures, identifying scheduling, admission control, and dynamic resource provisioning the main keys to solving to this problem. User expectations drive the design of the cloud model, which is articulated through four pillars: (i) public (a kind of cloud available to a large audience, which deploys services at a low cost); (ii) private (access is restricted to the members of a particular organization); (iii) community (access is shared by organizations sharing analog motivations); and (iv) hybrid. Such pillars present both advantages and disadvantages. Among the former, the most evident is the cost cutting in IT companies infrastructures regarding implementation, scalability, maintenance, and reliability. Having fluid access to a ubiquitous cloud represents another significant landmark. The most interesting challenge consists of security and privacy matters, followed by some ambiguities in defining the services (this problem has been partially mitigated by the Open Cloud Consortium).