In this era of virtualisation, the abstraction of underlying hardware resources and the prominence of tools for infrastructural automation have been key enablers for the deployment of distributed services at scale. The growing role of software in managing infrastructures and the DevOps movement, focused on the automation of infrastructure management, are targeting the challenges of increasing speed and quality of infrastructure management, thus lowering costs and enhancing security and trustworthiness. However, the market of infrastructure automation tools is fragmented, there is no single one to manage the whole lifecycle of infrastructure as code (IaC) and existing solutions do not address all trustworthiness and security aspects throughout the whole lifecycle. PIACERE will develop tools, techniques and methods enabling organisations to fully embrace the IaC approach through the DevSecOps philosophy. PIACERE will provide the first Integrated Development Environment (IDE) to develop and verify IaC. Exploiting Model-Driven Engineering (MDE), the IDE will enable developers to create infrastructural code at an abstract level. Using the novel DevOps Modelling Language (DOML), the DevOps team will generate IaC for different languages and verify its correctness at model and code level along with the corresponding security components. The IDE is one part of the complete workflow and will be supported with: 1) a canary environment to aid the simulation of the conditions of the production environment allowing the early identification of potential vulnerabilities and 2) an IaC execution Environment to automatically deploy, monitor and ensure that the conditions are met, incorporating self-healing and self-learning features. The integration, security first and IaC polyglotism arm the DevSecOps teams to treat and work with IaC as they do with traditional code, simplifying the design, development and operation of IaC, while increasing their productivity, quality and reliability

The rapid increase in demand for data-intensive applications capable of exploiting Big Data technologies such as Hadoop/MapReduce, NoSQL, cloud-based storage, and stream processing is creating massive growth opportunities for European independent software vendors (ISVs). However, developing software that meets the high-quality standards expected for business-critical cloud applications remains a barrier to this market for many small and medium ISVs, which often lack resources and expertise for advanced quality engineering. DICE will tackle this challenge by defining a quality-driven development methodology and related tools that will markedly accelerate the development of business-critical data-intensive applications running on public or private clouds. Building on the principles of model-driven development (MDD) and on popular standards such as UML, MARTE and TOSCA, the project will first define a novel MDD methodology that can describe data and data-intensive technologies in cloud applications. A quality engineering toolchain offering simulation, verification, and numerical optimisation will leverage these extensions to drive the early design stages of the application development and guide software quality evolution. DevOps-inspired methods for deployment, testing, continuous integration and monitoring feedback analysis will be used to accelerate the incorporation of quality in data-intensive cloud application both in public and private deployments, enhancing the capability of small and medium European ISVs to enter the Big Data market.

DataPorts will boost the transition of European seaports from connected and digital to smart and cognitive, by providing a secure environment for the aggregation and integration of data coming from the several data sources existing in the digital ports and owned by different stakeholders, so that the whole port community could get real value from this data in order to improve their processes, offer new services and devise new AI based and data driven business models. To this end, DataPorts will design, implement and operate an Industrial Data Platform (Cognitive Ports Data Platform) that: i) connects to the different digital infrastructures currently existing in digital seaports, enabling the interconnection of a wide variety of systems into a tightly integrated ecosystem, ii) sets the policies for a trusted and reliable data sharing and trading based on data owners rules and offering a clear value proposition, and iii) leverages on the data collected to provide advanced Data Analytic services based on which the different actors in the port value chain could develop novel AI and cognitive applications. DataPorts project involves the design and implementation of the platform, its deployment in two relevant European seaports connecting to their existing digital infrastructures and addressing specific local constraints, a global use case involving these two ports and other actors and targeting inter-port objectives, and all the actions to foster the adoption of the platform at European level. This project will imply that tools, platforms and systems running in the different seaports all across Europe will benefit from the DataPorts industrial data platform, in order to create an even more trusted, reliable and efficient way of conducting businesses in Europe and to reinforce the European Single Market.