Component-aware Orchestration of Cloud-based Enterprise Applications, from TOSCA to Docker and Kubernetes

Enterprise IT is currently facing the challenge of coordinating the management of complex, multi-component applications across heterogeneous cloud platforms. Containers and container orchestrators provide a valuable solution to deploy multi-component applications over cloud platforms, by coupling the lifecycle of each application component to that of its hosting container. We hereby propose a solution for going beyond such a coupling, based on the OASIS standard TOSCA and on Docker. We indeed propose a novel approach for deploying multi-component applications on top of existing container orchestrators, which allows to manage each component independently from the container used to run it. We also present prototype tools implementing our approach, and we show how we effectively exploited them to carry out a concrete case study

Data integration and conceptual modelling of the Larderello geothermal area, Italy

n/

A microservice-based architecture for (customisable) analyses of Docker images

We introduce DockerAnalyser, a microservice-based tool that permits building customised analysers of Docker images. The architecture of DockerAnalyser is designed to crawl Docker images from a remote Docker registry, to analyse each image by running an analysis function, and to store the results into a local database. Users can build their own image analysers by instantiating DockerAnalyser with a custom analysis function and by configuring the architecture. More precisely, the steps needed to obtain new analysers are (1) replacing the analysis function used to analyse crawled Docker images, (2) setting the policy for crawling Docker images, and (3) setting the scalability options for obtaining a scalable architecture. In this paper, we also present 2 different use cases, ie, 2 different analysers of Docker images created by instantiating DockerAnalyser with 2 different analysis functions and configuration options. The 2 use cases show that DockerAnalyser decreases the effort required to obtain new analysers versus building them from scratch

Orchestrating incomplete TOSCA applications with Docker

Cloud applications typically integrate multiple components, each needing a virtualised runtime environment that provides the required software support (e.g., operating system, libraries). This paper shows how TOSCA and Docker can effectively support the orchestration of multi-component applications, even when their runtime specification is incomplete. More precisely, we first introduce a TOSCA-based representation of multi-component applications, and we illustrate how such representation can be exploited to specify only the application-specific components. We then present TOSKERISER, a tool for automatically completing TOSCA application specifications, which can automatically discover the Docker-based runtime environments that provide the software support needed by the application components. We also show how we fruitfully exploited TOSKERISER in two concrete case studies. Finally, we discuss how the specifications completed by TOSKERISER can be automatically orchestrated by already existing TOSCA engines

Container-based Support for Autonomic Data Stream Processing through the Fog

We present a container-based architecture for supporting autonomic data stream processing application on Fog computing infrastructures. Our architecture runs applications as Docker containers, and it exploits Docker’s native features to dynamically scale up/down the resources of a Fog node assigned to the applications running on it. Preliminary results demonstrate that Docker containers are appropriate for building migratable autonomic solutions in the Fog

Hemodynamic variations in arterial wave reflection associated with the application of increasing levels of PEEP in healthy subjects

: Positive end-expiratory pressure (PEEP) may affect arterial wave propagation and reflection, thus influencing ventricular loading conditions. The aim of the study was to investigate the hemodynamic variations in arterial wave reflection (i.e., wave reflection time, augmentation index, left ventricular ejection time, diastolic time, SEVR) associated with the application of increasing levels of PEEP in healthy subjects. We conducted a prospective observational study. Study population was selected from students and staff. Pulse contour wave analysis was performed from the right carotid artery during stepwise increase in PEEP levels (from 0 cmH2O, 5 cmH20, 10 cmH2O) with applanation tonometry. Sixty-two healthy volunteers were recruited. There were no significant changes in heart rate, augmentation index (AIx), left ventricular ejection time, Diastolic time (DT) among all of the different steps. A significant increase of time to the inflection point (Ti) was observed during all steps of the study. Diastolic area under the curve (AUC) divided by systolic-AUC (SEVR) increased from baseline to PEEP = 5 cmH2O, and from baseline to PEEP = 10 cmH2O. AIx and Ti were significantly correlated (directly) at the baseline and during PEEP = 10 cmH2O. Ti and DT were significantly correlated at the baseline and during PEEP = 5 cmH2O. In our preliminary results, low levels of PEEP played a role in the interaction between the heart and the vascular system, apparently mediated by a prolongation of the diastolic phase and a reduction in the systolic work of the heart.Clinical trials registration number: NCT03294928, 19/09/2017