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

Network Service Orchestration: A Survey

Business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5G, Software Defined Networking~(SDN), and Network Function Virtualization~(NFV). Emerging scenarios call for agile network services consuming network, storage, and compute resources across heterogeneous infrastructures and administrative domains. Coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge. Research and development efforts are being devoted to enabling orchestration processes to automate, coordinate, and manage the deployment and operation of network services. In this survey, we delve into the topic of Network Service Orchestration~(NSO) by reviewing the historical background, relevant research projects, enabling technologies, and standardization activities. We define key concepts and propose a taxonomy of NSO approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse NSO application scenarios. Based on the analysis of the state of affairs, we present a series of open challenges and research opportunities, altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration.Comment: Accepted for publication at Computer Communications Journa

Orchestrating applications with TOSCA and Docker

The objective of this thesis was to contribute to automating the deployment of (complex) applications over heterogeneous infrastructures, by trying to combine the orthogonal approaches proposed by TOSCA and Docker. After analysing the state of the art, we designed and prototyped TosKer – the first engine (at the best of our knowledge) that is capable to input a TOSCA description of a multi-component application, and to automatically deploy and orchestrate it on top of Docker

MACHS: Mitigating the Achilles Heel of the Cloud through High Availability and Performance-aware Solutions

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their HA and satisfying the QoS requirements. Second, a Stochastic Petri Net (SPN) model is proposed to capture the stochastic characteristics of cloud services and quantify the expected availability offered by an application deployment. The SPN model is then associated with an extensible policy-driven cloud scoring system that integrates other cloud challenges (i.e. green and cost concerns) with HA objectives. The proposed HA-aware solutions are extended to include a live virtual machine migration model that provides a trade-off between the migration time and the downtime while maintaining HA objective. Furthermore, the thesis proposes a generic input template for cloud simulators, GITS, to facilitate the creation of cloud scenarios while ensuring reusability, simplicity, and portability. Finally, an availability-aware CloudSim extension, ACE, is proposed. ACE extends CloudSim simulator with failure injection, computational paths, repair, failover, load balancing, and other availability-based modules

Blueprint model and language for engineering cloud applications

Abstract: The research presented in this thesis is positioned within the domain of engineering CSBAs. Its contribution is twofold: (1) a uniform specification language, called the Blueprint Specification Language (BSL), for specifying cloud services across several cloud vendors and (2) a set of associated techniques, called the Blueprint Manipulation Techniques (BMTs), for publishing, querying, and composing cloud service specifications with aim to support the flexible design and configuration of an CSBA.

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Exploiting BPMN features to design a fault-aware TOSCA orchestrator

Cloud computing is nowadays a consolidated paradigm that enables scalable access to computing resources and complex services. One of the greatest challenges Cloud providers have to deal with is to efficiently automate the service "provisioning" activities through Cloud orchestration techniques. By relying on TOSCA, a well-known standard specification for the interoperable description of Cloud services, we developed a fault-aware orchestrator capable of automating the workflow for service provisioning. The BPMN notation was used to define both the workflow and the data associated with workflow elements. To corroborate the proposal, a software prototype was developed and tested with a sample use case which is discussed in the paper