BPMN4sML: A BPMN Extension for Serverless Machine Learning. Technology Independent and Interoperable Modeling of Machine Learning Workflows and their Serverless Deployment Orchestration

Machine learning (ML) continues to permeate all layers of academia, industry and society. Despite its successes, mental frameworks to capture and represent machine learning workflows in a consistent and coherent manner are lacking. For instance, the de facto process modeling standard, Business Process Model and Notation (BPMN), managed by the Object Management Group, is widely accepted and applied. However, it is short of specific support to represent machine learning workflows. Further, the number of heterogeneous tools for deployment of machine learning solutions can easily overwhelm practitioners. Research is needed to align the process from modeling to deploying ML workflows. We analyze requirements for standard based conceptual modeling for machine learning workflows and their serverless deployment. Confronting the shortcomings with respect to consistent and coherent modeling of ML workflows in a technology independent and interoperable manner, we extend BPMN's Meta-Object Facility (MOF) metamodel and the corresponding notation and introduce BPMN4sML (BPMN for serverless machine learning). Our extension BPMN4sML follows the same outline referenced by the Object Management Group (OMG) for BPMN. We further address the heterogeneity in deployment by proposing a conceptual mapping to convert BPMN4sML models to corresponding deployment models using TOSCA. BPMN4sML allows technology-independent and interoperable modeling of machine learning workflows of various granularity and complexity across the entire machine learning lifecycle. It aids in arriving at a shared and standardized language to communicate ML solutions. Moreover, it takes the first steps toward enabling conversion of ML workflow model diagrams to corresponding deployment models for serverless deployment via TOSCA.Comment: 105 pages 3 tables 33 figure

A pattern language for modeling the provisioning of applications

In cloud computing, there are various technologies that automate the provisioning of cloud applications by employing different domain-specific languages and modeling techniques. These domain-specific languages and modeling techniques encompass different extents of functionality that the user have to know before the decision for or against a technology can be made. This master thesis contributes by introducing the Application Provisioning Modeling Pattern Language that enables the user to understand the underlying principles of the considered technologies, choose one technology according the requirements, and model the provisioning of the desired cloud application. The introduced Application Provisioning Modeling Pattern Language fosters the understanding of cloud application provisioning and works out the differences of the considered technologies as well as shows how the concepts can be combined. The Application Provisioning Modeling Pattern Language is validated by documenting systematically the occurrences of the concepts, their requirements and implications and by providing a statistical basis that quantitatively proves the repeatedly occurrence of the found principles

Integrating cloud service deployment automation with software-defined environments

The last decade has seen a deluge of technology and services related to cloud-computing. The idea of traditional IT infrastructure has been usurped by a rush to move all services to a cloud infrastructure and to implement them in a cloud-native way. A cloud infrastructure is unlike a conventional infrastructure in that, it is implemented as a Software-Defined Environment (SDE) which abstracts and virtualises the underlying physical resources. It manages physical resources and provides virtual resources that process, manage, store, create networks and provision services. But while the concept of a virtual data center as played out by an SDE seems ideal, the issues it brings in implementation are quite a few. For one, deployment and management of services on such a large scale is difficult. It is also subject to human efficiency and error. So, new levels of tracking and automation have to be explored in parallel to support and sustain the cloud-computing phenomenon. Several configuration management and orchestration tools have been developed over years, to fulfill the need of automated deployment and management. TOSCA is one of such that provides a specification which empowers this goal by using a metamodel. It defines implementation artifacts that encapsulate functionality of external services to use them during deployment. An open-source container called OpenTOSCA, is under development at the University of Stuttgart. This framework can process the TOSCA specification. In this thesis, OpenStack has been employed as the cloud infrastructure provider. To achieve our goal, an implementation artifact for the relevant OpenStack components has to be developed in concept and implementation. In order to create useful implementation artifacts an appropriate level of abstraction has to be introduced between the low-level OpenStack API and the services that the implementation artifact provides. Accordingly, a TOSCA artifact is designed and implemented as a web service and packaged in a container file, called CSAR. This file, when processed by the OpenTOSCA container, causes the automated provisioning of a server on OpenStack. To evaluate the nature of the implementation artifact, the web service is hosted on the local machine and tests are performed to check for correct implementation of service endpoints. The results of these invocations are later presented

Modeling context-aware systems using TOSCA

Cloud Computing is widely accepted as a provider of virtual resources over the Internet, it is due to its economical and technical benefits, such as on-demand self-service, resource pooling and rapid elasticity capabilities. To exploit these properties reliably, it is needed to automate their internal processes for application provisioning, configuration and management. One of the standards that has been developed in the last years with this aim is the Topology and Orchestration Specification for Cloud Applications (TOSCA) by OASIS. TOSCA is a standard which enables application developers to describe applications and their management as models that incorporate components and their relations among each other. Due to the emerging of new fields such as the Internet of Things, Industry 4.0 and the upcoming Fog Computing paradigm, which depend more and more on dynamically changing situations and therefore reconfiguration of applications in such a scenario, a systematic modelling approach which handles situational dependencies directly in the models of these applications is needed. The goal of the thesis is to identify suitable modeling concepts from the field of context- aware systems and apply one of these on the TOSCA language to incorporate the inherent nature of change of future applications in the field of Cloud/Fog Computing, Internet of Things and Industry 4.0

Dynamic cloud provisioning based on TOSCA

Cloud computing, today, is a ubiquitous paradigm. Its features such as availability of a practically infinite pool of computing resources, on demand, by using a pay-per-use model has resulted in its adoption by the industry for the realization of modern, sophisticated, and highly scalable IT applications. Such applications are often comprised of various components and services offered by different cloud service providers. This, in turn, raises two significant challenges- (i) automated provisioning and management, and (ii) interoperability and portability of the applications in a multi-cloud environment. As a result, the Topology and Orchestration Specification for Cloud Applications (TOSCA) standard was introduced by OASIS. This standard provides a metamodel to describe the topology of complex applications along with all the components, artifacts, and services in a single template that allows deploying the application in an interoperable and portable manner. In this Master thesis, we propose a concept that generates small and reusable TOSCA provisioning plans which can be orchestrated to deploy the overall application as opposed to using a monolithic provisioning plan. This goal is achieved in three steps - (i) splitting the application topology into a set of smaller sub-topologies, (ii) generating smaller plans called partial plans for each sub-topology, (iii) and finally orchestrating the partial plans to provision an instance of the application. Additionally, this concept enables the reuse of these plans for tasks such as scaling out individual components of the application. Finally, the feasibility of the proposed concept is demonstrated by a prototypical implementation developed using the OpenTOSCA framework

Concepts for integrating DevOps methodologies with model-driven cloud management based on TOSCA

The paradigm of Cloud computing introduces new approaches to manage IT services and applications. Those approaches overcome traditional IT infrastructure and service management. One of the main goals of Cloud computing is to automate the whole management of IT services in order to reduce costs and to make the execution of management tasks less error-prone. To make this happen, Cloud providers offer proprietary tools to create and manage services in the Cloud. However, when services get more complex it is hard to manage them because those tools aim to be simple and thus provide limited functionality only. In addition, a particular service that was built based on a certain Cloud offering is bound to this offering including all its management aspects. Consequently, a service cannot be easily moved from one Cloud provider's infrastructure to another one's infrastructure. Today, tools and frameworks implementing so called "DevOps methodologies" can be used to realize management of Cloud services without binding a service to a particular Cloud provider. Nevertheless, complex services are still hard to manage by following those methodologies. To make such services manageable and enable automation of management tasks, a holistic service model is needed. Thus, model-driven Cloud management is an emerging paradigm to realize a holistic management approach for services in the Cloud. Because the DevOps approach and the model-driven approach are originating in different backgrounds, model-driven Cloud management does not cover some aspects of DevOps methodologies that are key for Cloud services. This thesis is focused on integrating DevOps methodologies with model-driven Cloud management. The goal is to combine the strengths of both approaches in order to minimize the shortcomings of the individual approaches

Development of TOSCA service templates for provisioning portable IT services

Provisioning cloud computing solutions is a tedious and long process, especially when configuring many components and not only offering the application but also the infrastructure. Today, an administrator has to upload, install and configure all the components of a software solution manually, which not only takes time and is prone to errors but also increases the onboarding costs at the cloud provider. Decreasing deployment times by the use of an automated system is favored. TOSCA provides a specification which allows the deployment and management of cloud services by providing a meta-model. With that it is possible to mitigate all problems in theory. OpenTOSCA is a framework called container, which can interpret the TOSCA specification and is used in this work to deploy an Enterprise Content Management stack on a cloud environment, testing the boundaries of its capabilities. After designing deployment models by the means of a domain specific modeling approach, an implementation is realized and compiled into a deployment file. This file is also called a container file and is processed by OpenTOSCA to initiate the deployment on the cloud environment, including the necessary middleware. The goal of this diploma thesis is to develop a TOSCA Service Template, that provides a topology model and automates the deployment of ECM core components. TOSCA Node Types for the middleware and application components have to be defined. To further help modeling the topology, a domain specific model (DSM) will be introduced by generically defining all components and their operations. That generic model will be used to realize the actual ECM stack components. The ECM stack is then deployed via OpenTOSCA and the execution is reviewed

A TOSCA-Based Conceptual Architecture to Support the Federation of Heterogeneous MSaaS Infrastructures †

Modeling and simulation (M&S) techniques are effectively used in many application domains to support various operational tasks ranging from system analyses to innovative training activities. Any (M&S) effort might strongly benefit from the adoption of service orientation and cloud computing to ease the development and provision of M&S applications. Such an emerging paradigm is commonly referred to as M&S-as-a-Service (MSaaS). The need for orchestrating M&S services provided by different partners in a heterogeneous cloud infrastructure introduces new challenges. In this respect, the adoption of an effective architectural approach might significantly help the design and development of MSaaS infrastructure implementations that cooperate in a federated environment. In this context, this work introduces a MSaaS reference architecture (RA) that aims to investigate innovative approaches to ease the building of inter-cloud MSaaS applications. Moreover, this work presents ArTIC-MS, a conceptual architecture that refines the proposed RA for introducing the TOSCA (topology and orchestration specification for cloud applications) standard. ArTIC-MS’s main objective is to enable effective portability and interoperability among M&S services provided by different partners in heterogeneous federations of cloud-based MSaaS infrastructure. To show the validity of the proposed architectural approach, the results of concrete experimentation are provided