Application period is about to start!

Google Summer of Code (GSoC) is a program designed to bring new, excited contributors into open source communities, with the hope that they will continue to contribute to open source communities long after their GSoC program ends. Google Summer of Code (GSoC) is a program designed to bring new, excited contributors into open source communities, with the hope that they will continue to contribute to open source communities long after their GSoC program ends.

Partners of the PHYSICS project will be mentoring through ELLAK, the greek free and open source community, with a focus on implementing workflow, parallelization and cloud design patterns in Node-RED for Function as Service coordination:

You may follow the PHYSICS project activities on Twitter and LinkedIn.

The post Press Release: Google Summer of Code 2022 – PHYSICS representatives will be mentoring on FaaS appeared first on PHYSICS.

5th Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2022) at ICPE 2022

9. April, 2022 – Virtual Conference

Overview

The HotCloudPerf workshop proposes a meeting venue for academics and practitioners, from experts to trainees, in the field of cloud computing performance. The new understanding of cloud computing covers the full computational continuum from data centers to edge resources to IoT sensors and devices. The workshop aims to engage this community and to lead to the development of new methodological aspects for gaining a deeper understanding not only of cloud performance, but also of cloud operation and behavior, through diverse quantitative evaluation tools, including benchmarks, metrics, and workload generators. The workshop focuses on novel cloud properties such as elasticity, performance isolation, dependability, and other non-functional system properties, in addition to classical performance-related metrics such as response time, throughput, scalability, and efficiency.

You may follow the PHYSICS project activities on Twitter and LinkedIn.

The post Acceptance of a new paper: Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows appeared first on PHYSICS.

Modern cloud computing advances have been pressing application modernization in the last 15 years, stressing the need for application redesign towards the use of more distributed and ephemeral resources. From the initial IaaS and PaaS approaches, to microservices and now to the serverless model (and especially the Function as a Service approach), new challenges arise constantly for application developers. This paper presents a design and development environment that aims to ease application evolution and migration to the new FaaS model, based on the widely used Node-RED open source tool. The goal of the environment is to enable a more user friendly and abstract function and workflow creation for complex FaaS applications. To this end, it bypasses workflow description and function reuse limitations of the current FaaS platforms, by providing an extendable, pattern-enriched palette of ready-made, reusable functionality that can be combined in arbitrary ways. The environment embeds seamless DevOps processes for generating the deployable artefacts (i.e. functions and images) of the FaaS platform (Openwhisk). Annotation mechanisms are also available for the developer to dictate diverse execution options or management guidelines towards the deployment and operation stacks. The evaluation is based on case studies of indicative scenarios, including creating, registering and executing functions and flows based on the Node-RED runtime, embedding of existing legacy code in a FaaS environment, parallelizing a workload, collecting data at the edge and creating function orchestrators to accompany the application. For the latter, a detailed argumentation is provided as to why this process should not be constrained by the “double billing” principle of FaaS.

Authors

• George Kousiouris, 
• Szymon Ambroziak, 
• Domenico Costantino, 
• Stylianos Tsarsitalidis, 
• Evangelos Boutas, 
• Alessandro Mamelli, 
• Teta Stamati

The post Combining Node-RED and Openwhisk for Pattern-based Development and Execution of Complex FaaS Workflows appeared first on PHYSICS.

Most current implementations are facing the following constraints that limit their potential:

• Lack of Proper Resources Catalog Management: Not all cloud providers would provide the same resources or services in their catalog. Therefore it could happen that the platform would be in need for some specific resources that are not present in the given provider. 
• Deployment Heterogeneity: Most of the cloud providers provide the same basic resources in their catalog. However, not all of them are provisioned the same way. This means that all providers expose a different interface on how resources are created, administered and operated.
• Operations Diversity: Given this deployment diversity, there would be different procedures on how to execute the required operations to deploy and maintain the platform. 
• Limited Orchestration Intelligence : On top of the previous points, there is a need of orchestration that makes the platform work automatically. Orchestration enables operations execution with the minimum human interaction or even no interaction at all. Ideally, a FaaS cloud platform must automatically detect points of failure either proactive or reactive way and apply the required operation action.

To alleviate these limitations, PHYSICS proposes a novel approach that addresses the need of simplifying the heterogeneity complexity by simply adding an abstraction layer for FaaS cloud computing.

This abstraction layer is composed of two core components:

• Platform operator: This element administrers the platform and decides what needs to be done and how. This element contains the logic to create the new operations given the current status of the platform i.e. it is an active element.
• Platform runtime: The element is aware of the current state of the platform and provides back to the operator the necessary information required for the operations to proceed. It is responsible for the administrative and maintenance operations to keep the platform healthy and alive. This is a passive element since it does not have any logic to make proactive operations. Its sole purpose is to persist the state of the platform as instructed by the operator. 

By including those elements all platform operations will be interfaced by the operator who will include the abstraction logic of the operations. Therefore, the operator will get a declarative input on what is needed. Accordingly, the operator will automatically execute the necessary tasks in the best possible way to get to the new state. Once the Operator has executed the necessary operations, the platform runtime will try to keep the state that was ordered by the operator and will execute any fixing actions in case any error takes place due to the new change.

In this way, the solution developed by PHYSICS will simplify platform operations in a multi-cloud environment with multi providers, while offering increased scalability. All operations will be performed based on the specific needs of each application at the right time, without a prior knowledge of the operator conditions.

To keep up with our implementation updates, follow PHYSICS on Twitter: https://twitter.com/H2020Physics

The post Abstracting Heterogeneity Complexity for Platform Operations: The PHYSICS approach appeared first on PHYSICS.

The main goal of PHYSICS is to unlock the potential of the Function-as-a-Service (FaaS) paradigm for Cloud Service Providers (CSP) and for Application Developers. Specifically, it will enable application developers to design, implement and deploy advanced FaaS applications in the scope of advanced cloud application design environments, leveraging proven design patterns and existing libraries of cloud/FaaS components. Furthermore, PHYSICS will offer a novel Global Continuum Layer that will undertake to deploy functions in optimal ways that will optimize multiple application objectives at the same time, including for example performance, latency, and cost. The platform will offer a graphical view of the application flow, allowing through simple drag and drop commands to create pipelines of functions according to the FaaS model.

PHYSICS will validate the benefits of its Global Continuum Layer and tools, in the scope of user-driven application scenarios in three important sectors, namely healthcare, agriculture and industry.

Specifically:

• PHYSICS in Manufacturing: The PHYSICS industrial use cases will focus on manufacturing and production. It will be deployed in a smart plant testbed to demonstrate how FaaS model can be used to optimize production pipelines in environments where multiple edge devices are used. Specifically, FaaS enabled production pipelines based on heterogeneous devices that are currently available in the plant will be developed. The devices of the pilot plant include edge devices, several HPC (High-Performance Computing) Clusters or single HPCs, special GPU (Graphical Processing Units) enabled processing nodes, industrial PCs, PLCs (Programmable Logic Controllers), Single-board computers, Raspberry Pis, as well as devices that simulate Quantum-like processes. PHYSICS will facilitate the combination and use of services from these diverse setups in a seamless and integrated manner. Moreover, it will ensure that relevant FaaS functions for accessing the capabilities of these devices are assigned and used in optimally.
  
• PHYSICS in Healthcare: The PHYSICS healthcare use case will focus on the deployment of functions (FaaS) across multiple IoT edge devices and smartphones that provide Real-World Data and enable the extraction of novel biomarkers about certain diseases. The data received are divided into two main categories: measured (objective) and reported (subjective). Through different devices it will be possible, exploiting the FaaS paradigm and Machine Learning technologies, to make predictions on possible problems based also on clustering activities between patients with similar lifestyles. PHYSICS FaaS functions will be optimized to address diverse needs about data access interfaces, data harmonization, and transformation, as well as different privacy and data protection requirements. 
  
• PHYSICS in Agriculture: The PHYSICS Agriculture Use Case will showcase how the FaaS paradigm can facilitate the implementation of many thousands of daily climatic simulations towards improving crop management and yield estimation. The scalable execution of thousands of simulations about each greenhouse is a key to manage meteorological uncertainty and correcting its trajectory with existing historical data. Specifically, FaaS will facilitate the optimal distribution and deployment of functions across different cloud environments and the local sites, in ways that ease (re)configuration of simulations towards an optimal distribution of computations across edge nodes and the cloud. Likewise, the use case will showcase a tangible performance improvement in the execution of simulation, including the possibility to execute simulations in near real-time.

Follow GFT on Twitter and on Linkedin to see the latest updates!

The post The main goals and Use cases of the PHYSICS Project appeared first on PHYSICS.