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Towards a Security-Aware Benchmarking Framework for Function-As-A-Service
Towards a Security-Aware Benchmarking Framework for Function-as-a-Service Roland Pellegrini1, Igor Ivkic1 and Markus Tauber1 1University of Applied Sciences Burgenland, Eisenstadt, Austria {1610781022, igor.ivkic, markus.tauber}@fh-burgenland.at Keywords: Cloud Computing, Benchmarking, Cloud Security, Framework, Function-as-a-Service Abstract: In a world, where complexity increases on a daily basis the Function-as-a-Service (FaaS) cloud model seams to take countermeasures. In comparison to other cloud models, the fast evolving FaaS increasingly abstracts the underlying infrastructure and refocuses on the application logic. This trend brings huge benefits in application and performance but comes with difficulties for benchmarking cloud applications. In this position paper, we present an initial investigation of benchmarking FaaS in close to reality production systems. Furthermore, we outline the architectural design including the necessary benchmarking metrics. We also discuss the possibility of using the proposed framework for identifying security vulnerabilities. 1 INTRODUCTION illustrates the technical workflow between the components: Cloud computing, as defined by Mell and Grance (2011), is a model for enabling on-demand network access to a shared pool of configurable resources. Cloud vendors provide these resources in the service models Infrastructure as a Service (IaaS), Platform- as-a-Service (PaaS) and Software-as-a-Service (SaaS). Through virtualization, the IaaS service model provides computing resources (e.g.: servers, storage, network) to consumers so they can deploy Figure 1: FaaS architecture, based on Pientka (2017) and run software. In other words, the consumers do not control the infrastructure, but are able to manage However, Cloud Service Providers (CSP) often the running operating systems and applications. -
Nfaas: Named Function As a Service Michał Król Ioannis Psaras University College London University College London [email protected] [email protected]
NFaaS: Named Function as a Service Michał Król Ioannis Psaras University College London University College London [email protected] [email protected] ABSTRACT functionality to be incorporated. Powerful end-user devices and In the past, the Information-centric networking (ICN) community new applications (e.g., augmented reality [1]) demand minimum has focused on issues mainly pertaining to traditional content de- service delay, while the Internet of Things (IoT) [2] generates huge livery (e.g., routing and forwarding scalability, congestion control amounts of data that flow in the reverse direction from traditional and in-network caching). However, to keep up with future Internet flows (that is, from the edge towards the core for processing). As architectural trends the wider area of future Internet paradigms, a result, computation needs to be brought closer to the edge to there is a pressing need to support edge/fog computing environ- support minimum service latencies and to process huge volumes ments, where cloud functionality is available more proximate to of IoT data. where the data is generated and needs processing. In contrast to cloud computing, edge and fog computing promote With this goal in mind, we propose Named Function as a Service the usage of resources located closer to the network edge to be (NFaaS), a framework that extends the Named Data Networking used by multiple different applications, effectively reducing the architecture to support in-network function execution. In contrast transmission delay and the amount of traffic flowing towards the to existing works, NFaaSbuilds on very lightweight VMs and allows network core. -
Hype Cycle for Storage and Data Protection Technologies, 2020
Hype Cycle for Storage and Data Protection Technologies, 2020 Published 6 July 2020 - ID G00441602 - 78 min read By Analysts Julia Palmer Initiatives:Data Center Infrastructure This Hype Cycle evaluates storage and data protection technologies in terms of their business impact, adoption rate and maturity level to help IT leaders build stable, scalable, efficient and agile storage and data protection platform for digital business initiatives. Analysis What You Need to Know The storage and data protection market is evolving to address new challenges in enterprise IT such as exponential data growth, changing demands for skills, rapid digitalization and globalization of business, requirements to connect and collect everything, and expansion of data privacy and sovereignty laws. Requirements for robust, scalable, simple and performant storage are on the rise. As the data center no longer remains the center of data, IT leaders expect storage to evolve from being delivered by rigid appliances in core data centers to flexible storage platforms capable of enabling hybrid cloud data flow at the edge and in the public cloud. Here, Gartner has assessed 24 of the most relevant storage and data protection technologies that IT leaders must evaluate to address the fast-evolving needs of the enterprise. For more information about how peer I&O leaders view the technologies aligned with this Hype Cycle, see “2020-2022 Emerging Technology Roadmap for Large Enterprises.” The Hype Cycle IT leaders responsible for storage and data protection must cope with the rapidly changing requirements of digital business, exponential data growth, introduction of new workloads, and the desire to leverage public cloud and enable edge capabilities. -
2.5 AWS Lambda
Bachelorarbeit Jules Fehr Serverlose Architektur: Function as a Service mit AWS Lambda am Beispiel einer Web-Anwendung für Fotografen Fakultät Technik und Informatik Faculty of Engineering and Computer Science Department Informatik Department of Computer Science Jules Fehr Serverlose Architektur: Function as a Service mit AWS Lambda am Beispiel einer Web-Anwendung für Fotografen Abschlussarbeit eingereicht im Rahmen der Bachelorprüfung im Studiengang Wirtschaftsinformatik am Department Informatik der Fakultät Technik und Informatik der Hochschule für Angewandte Wissenschaften Hamburg Betreuender Prüfer: Prof. Dr. Ulrike Steffens Zweitgutachter: Prof. Dr. Stefan Sarstedt Abgegeben am 19.07.2018 Jules Fehr Thema der Arbeit Serverlose Architektur: Function as a Service mit AWS Lambda Beispiel einer Web-Anwendung für Fotografen Stichworte FaaS, Serverless, AWS Lambda, Web-Anwendung Kurzzusammenfassung Das Ziel dieser Bachelorarbeit ist die Konzeption und Entwicklung einer Function as a Service Web-Anwendung für Fotografen. In dieser Arbeit werden die Prinzipien von serverloser Architektur behandelt. Es wird eine Referenzarchitektur vorgestellt und es wird eine Anforderungsanalyse für die Anwendung erstellt. Basierend auf der Analyse und den Prinzipien der serverlosen Architektur wird die Umsetzung wichtiger Komponenten erläutert. Jules Fehr Title of the paper Serverless Architecture: Function as a Service with AWS Lambda on the example of a web application for photographers Keywords FaaS, Serverless, AWS Lambda, Web-application Abstract The goal of this bachelor thesis is the conception and development of a Function as a Service web-application for photographers. The principles of serverless architecture will be discussed. A reference architecture will be presented and a requirement analysis will be made. The implementation of important components will be made based on the analysis and the principles of serverless architecture. -
Nanolambda: Implementing Functions As a Service at All Resource Scales for the Internet of Things
NanoLambda: Implementing Functions as a Service at All Resource Scales for the Internet of Things. Gareth George, Fatih Bakir, Rich Wolski, and Chandra Krintz Computer Science Department Univ. of California, Santa Barbara Abstract—Internet of Things (IoT) devices are becoming in- decompose their applications into multiple functions, each re- creasingly prevalent in our environment, yet the process of sponsible for some short-lived piece of processing. A function programming these devices and processing the data they produce is typically a small, single-entry code package (50 megabytes remains difficult. Typically, data is processed on device, involving arduous work in low level languages, or data is moved to the or less) written in a high level language (e.g. Python, node.js, cloud, where abundant resources are available for Functions or Java). Thanks to their small size and self-contained design, as a Service (FaaS) or other handlers. FaaS is an emerging these functions are easily invoked and scaled automatically category of flexible computing services, where developers deploy by the FaaS platform in response to incoming events (data self-contained functions to be run in portable and secure con- arrival, messages, web requests, storage updates, etc.). Many tainerized environments; however, at the moment, these functions are limited to running in the cloud or in some cases at the “edge” functions, potentially belonging to different tenants, execute on of the network using resource rich, Linux-based systems. a single server, using Linux containers to provide secure iso- In this paper, we present NanoLambda, a portable platform lation and a consistent execution environment. -
Serverless Computing in Financial Services High Performance Computing—With More Speed, Accuracy and Flexibility Authors
Serverless computing in financial services High performance computing—with more speed, accuracy and flexibility Authors Michael Behrendt is a Distinguished Engineer in Neil Cowit is the Worldwide Cloud Offering the IBM Cloud development organization. He is Manager for High Performance Computing at responsible for IBM’s technical strategy around IBM. HPC has been a significant part of Neil’s serverless & Function-as-a-Service. 20-plus-year career within the financial services technology sector. He has held leadership In that context, he’s also the chief architect for and individual contributor roles in Product the IBM serverless offering, IBM Cloud Functions. Management, Development, Sales and Marketing. Before that, he was the chief architect of the core platform of IBM Bluemix and was one of the initial founding members incubating it. Michael has been working on cloud computing for more than 13 years and has 35 patents. He is located in the IBM Research & Development Laboratory in Boeblingen, Germany. | 2 | Contents Authors 02 Introduction 04 What issues can serverless computing help address? 06 Technical perspective 07 IBM Cloud Functions: Implementing serverless computing 08 Benefits of IBM Cloud Functions 08 Conclusion 09 Glossary 10 | 3 | Introduction If Mrs. Wallis Simpson were alive today and Wouldn’t it be terrific if we only had to solve static involved in financial services, she may very well or deterministic models as opposed to stochastic have modified her famous quote from “You can or probabilistic financial models? Imagine being never be too rich or too thin.” to “You can never able to cover all the possible contingencies in have too much compute capacity.” proportion to their likelihood. -
Performance and Progress Report
Performance and Progress Report NOAA Grant No: NA15NOS4000200 Project Title: Joint Hydrographic Center Report Period: 01/01/2016 – 12/31/2016 Lead Principal Investigator: Larry A. Mayer Principal Investigators Brian Calder John Hughes Clarke James Gardner David Mosher Colin Ware Thomas Weber Co-PIs Thomas Butkiewicz Jenn Dijkstra Semme Dijkstra Paul Johnson Thomas Lippmann Giuseppe Masetti Shachak Pe’eri Yuri Rzhanov Val Schmidt Briana Sullivan Larry Ward CONTENTS INTRODUCTION ........................................................................................................................................................ 3 INFRASTRUCTURE .................................................................................................................................................. 4 PERSONNEL .......................................................................................................................................................................... 4 Research Scientists and Staff .......................................................................................................................................... 9 NOAA Employees ......................................................................................................................................................... 14 Other Affiliated Faculty ................................................................................................................................................ 16 Visiting Scholars .......................................................................................................................................................... -
A Brief History of Cloud Application Architectures
applied sciences Review A Brief History of Cloud Application Architectures Nane Kratzke ID Lübeck University of Applied Sciences, Department of Electrical Engineering and Computer Science, 23562 Lübeck, Germany; [email protected] Received: 14 July 2018; Accepted: 27 July 2018; Published: 14 August 2018 Featured Application: This paper features system and software engineering use cases for large-scale (business) Cloud-native applications (e.g., Netflix, Twitter, Uber, Google Search). Such Cloud-native applications (CNA) provide web-scalability and independent deployability of their components and enable exponential user growth. Furthermore, migration and architecture transformation use cases of existing tiered and on-premise (business) applications are additionally of interest. Thus, questions of how existing and not cloud-ready applications are migratable into cloud environments are covered as well. Abstract: This paper presents a review of cloud application architectures and its evolution. It reports observations being made during a research project that tackled the problem to transfer cloud applications between different cloud infrastructures. As a side effect, we learned a lot about commonalities and differences from plenty of different cloud applications which might be of value for cloud software engineers and architects. Throughout the research project, we analyzed industrial cloud standards, performed systematic mapping studies of cloud-native application-related research papers, did action research activities in cloud engineering projects, modeled a cloud application reference model, and performed software and domain-specific language engineering activities. Two primary (and sometimes overlooked) trends can be identified. First, cloud computing and its related application architecture evolution can be seen as a steady process to optimize resource utilization in cloud computing. -
Architectural Implications of Function-As-A-Service Computing
Architectural Implications of Function-as-a-Service Computing Mohammad Shahrad Jonathan Balkind David Wentzlaff Princeton University Princeton University Princeton University Princeton, USA Princeton, USA Princeton, USA [email protected] [email protected] [email protected] ABSTRACT Network Serverless computing is a rapidly growing cloud application model, popularized by Amazon’s Lambda platform. Serverless cloud ser- Scheduling vices provide fine-grained provisioning of resources, which scale Platform (priorwork) automatically with user demand. Function-as-a-Service (FaaS) appli- Queueing Management cations follow this serverless model, with the developer providing 35% decrease in IPC Interference their application as a set of functions which are executed in response due to interference 6x variation due to to a user- or system-generated event. Functions are designed to Memory BW invocation pattern 20x MPKI for be short-lived and execute inside containers or virtual machines, Branch MPKI >10x exec time short functions introducing a range of system-level overheads. This paper studies for short functions Cold Start Server the architectural implications of this emerging paradigm. Using (500ms cold start) Up to 20x (thispaper) Container the commercial-grade Apache OpenWhisk FaaS platform on real slowdown servers, this work investigates and identifies the architectural im- Native plications of FaaS serverless computing. The workloads, along with Execution Figure 1: We characterize the server-level overheads of the way that FaaS inherently interleaves short functions from many Function-as-a-Service applications, compared to native exe- tenants frustrates many of the locality-preserving architectural cution. This contrasts with prior work [2–5] which focused structures common in modern processors. -
Persistent Helper Functions in a Serverless Offering
Journal of Software Engineering and Applications, 2020, 13, 278-287 https://www.scirp.org/journal/jsea ISSN Online: 1945-3124 ISSN Print: 1945-3116 Result-as-a-Service (RaaS): Persistent Helper Functions in a Serverless Offering Arshdeep Bahga, Vijay K. Madisetti, Joel R. Corporan Georgia Institute of Technology, Atlanta, USA How to cite this paper: Bahga, A., Madi- Abstract setti, V.K. and Corporan, J.R. (2020) Re- sult-as-a-Service (RaaS): Persistent Helper Serverless Computing or Functions-as-a-Service (FaaS) is an execution model Functions in a Serverless Offering. Journal for cloud computing environments where the cloud provider executes a piece of Software Engineering and Applications, of code (a function) by dynamically allocating resources. When a function 13, 278-287. https://doi.org/10.4236/jsea.2020.1310018 has not been executed for a long time or is being executed for the first time, a new container has to be created, and the execution environment has to be in- Received: September 21, 2020 itialized resulting in a cold start. Cold start can result in a higher latency. We Accepted: October 24, 2020 propose a new computing and execution model for cloud environments Published: October 27, 2020 called Result-as-a-Service (RaaS), which aims to reduce the computational Copyright © 2020 by author(s) and cost and overhead while achieving high availability. In between successive Scientific Research Publishing Inc. calls to a function, a persistent function can help in successive calls by pre- This work is licensed under the Creative computing the functions for different possible arguments and then distribut- Commons Attribution International License (CC BY 4.0). -
A Systematic Mapping Study on Engineering Function-As-A-Service Platforms and Tools
Institute of Architecture of Application Systems A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools Vladimir Yussupov, Uwe Breitenbücher, Frank Leymann, Michael Wurster Institute of Architecture of Application Systems, University of Stuttgart, Germany, {yussupov, breitenbuecher, leymann, wurster}@iaas.uni-stuttgart.de : @inproceedings{Yussupov2019_SystematicMappingStudyFaaS, author = {Vladimir Yussupov and Uwe Breitenb{\"u}cher and Frank Leymann and Michael Wurster}, title = {{A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools}}, booktitle = {Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2019)}, publisher = {ACM}, year = 2019, month = dec, pages = {229--240}, doi = {10.1145/3344341.3368803} } © Yussupov et al. 2019. This is an Open Access publication licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools Vladimir Yussupov Uwe Breitenbücher Institute of Architecture of Application Systems Institute of Architecture of Application Systems University of Stuttgart, Germany University of Stuttgart, Germany [email protected] [email protected] Frank Leymann Michael Wurster Institute of Architecture of Application Systems Institute of Architecture of Application Systems University of Stuttgart, Germany University of Stuttgart, Germany [email protected] [email protected] ABSTRACT which creates a wrong impression that servers are absent. A recent Function-as-a-Service (FaaS) is a novel cloud service model allowing newcomer in the line of as-a-service offerings called Function-as- to develop fine-grained, provider-managed cloud applications. -
Rethinking Scalable Service Architectures for the Internet of Things
Devices-as-Services: Rethinking Scalable Service Architectures for the Internet of Things Fatih Bakir, Rich Wolski, Chandra Krintz Gowri Sankar Ramachandran Univ. of California, Santa Barbara Univ. of Southern California Abstract vices at the edge that augment device capabilities and enable We investigate a new distributed services model and architec- scale. In this paper, we outline this approach to implementing ture for Internet of Things (IoT) applications. In particular, Devices-as-Services and describe some of the capabilities of we observe that devices at the edge of the network, although an early prototype. resource constrained, are increasingly capable – performing Our work is motivated by the following observations. • IoT applications can and will likely be structured as collec- actions (e.g. data analytics, decision support, actuation, con- tions of services that require functionality from a device trol, etc.) in addition to event telemetry. Thus, such devices tier, an edge tier, and a cloud tier are better modeled as servers, which applications in the cloud • in-network data processing can significantly reduce re- compose for their functionality. We investigate the implica- sponse time and energy consumption [31], tions of this “flipped” IoT client-server model, for server dis- • edge isolation precludes the need for dedicated commu- covery, authentication, and resource use. We find that by com- nication channels between application and devices, and bining capability-based security with an edge-aware registry, facilitates privacy protection for both data and devices, this model can achieve fast response and energy efficiency. • actuation in device tier will require some form of request- 1 Introduction response protocol where the device fields the request, • the heterogeneity of devices militates for a single program- As the Internet of Things (IoT) grows in size and ubiquity, it ming paradigm and distributed interaction model, and is becoming critical that we perform data-driven operations • multi-function devices can and will be able to perform their (i.e.