arXiv subjects

Cristina L. Abad

Publications and source records attributed to Cristina L. Abad.

8 recordsLinked to original sources

arXiv2025

OpenLambdaVerse: A Dataset and Analysis of Open-Source Serverless Applications

Function-as-a-Service (FaaS) is at the core of serverless computing, enabling developers to easily deploy applications without managing computing resources. With an Infrastructure-as-Code (IaC) approach, frameworks like the Serverless Framework use YAML configurations to define and deploy APIs, tasks, workflows, and event-driven applications on cloud providers, promoting zero-friction development. As with any rapidly evolving ecosystem, there is a need for updated insights into how these tools are used in real-world projects. Building on the methodology established by the Wonderless dataset for serverless computing (and applying multiple new filtering steps), OpenLambdaVerse addresses this gap by creating a dataset of current GitHub repositories that use the Serverless Framework in applications that contain one or more AWS Lambda functions. We then analyze and characterize this dataset to get an understanding of the state-of-the-art in serverless architectures based on this stack. Through this analysis we gain important insights on the size and complexity of current applications, which languages and runtimes they employ, how are the functions triggered, the maturity of the projects, and their security practices (or lack of). OpenLambdaVerse thus offers a valuable, up-to-date resource for both practitioners and researchers that seek to better understand evolving serverless workloads.

cs.SE↗

arXiv2025

An Analysis of HPC and Edge Architectures in the Cloud

We analyze a recently published dataset of 396 real-world cloud architectures deployed on AWS, from companies belonging to a wide range of industries. From this dataset, we identify those architectures that contain HPC or edge components and characterize their designs. Specifically, we investigate the prevalence and interplay of AWS services within these architectures, examine the types of storage systems employed, assess architectural complexity and the use of machine learning services, discuss the implications of our findings and how representative these results are of HPC and edge architectures in the cloud. This characterization provides valuable insights into current industry practices and trends in building robust and scalable HPC and edge solutions in the cloud continuum, and can be valuable for those seeking to better understand how these architectures are being built and to guide new research.

cs.DC↗

arXiv2023

Servo: Increasing the Scalability of Modifiable Virtual Environments Using Serverless Computing -- Extended Technical Report

Online games with modifiable virtual environments (MVEs) have become highly popular over the past decade. Among them, Minecraft -- supporting hundreds of millions of users -- is the best-selling game of all time, and is increasingly offered as a service. Although Minecraft is architected as a distributed system, in production it achieves this scale by partitioning small groups of players over isolated game instances. From the approaches that can help other kinds of virtual worlds scale, none is designed to scale MVEs, which pose a unique challenge -- a mix between the count and complexity of active in-game constructs, player-created in-game programs, and strict quality of service. Serverless computing emerged recently and focuses, among others, on service scalability. Thus, addressing this challenge, in this work we explore using serverless computing to improve MVE scalability. To this end, we design, prototype, and evaluate experimentally Servo, a serverless backend architecture for MVEs. We implement Servo as a prototype and evaluate it using real-world experiments on two commercial serverless platforms, of Amazon Web Services (AWS) and Microsoft Azure. Results offer strong support that our serverless MVE can significantly increase the number of supported players per instance without performance degradation, in our key experiment by 40 to 140 players per instance, which is a significant improvement over state-of-the-art commercial and open-source alternatives. We release Servo as open-source, on Github: https://github.com/atlarge-research/opencraft

cs.DC↗

arXiv2021

Sizeless: Predicting the optimal size of serverless functions

Serverless functions are a cloud computing paradigm where the provider takes care of resource management tasks such as resource provisioning, deployment, and auto-scaling. The only resource management task that developers are still in charge of is selecting how much resources are allocated to each worker instance. However, selecting the optimal size of serverless functions is quite challenging, so developers often neglect it despite its significant cost and performance benefits. Existing approaches aiming to automate serverless functions resource sizing require dedicated performance tests, which are time-consuming to implement and maintain. In this paper, we introduce an approach to predict the optimal resource size of a serverless function using monitoring data from a single resource size. As our approach does not require dedicated performance tests, it enables cloud providers to implement resource sizing on a platform level and automate the last resource management task associated with serverless functions. We evaluate our approach on three different serverless applications, where it selects the optimal memory size for 71.7% of the serverless functions and the second-best memory size for 22.3% of the serverless functions, which results in an average speedup of 43.6% while simultaneously decreasing average costs by 10.2%.

cs.DC↗

arXiv2021

An Analysis of Distributed Systems Syllabi With a Focus on Performance-Related Topics

We analyze a dataset of 51 current (2019-2020) Distributed Systems syllabi from top Computer Science programs, focusing on finding the prevalence and context in which topics related to performance are being taught in these courses. We also study the scale of the infrastructure mentioned in DS courses, from small client-server systems to cloud-scale, peer-to-peer, global-scale systems. We make eight main findings, covering goals such as performance, and scalability and its variant elasticity; activities such as performance benchmarking and monitoring; eight selected performance-enhancing techniques (replication, caching, sharding, load balancing, scheduling, streaming, migrating, and offloading); and control issues such as trade-offs that include performance and performance variability.

cs.CY↗

arXiv2021

A Review of Serverless Use Cases and their Characteristics

The serverless computing paradigm promises many desirable properties for cloud applications - low-cost, fine-grained deployment, and management-free operation. Consequently, the paradigm has underwent rapid growth: there currently exist tens of serverless platforms and all global cloud providers host serverless operations. To help tune existing platforms, guide the design of new serverless approaches, and overall contribute to understanding this paradigm, in this work we present a long-term, comprehensive effort to identify, collect, and characterize 89 serverless use cases. We survey use cases, sourced from white and grey literature, and from consultations with experts in areas such as scientific computing. We study each use case using 24 characteristics, including general aspects, but also workload, application, and requirements. When the use cases employ workflows, we further analyze their characteristics. Overall, we hope our study will be useful for both academia and industry, and encourage the community to further share and communicate their use cases. This article appears also as a SPEC Technical Report: https://research.spec.org/fileadmin/user_upload/documents/rg_cloud/endorsed_publications/SPEC_RG_2020_Serverless_Usecases.pdf The article may be submitted for peer-reviewed publication.

cs.SE↗

arXiv2020

Have We Reached Consensus? An Analysis of Distributed Systems Syllabi

Correctly applying distributed systems concepts is important for software that seeks to be scalable, reliable and fast. For this reason, Distributed Systems is a course included in many Computer Science programs. To both describe current trends in teaching distributed systems and as a reference for educators that seek to improve the quality of their syllabi, we present a review of 51 syllabi of distributed systems courses from top Computer Science programs around the world. We manually curated the syllabi and extracted data that allowed us to identify approaches used in teaching this subject, including choice of topics, book, and paper reading list. We present our results and a discussion on whether what is being taught matches the guidelines of two important curriculum initiatives.

cs.CY↗

arXiv2020

Serverless Applications: Why, When, and How?

Serverless computing shows good promise for efficiency and ease-of-use. Yet, there are only a few, scattered and sometimes conflicting reports on questions such as 'Why do so many companies adopt serverless?', 'When are serverless applications well suited?', and 'How are serverless applications currently implemented?' To address these questions, we analyze 89 serverless applications from open-source projects, industrial sources, academic literature, and scientific computing - the most extensive study to date.

cs.SE↗