arXiv subjects

Nnamdi Ekwe-Ekwe

Publications and source records attributed to Nnamdi Ekwe-Ekwe.

3 recordsLinked to original sources

arXiv2026

Priceless: An examination of Serverless Functions-as-a-Service (FaaS) pricing models

Serverless Functions-as-a-Service providers have grown in their offering since inception a decade ago, with a myriad of new functionalities offered to end-users. These new features have also brought new, varied and at times complex pricing models that differ between providers. In this paper, we present Priceless, a detailed examination of the current state of the art of FaaS features, and their pricing models. We then perform a comparative price analysis of running example workloads across AWS Lambda, Microsoft Azure Functions and Google Cloud Functions. Our work finds significant cost differences both cross-provider, but also, cross-region within the provider. We find that AWS is the cheapest overall to run functions on, with Microsoft Azure being the most expensive for equivalent workloads.

cs.DC↗

arXiv2024

The State of FaaS: An analysis of public Functions-as-a-Service providers

Serverless computing is a growing and maturing field that is the focus of much research, industry interest and adoption. Previous works exploring Functions-as-a-Service providers have focused primarily on the most well known providers AWS Lambda, Google Cloud Functions and Microsoft Azure Functions without exploring other providers in similar detail. In this work, we conduct the first detailed review of ten currently publicly available FaaS platforms exploring everything from their history, to their features and pricing to where they sit within the overall public FaaS landscape, before making a number of observations as to the state of the FaaS.

cs.DC↗

arXiv2018

Location, Location, Location: Exploring Amazon EC2 Spot Instance Pricing Across Geographical Regions - Extended Version

Cloud computing is becoming an almost ubiquitous part of the computing landscape. For many companies today, moving their entire infrastructure and workloads to the cloud reduces complexity, time to deployment, and saves money. Spot Instances, a subset of Amazon's cloud computing infrastructure (EC2), expands on this. They allow a user to bid on spare compute capacity in Amazon's data centres at heavily discounted prices. If demand was ever to increase such that the user's maximum bid is exceeded, their instance is terminated. In this paper, we conduct one of the first detailed analyses of how location affects the overall cost of deployment of a spot instance. We analyse pricing data across all available Amazon Web Services regions for 60 days for a variety of spot instance types. We relate the data we find to the overall AWS region as well as to the Availability Zone within that region. We conclude that location does play a critical role in spot instance pricing and also that pricing differs depending on the granularity of that location - from a more coarse-grained AWS region to a more fine-grained Availability Zone within a region. We relate the pricing differences we find to the price's reliability, confirming whether one can be confident in the prices reported and subsequently, in the ensuing bids one makes. We conclude by showing that it is possible to run workloads on Spot Instances achieving both a very low risk of termination as well as paying very low amounts per hour.

cs.DC↗