Name
Abstract | ||
|---|---|---|
Microservices, serverless architectures, cloud native programming are novel paradigms and techniques which could significantly reduce the burden on both developers and operators of future services. Several types of applications fit in well with the new concepts easing the life of different stakeholders while enabling cloud-grade service deployments. However, latency sensitive applications with strict delay constraints between different components pose additional challenges on the platforms. In order to gain benefit from recent cloud technologies for latency sensitive applications as well, a comprehensive performance analysis of available platforms and relevant components is a crucial first step. In this paper, we address one of the most widely used and versatile cloud platforms, namely Amazon Web Services (AWS), and reveal the delay characteristics of key components and services which impact the overall performance of latency sensitive applications. Our contribution is threefold. First, we define a detailed measurement methodology for CaaS/FaaS (Container/Function as a Service) platforms, specifically for AWS. Second, we provide a comprehensive analysis of AWS components focusing on delay characteristics. Third, we attempt to adjust a drone control application to the platform and investigate the performance on today's system. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CLOUD.2019.00054 | 2019 IEEE 12th International Conference on Cloud Computing (CLOUD) |
Keywords | Field | DocType |
AWS,Cloud computing,Latency sensitive applications,Performance measurement,Function as a Service | Latency (engineering),Computer science,Performance measurement,Function as a service,Operator (computer programming),Drone,Microservices,Amazon web services,Distributed computing,Cloud computing | Conference |
ISSN | ISBN | Citations |
2159-6182 | 978-1-7281-2706-4 | 2 |
PageRank | References | Authors |
0.40 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| István Pelle | 1 | 13 | 2.82 |
| Janos Czentye | 2 | 34 | 4.22 |
| János Dóka | 3 | 10 | 3.24 |
| Balázs Sonkoly | 4 | 137 | 22.70 |