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I/O resource isolation of public cloud serverless function runtimes for data-intensive applications
by
Lee, Kyungyong
, Kim, Jeongchul
in
Algorithms
/ Cloud computing
/ Computer Communication Networks
/ Computer Science
/ Employment
/ Linear algebra
/ Operating Systems
/ Processor Architectures
/ Resource allocation
/ Software
/ Workloads
2020
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I/O resource isolation of public cloud serverless function runtimes for data-intensive applications
by
Lee, Kyungyong
, Kim, Jeongchul
in
Algorithms
/ Cloud computing
/ Computer Communication Networks
/ Computer Science
/ Employment
/ Linear algebra
/ Operating Systems
/ Processor Architectures
/ Resource allocation
/ Software
/ Workloads
2020
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Do you wish to request the book?
I/O resource isolation of public cloud serverless function runtimes for data-intensive applications
by
Lee, Kyungyong
, Kim, Jeongchul
in
Algorithms
/ Cloud computing
/ Computer Communication Networks
/ Computer Science
/ Employment
/ Linear algebra
/ Operating Systems
/ Processor Architectures
/ Resource allocation
/ Software
/ Workloads
2020
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I/O resource isolation of public cloud serverless function runtimes for data-intensive applications
Journal Article
I/O resource isolation of public cloud serverless function runtimes for data-intensive applications
2020
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Overview
Serverless computing and a function execution model, Function-as-a-Service (FaaS), are currently receiving considerable attention from both academia and industry. One of the reasons for the success of serverless computing is its straightforward interface that abstracts complex internals of cloud computing resource usage and configurations. However, this approach may result in hiding too much information about how underlying cloud resources would work, entailing that users cannot predict how their applications will perform, especially for IO-heavy ones. To address this issue, we evaluate several aspects of network and disk IO performance with realistic workloads using public FaaS systems. Our analysis reveals that current public FaaS systems do not provide appropriate levels of IO performance differentiation, and the ability to isolate network resource allocation during concurrent execution is rarely offered by service providers. Based on the results presented in this paper, we insist that it must be mandatory for network and disk IO resource performance of FaaS to be more visible and predictable, as is the case for memory and CPU, in order to expand serverless computing applications to data-intensive ones.
Publisher
Springer US,Springer Nature B.V
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