2023_12_wenRisePlanetServerless2023_Reading_Notes
Title: Rise of the Planet of Serverless Computing: A Systematic Review
zoterolink: Rise of the Planet of Serverless Computing A Systematic Review(2023 - Wen et al.).pdf
Reading Notes
Import zotero note:
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Annotations
Following content are annotations from origin paper:
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Imported: 2023-12-27 11:35 pm
background adopted to develop a wide range of software applications, including machine/deep learning [252, 268], numerical computing [227], video processing [74, 125], Internet of Things [144, 277], big data analytics [119, 130], etc
background AWS Lambda [16], Microsoft Azure Functions [22], and Google Cloud Functions [35]. Moreover, there are also some available open-source serverless platforms, e.g., OpenWhisk [48] and OpenFaaS [45].
background serverless evolution [243], characteristic analysis of serverless applications [114, 115], developers’ challenges [121, 257],
background application modelling [272], programming framework of specific applications [84, 277], multi-cloud development [219], stateful serverless applications [82], application migration [214], serverless economic [63], serverless dataset [120], technical debt conceptualization [163], testing and debugging [164], etc.
background resource management [137, 200, 275], cold start performance optimization [67, 126, 198], function communication [143, 230], general programming framework [124, 140]
background Serverless computing provides “Backend as a Service” (BaaS) and “Function as a Service” (FaaS)
target key characteristics
target (1) Functionality and no operations (NoOps)
target (2) Auto-scaling
background Horizontal scaling is to launch (i.e., scale-in) new function instances or recycle (i.e., scale-out) running ones, while vertical scaling is to add (i.e., scale-up) or remove (i.e., scale-down) the amount of computation and other resources from running function instances
target (3) Utilization-based billing:
target (4) Separation of computation and storage
target (5) Additional limitations
background
background Resource Management; General Framework; Cold Start Performance; Function Communication; Function Execution; Stateful FaaS
background Generalizability of application conversion approaches
background generic conversion tools for any application
background Cold start performance problem of serverless applications
background Performance variability of serverless functions
background Fine-grained resource configuration on application development
background Heterogeneous accelerator support
background Monitoring tools
background Representativeness and completeness of benchmark dataset
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Summary
The Problem
Key Ideas & Key insights
Key Mechanisms
Implementation
Key Results
Key Conclusions
Strengths
Weaknesses
Can I do better?
Takeaways
Other comments
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