| 11. |
- Scheuner, Joel, 1991, et al.
(author)
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Transpiling Applications into Optimized Serverless Orchestrations
- 2019
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In: Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019. - : IEEE. ; June 2019, s. 72-73
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Conference paper (peer-reviewed)abstract
- The serverless computing paradigm promises increased development productivity by abstracting the underlying hardware infrastructure and software runtime when building distributed cloud applications. However, composing a serverless application consisting of many tiny functions is still a cumbersome and inflexible process due to the lack of a unified source code view and strong coupling to non-standardized function-level interfaces for code and configuration. In our vision, developers can focus on writing readable source code in a logical structure, which then gets transformed into an optimized multi-function serverless orchestration. Our idea involves transpilation (i.e., source-to-source transformation) based on an optimization model (e.g., cost optimization) by dynamically deciding which set of methods will be grouped into individual deployment units. A successful implementation of our vision would enable a broader range of serverless applications and allow for dynamic deployment optimization based on monitoring runtime metrics. Further, we would expect increased developer productivity by using more familiar abstractions and facilitating clean coding practices and code reuse.
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| 12. |
- Scheuner, Joel, 1991, et al.
(author)
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TriggerBench: A Performance Benchmark for Serverless Function Triggers
- 2022
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In: Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. ; , s. 96-103
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Conference paper (peer-reviewed)abstract
- Serverless computing offers a scalable event-based paradigm for deploying managed cloud-native applications. Function triggers are essential building blocks in serverless, as they initiate any function execution. However, function triggering is insufficiently studied and inherently hard to measure given the distributed, ephemeral, and asynchronous nature of event-based function coordination. To address this gap, we present TriggerBench, a cross-provider benchmark for evaluating serverless function triggers based on distributed tracing. We evaluate the trigger latency (i.e., time to transition between two functions) of eight types of triggers in Microsoft Azure and three in AWS. Our results show that all triggers suffer from long tail latency, storage triggers introduce variable multi-second delays, and HTTP triggers are most suitable for interactive applications. Our insights can guide developers in choosing optimal event or messaging triggers for latency-sensitive applications. Researchers can extend TriggerBench to study the latency, scalability, and reliability of further trigger types and cloud providers.
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| 13. |
- Schirmer, Trever, et al.
(author)
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Fusionize: Improving Serverless Application Performance through Feedback-Driven Function Fusion
- 2022
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In: Proceedings - 2022 IEEE International Conference on Cloud Engineering, IC2E 2022. ; , s. 85-95
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Conference paper (peer-reviewed)abstract
- Serverless computing increases developer productivity by removing operational concerns such as managing hardware or software runtimes. Developers, however, still need to partition their application into functions, which can be error-prone and adds complexity: Using a small function size where only the smallest logical unit of an application is inside a function maximizes flexibility and reusability. Yet, having small functions leads to invocation overheads, additional cold starts, and may increase cost due to double billing during synchronous invocations. In this paper we present Fusionize, a framework that removes these concerns from developers by automatically fusing the application code into a multi-function orchestration with varying function size. Developers only need to write the application code following a lightweight programming model and do not need to worry how the application is turned into functions. Our framework automatically fuses different parts of the application into functions and manages their interactions. Leveraging monitoring data, the framework optimizes the distribution of application parts to functions to optimize deployment goals such as end-to-end latency and cost. Using two example applications, we show that Fusionizecan automatically and iteratively improve the deployment artifacts of the application.
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| 14. |
- van Eyk, Erwin, et al.
(author)
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Beyond Microbenchmarks: The SPEC-RG Vision for a Comprehensive Serverless Benchmark
- 2020
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In: Companion of the ACM/SPEC International Conference on Performance Engineering. - New York, NY, USA : ACM. - 9781450371094 ; , s. 26-31
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Conference paper (peer-reviewed)abstract
- Serverless computing services, such as Function-as-a-Service (FaaS), hold the attractive promise of a high level of abstraction and high performance, combined with the minimization of operational logic. Several large ecosystems of serverless platforms, both open- and closed-source, aim to realize this promise. Consequently, a lucrative market has emerged. However, the performance trade-offs of these systems are not well-understood. Moreover, it is exactly the high level of abstraction and the opaqueness of the operational-side that make performance evaluation studies of serverless platforms challenging. Learning from the history of IT platforms, we argue that a benchmark for serverless platforms could help address this challenge. We envision a comprehensive serverless benchmark, which we contrast to the narrow focus of prior work in this area. We argue that a comprehensive benchmark will need to take into account more than just runtime overhead, and include notions of cost, realistic workloads, more (open-source) platforms, and cloud integrations. Finally, we show through preliminary real-world experiments how such a benchmark can help compare the performance overhead when running a serverless workload on state-of-the-art platforms.
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