Towards Serverless as Commodity

Kaviani, Nima; Kalinin, D. S.; Maximilien, Michael

doi:10.1145/3366623.3368135

Cited by 20 publications

(16 citation statements)

References 4 publications

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“…Eismann et al [37] demonstrated the benefits and challenges that arise in the performance testing of microservices and how to manage the unique complications that arise while doing so. Kaviani et al [38] discusses the effectiveness of several key components of Knative and its contribution to opensource serverless computing platforms. They found the Knative autoscaler highly effective and mature for modern workloads.…”

Section: Related Workmentioning

confidence: 99%

Performance Modeling of Serverless Computing Platforms

Mahmoudi

Khazaei

2022

IEEE Trans. Cloud Comput.

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Developing accurate and extendable performance models for serverless platforms, aka Function-as-a-Service (FaaS) platforms, is a very challenging task. Also, implementation and experimentation on real serverless platforms is both costly and time-consuming. However, at the moment, there is no comprehensive simulation tool or framework to be used instead of the real platform. As a result, in this paper, we fill this gap by proposing a simulation platform, called SimFaaS, which assists serverless application developers to develop optimized Function-as-a-Service applications in terms of cost and performance. On the other hand, SimFaaS can be leveraged by FaaS providers to tailor their platforms to be workload-aware so that they can increase profit and quality of service at the same time. Also, serverless platform providers can evaluate new designs, implementations, and deployments on SimFaaS in a timely and cost-efficient manner. SimFaaS is open-source, well-documented, and publicly available, making it easily usable and extendable to incorporate more use case scenarios in the future. Besides, it provides performance engineers with a set of tools that can calculate several characteristics of serverless platform internal states, which is otherwise hard (mostly impossible) to extract from real platforms. In previous studies, temporal and steady-state performance models for serverless computing platforms have been developed. However, those models are limited to Markovian processes. We designed SimFaaS as a tool that can help overcome such limitations for performance and cost prediction in serverless computing. We show how SimFaaS facilitates the prediction of essential performance metrics such as average response time, probability of cold start, and the average number of instances reflecting the infrastructure cost incurred by the serverless computing provider. We evaluate the accuracy and applicability of SimFaaS by comparing the prediction results with real-world traces from Amazon AWS Lambda.

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Section: Related Workmentioning

confidence: 99%

Performance Modeling of Serverless Computing Platforms

Mahmoudi

Khazaei

2022

IEEE Trans. Cloud Comput.

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“…Kubernetes is for cloud native applications an extension of what the operating system is for traditional applications. It is becoming the de facto standard for Platform as a Service [3], abstracting computational infrastructure and standardizing deployment, so that an application can run unmodified on sites across the globe. Scientific applications are routinely deployed on Kubernetes [4][5][6], and even HPC use cases are being investigated [7].…”

Section: Why Kubernetes?mentioning

confidence: 99%

“…Based on this, we define 3 QoS classes, which serve as Service Level Objectives (SLO), against the Service Level Indicator (SLI) of response latency under load. Because the latency depends on the complexity of each website, which is in the hands of the website admins and not the infrastructure, the SLO is met not by defining a set value of the SLI, but by asserting that the SLI be stable 3 . The 3 QoS classes are:…”

Section: Service Level Objectivesmentioning

confidence: 99%

Building a Kubernetes infrastructure for CERN’s Content Management Systems

et al. 2021

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The infrastructure behind home.cern and 1000 other Drupal websites serves more than 15,000 unique visitors daily. To best serve the site owners, a small engineering team needs development speed to adapt to their evolving needs and operational velocity to troubleshoot emerging problems rapidly. We designed a new Web Frameworks platform by extending Kubernetes to replace the ageing physical infrastructure and reduce the dependency on homebrew components. The new platform is modular, built around standard components and thus less complex to operate. Some requirements are covered solely by upstream open source projects, whereas others by components shared across CERN’s web hosting platforms. We leverage the Operator framework and the Kubernetes API to get observability, policy enforcement, access control and auditing, and high availability for free. Thanks to containers and namespaces, websites are isolated. This isolation clarifies security boundaries and minimizes attack surface, while empowering site owners. In this work we present the new system’s open-source design contrasted with the one it replaces, demonstrating how we drastically reduced our technical debt.

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“…Fixing the number of containers in an application agnostic manner will result in SLO violations, especially for functions with strict response latencies. Also the schedulers used in existing open-source platforms like Fission [14], Knative [59] use horizontal pod autoscaler which are not aware of application execution times to employ queuing. Key takeaway: Based on SLOs, cold-start latencies and execution times of applications, queuing functions can minimize the number of containers spawned without violating SLOs.…”

Section: Cold-start Latency For Singlementioning

confidence: 99%