Large-scale data centers run latency-critical jobs with quality-of-service (QoS) requirements,
and throughput-oriented background jobs, which need to achieve high perfor-mance …

Nowadays, large monolithic web applications are manually decomposed into microservices
for many reasons including adopting a modern architecture to ease maintenance and …

Scientific workflow management systems like Nextflow support large-scale data analysis by
abstracting away the details of scientific workflows. In these systems, workflows consist of …

Finding good cloud configurations for deploying a single distributed system is already a
challenging task, and it becomes substantially harder when a data analytics cluster is …

Multi-core architectures have enabled data centers to increasingly co-locate multiple jobs to
improve resource utilization and lower the operational cost. Unfortunately, naively co …

As software systems grow in complexity and the space of possible configurations increases
exponentially, finding the near-optimal configuration of a software system becomes …

Deep learning model inference is a key service in many businesses and scientific discovery
processes. This paper introduces Ribbon, a novel deep learning inference serving system …

Current serverless offerings give users limited flexibility for configuring the resources
allocated to their function invocations. This simplifies the interface for users to deploy server …

In modern computing environments, users may have multiple systems accessible to them
such as local clusters, private clouds, or public clouds. This abundance of choices makes it …

Cloud configuration optimization is the procedure to determine the number and the type of
instances to use when deploying an application in cloud environments, given a cost or …