In order to meet stringent performance requirements, system administrators must effectively
detect undesirable performance behaviours, identify potential root causes, and take …

Serverless computing is a new pay-per-use cloud service paradigm that automates resource
scaling for stateless functions and can potentially facilitate bursty machine learning serving …

Many large-scale software systems must service thousands or millions of concurrent
requests. These systems must be load tested to ensure that they can function correctly under …

Serverless computing is gaining popularity for machine learning (ML) serving workload due
to its autonomous resource scaling, easy to use and pay-per-use cost model. Existing …

Commodity clusters are used routinely for deploying service hosting platforms. Due to
hardware and operation costs, clusters need to be shared among multiple services. Crucial …

Flash-based Solid State Drive (SSD) has been productively shipped and deployed in large
scale storage systems. However, a single flash-based SSD cannot satisfy the capacity …

Entering the era of cloud computing, data centers are scaling in a fast pace. However, as the
increasing number of servers being deployed in data centers, the data center power …

Business process (BP) designs and enterprise information system (IS) designs are often not
well aligned. Missing alignment may result in performance problems at run-time, such as …

Modern distributed systems and Internet-of-Things applications are governed by fast living
and changing requirements. Moreover, they have to struggle with huge amounts of data that …

The design of autonomic systems often relies on representative benchmarks for evaluating
system performance and scalability. Despite the fact that experimental observations have …