Workload characterization is a well-established discipline that plays a key role in many
performance engineering studies. The large-scale social behavior inherent in the …

Google's Borg system is a cluster manager that runs hundreds of thousands of jobs, from
many thousands of different applications, across a number of clusters each with up to tens of …

To better understand the challenges in develo** effective cloud-based resource
schedulers, we analyze the first publicly available trace data from a sizable multi-purpose …

Increasing scale and the need for rapid response to changing requirements are hard to meet
with current monolithic cluster scheduler architectures. This restricts the rate at which new …

Large-scale data analytics frameworks are shifting towards shorter task durations and larger
degrees of parallelism to provide low latency. Scheduling highly parallel jobs that complete …

To improve resource efficiency and design intelligent scheduler for clouds, it is necessary to
understand the workload characteristics and machine utilization in large-scale cloud data …

TetriSched is a scheduler that works in tandem with a calendaring reservation system to
continuously re-evaluate the immediate-term scheduling plan for all pending jobs (including …

System logs are widely used in various tasks of software system management. It is crucial to
avoid logging too little or too much. To achieve so, developers need to make informed …

Containers, as a lightweight application virtualization technology, have recently gained
immense popularity in mainstream cluster management systems like Google Borg and …

The advent of cloud computing promises to provide computational resources to customers
like public utilities such as water and electricity. To deal with dynamically fluctuating …