Resource under-utilization is common in cloud data centers. Prior works have proposed
improving utilization by running provider workloads in the background, colocated with tenant …

To fully utilize computing resources, cloud providers such as Google and Alibaba choose to
co-locate online services with batch processing applications in their data centers. By …

With the tremendous growth of cloud computing, it is increasingly critical to provide
quantifiable performance to tenants and to improve resource utilization for the cloud …

An effective way to increase utilization and reduce costs in datacenters is to co-locate their
latency-critical services and batch workloads. In this paper, we describe systems that harvest …

Service providers want to reduce datacenter costs by consolidating workloads onto fewer
servers. At the same time, customers have performance goals, such as meeting tail latency …

Cloud platform provides great flexibility and cost-efficiency for end-users and cloud
operators. However, low resource utilization in modern datacenters brings huge wastes of …

Multi-tenancy in modern datacenters is currently limited to a single latency-critical,
interactive service, running alongside one or more low-priority, best-effort jobs. This limits …

Cloud service providers improve resource utilization by co-locating latency-critical (LC)
workloads with best-effort batch (BE) jobs in datacenters. However, they usually treat an LC …

Despite the potential given by the combination of multi-tenancy and virtualization, resource
utilization in today's data centers is still low. We identify three key characteristics of cloud …

Online Internet applications see dynamic workloads that fluctuate over multiple time scales.
This paper argues that the non-stationarity in Internet application workloads, which causes …