...an extensive study of server CPU utilization across two different public cloud providers. To measure a cloud physical server’s utilization, we launch a small probing Virtual Machine (VM) (often the smallest VM offered) in a cloud provider, and then from within the VM, we monitor the CPU utilization of the underlying hardware machine. Since a cloud is built around multi-tenancy, there are several other VMs running on the same physical hardware. By measuring the underlying hardware’s CPU utilization, we measure the collective CPU utilization of other VMs sitting on the same hardware
Users of cloud services are presented with a bewildering choice of VM types and the choice of VM can have significant implications on performance and cost. In this paper we address the fundamental problem of accurately and economically choosing the best VM for a given workload and user goals. To address the problem of optimal VM selection, we present PARIS, a data-driven system that uses a novel hybrid offline and online data collection and modeling framework to provide accurate performance estimates with minimal data collection. PARIS is able to predict workload performance for different user-specified metrics, and resulting costs for a wide range of VM types and workloads across multiple cloud providers. When compared to a sophisticated baseline linear interpolation model using measured workload performance on two VM types, PARIS produces significantly better estimates of performance. For instance, it reduces runtime prediction error by a factor of 4 for some workloads on both AWS and Azure. The increased accuracy translates into a 45% reduction in user cost while maintaining performance.
In this first post of a series exploring containerized CI solutions, I’m going to be addressing the CI tool with the largest market share in the space: Jenkins. Whether you’re already running Jenkins in a more traditional virtualized or bare metal environment, or if you’re using another CI tool entirely, I hope to show you […]
Signed up to trial Aliyun, the Chinese IaaS cloud, but found out that they currently aren't provisioned for pay as you go, on demand in the US (or Hong Kong, or Singapore). Monthly contract rates are available, so they have capacity, just odd allocation, considering the competition.
Without actually benchmarking, cost seems comparable to an AWS t2.medium instance with similar specifications: 2 core, 4Gb.