Deploying and Optimizing for Cloud Storage Systems using Swift Simulator - DSI 2016

With the rise of cloud systems, IT spending on storage system is increasing. In order to minimize costs, architects must optimize system capacities and characteristics. Current capacity planning is mostly based on trial and errors as well as rough resource estimations. With increasing hardware diversity and software stack complexity this approach is not efficient enough. To meet both Storage capacity and SLA/SLOs requirements needs kind of trade-off.

If you are planning to deploy a storage cluster, growth is what you should be concerned with and prepared for. So how exactly can you architect a storage system, without breaking the bank, while sustaining a sufficient capacity and performance across the scaling spectrum?

The session is designed to present a novel simulation approach which shows flexibility and high accuracy to be used for cluster capacity planning, performance evaluation and optimization before system provisioning. We will focus specifically on storage capacity planning and provide criteria for getting the best price-performance configuration by setting Memory, SSD and Magnetic Disk ratio. We will also highlight performance optimization ability via evaluating different OS parameters (e.g. log flush and write barrier), software configurations (e.g. proxy and object worker numbers) and hardware setups (e.g. CPU, cluster size, the ratio of proxy server to storage server, network topology selection CLOS vs. Fat Tree).

Learning Objectives

Design challenges of a cloud storage deployment
Storage system modeling technology for OpenStack-Swift
Use Case study: plan and optimize a storage cluster to meet capacity and performance requirements.