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

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Publish Date: 
Monday, September 19, 2016
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Abstract: 

Today’s data centers are built on traditional architectures that can take days or weeks to provision new services and typically run with low server utilization, limiting efficiency and flexibility while driving up costs. To meet both Storage capacity and SLA/SLOs requirements also need kind of trade-off.

If you are planning to deploy a cloud storage cluster, growth is what you should be concerned with and prepared for. So how exactly can you architect such a 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 (Hardware Sizing, Hardware component selection and Software Stack Tuning)
Storage system modeling technology for OpenStack-Swift
Use Case study: Use simulation approach to plan and optimize a storage cluster to meet capacity and performance requirements.