Application Performance Optimization and Load Balancing

Application Performance Optimization and Load Balancing Application Performance Optimization and Load Balancing using RAID and Caching Techniques Akilesh Kailash Sunil Iyer Kolar Suresh Kumar Sabarish Venkatraman    ABSTRACT As the data processing and demand for storage grows, the performance of a critical application should always be intact with respect to disk I/O. There has been considerable improvements related to disk seek, latency and spindle speeds; However, these improvements have not met the challenges and addresses the need for better performance and load balancing. The challenge of any Database administrator is to maximize the Application I/O performance and ensure the high availability with zero downtime. This performance challenge can be met using I/O monitoring, Load balancing, Cache management and RAID (Redundant Array of Inexpensive Disks) technologies. The primary goal of this paper is to exemplify the details of successfully solving the I/O problems of a database application in a consistent fashion with the ap propriate RAID configurations, caching mechanisms and load balancing algorithm. Categories and Subject Descriptors B.3.2 [Design Styles]: Mass storage – RAID. D.4.2 [Storage Management]: Secondary storage, Storage hierarchies. D.4.3 [File Systems Management]: File organization. D.4.4 [Communications Management]: Input/Output. D.4.5 [Reliability]: Backup procedures, Fault-tolerance. General Terms Algorithms, Performance, Design, Theory, Reliability. Keywords RAID – Redundant Array of Inexpensive Disks I/O – Input/Output DBA – Database Administrators HA – High Availability OLTP – Online Transaction Processing. IOPS – HBA – 1. INTRODUCTION RAID technology addresses the need for higher storage capacity in IO system and provides the feature of data redundancy. This helps in efficient and improved disk access and avoids data loss by disk failures. Theoretically, RAID is mainly used to create a logical disk from two or more physical d isk drives in order to provide high bandwidth. RAID is an imperative part of storage stack and fabric layer and is coordinated by various storage vendors like EMC, Hitachi, NetApp. RAID technologies have enumerated different methods in building storage stacks and sub-systems for different kinds of databases. Thus, the two main technical reasons for switching to RAID are scalability and high availability in the context of I/O and system performance. As the database sizes of today have grown manifold from the gigabytes to petabytes range, the intricacy to scale I/O performance of such gigantic systems is needed very much for critical applications. Load balancing is a critical factor in environments like Operating Systems, Clusters, Networking and Applications. They play a quintessential role in the performance and reliability of any environment avoiding catastrophic failures. In a quotidian scenario, the resource allocation and load balancing are done through hash methods, genetic alg orithms and several scheduling algorithms in Operating systems. Many database applications demand high throughput and availability from storage subsystems. For instance, a stock market application running in New York stock exchange will need to have a high throughput and bandwidth with absolutely no downtime. This requires continuous operation i.e., the need to satisfy each I/O request even in the case of disk failures. It is not acceptable to meet the aforementioned requirements at the cost of deprived performance mainly in real-time applications such as video and audio. It is highly unacceptable if a video is played at slower speed or the data is lost during transmission and ends abruptly.