CISCO UCS POWERED BY FUSION IOMEMORY STORAGE DELIVERS LEADING HADOOP PERFORMANCE
#CiscoUCS servers with #CiscoStorageAccelerators, powered by #FusionioMemory technology, benefits #Hadoop deployment for #BigData applications by helping maximize performance while avoiding over-provisioning of hardware resources. EXECUTIVE SUMMARY This document describes the performance and scalability benefits of a high performance Hadoop cluster deployment. This deployment uses the Cisco Unified Computing System™ (Cisco UCS®) blade server, UCS fabric interconnect, and UCS Storage Accelerator devices powered by Fusion ioMemory technology, running the Cloudera Distribution of Apache Hadoop. This combined stack provides a faster time to analytics, with millisecond latency, while offering an unmatched performance advantage. This solution helps to maximize performance while avoiding over-provisioning of hardware resources, which enables optimized deployment of Big Data applications. Here are some of the competitive advantages of this solution: Unleashing Extreme Hadoop Performance: Cisco Unified Computing System B200 blade servers with Cisco Storage Accelerators deliver extreme performance for Hadoop-based Big Data applications. Providing Smart Infrastructure Management: Cisco UCS Manager provides faster resource allocation and this helps in easier, faster Hadoop cluster scaling. Automated server and network policies help to seamlessly scale the Hadoop cluster and lower scaling costs. Enabling High Availability and Higher Network Throughput: The Cisco UCS fabric interconnect provides lossless 40G Ethernet traffic when clustered within a chassis, delivering both high availability and high performance for Hadoop cluster deployments. Ensuring a Faster Time to Analytics, with Millisecond Latency: Cisco Storage Accelerator devices deliver the millisecond latency that Hadoop applications need to maintain real-time response when processing tens of terabytes of data. BIG DATA ADOPTION Big Data – the analysis of massive quantities of data to gain new business insights – has become a new competitive advantage for companies and will be fundamental to business growth and expansion. Big Data adoption is becoming increasingly important across most industries. Retail and healthcare are two prominent industries reaping the benefits of its deployment: retail employs selective ad promotion, while healthcare integrates information from various sources (sensors, X-rays, handwriting, and other medical images) and delivers relevant information in a shorter time, for better patient outcomes. Financial services, communications media, insurance, transportation, and manufacturing are other industries that are capitalizing on the benefits of Big Data. BIG DATA CHALLENGES As various industries adopt Big Data for enterprise-wide solutions, multiple challenges arise: Determining how to get the most business value Integrating Big Data technology with existing infrastructure Keeping the cost of technology infrastructure low (hardware economics) Using a shared infrastructure, being scalable without downtime, and offering fault tolerance, all with lower cost (economics of scale) SOLUTION STACK ADVANTAGES Integrating Big Data solutions with existing infrastructure is an important need. Customers using Cisco UCS infrastructure for relational databases such as Oracle and SQL Server will find it relatively easy to integrate Big Data applications into a solution stack, using Cisco UCS servers for seamless integration and deployment. Below are some of the key advantages of this solution stack. Cisco UCS BIOS policies can be customized and automated for large-scale and rapid Hadoop deployment. This saves significant time and effort and improves operational efficiency. The Cisco UCS blade server with Cisco Storage Accelerators saves significant rack space, thereby increasing Hadoop cluster density. The solution provides savings in power and cooling costs, compared to traditional rack servers with many hard disk drives. A fault-tolerant Cisco hardware stack, improved operation efficiency for Hadoop deployment, rack space savings, and reduced power and cooling requirements all reduces the customer total cost of ownership (TCO).