PPT-Queuing and Caching to Scalability

James Kovacs JamesKovacscom jkovacspostharvardedu Performance Application A 40 Requests per second Application B 20 Requests per second Scalability Is 20 Requests per Second Enough 20 requests per second. Queuing Theory represents the body of knowledge dealing with waiting lines.. Most queuing problems focus on determining the level of service that a company should provide.. Queuing Theory. Queuing Systems Configurations. in Kentico CMS. Boris . Pocatko. Solution Architect. Kentico Software. borisp@kentico.com. Agenda. Problem. Describing different caching mechanisms. Demo for cache dependencies. API caching and additional info. How It Works and When You Should Use It . Shy Cohen. Principal, . Shy Cohen Consulting. AAP314. What Gurus Need to Know. What’s a cache and what it does. Core and advanced concepts. Caching on premises and in Windows Azure. Ippokratis Pandis. CIDR 2009 - Gong Show. Scalability on CMP. 2. Sun Niagara I - 32 HW Contexts. Update intensive workload. No database lock conflicts. Linear (ideal) scaling. Scalability. problems. Ilija Vukotic. ADC TIM - Chicago. October 28, 2014. Caching – why and where?. Straight Tier3 . Most of the disk space is devoted to input data. The input data is almost always from downloaded from the grid. Telerik Software Academy. http://academy.telerik.com. . ASP.NET MVC. Table of Contents. Why do we need caching?. ASP.NET Output Caching. OutputCache. page directive. Cache profiles. Post-cache substitution. Victor Zakhary, . Divyakant. Agrawal, Amr El . Abbadi. 1. The old problem of Caching. Disk. RAM. L. 2. L. 1. Larger. Slower. Cheaper. Smaller. Faster. Expensive. 2. The old problem of Caching. Smaller. Name. Title. Microsoft Corporation. Presentation Summary. Version: Jul 2010. Feedback: . ryandunn@microsoft.com. . Technical Level: 300/400. Intended Audience: Developers, Architects. Intended Time: 60 minutes. A Framework for Evaluating Caching Policies in a Hierarchical Network of Caches Eman Ramadan, Pariya Babaie , Zhi -Li Zhang Presented By: Arvind Narayanan University of Minnesota, USA Caching at the Web Scale Victor Zakhary, Divyakant Agrawal, Amr El Abbadi Full slide deck: https://goo.gl/1VYGW3 1 The old problem of Caching Disk RAM L 2 L 1 Larger Slower Cheaper Smaller Faster Caching 50.5* COS 518: Advanced Computer Systems Lecture 9 Michael Freedman * Half of 101 Tradeoff Fast: Costly, small, close Slow: Cheap, large, far Based on two assumptions Temporal location: Will be accessed again soon Andrew A. Chien. William Eckhardt Professor of Computer Science, The University of Chicago. Senior Scientist, Argonne National Laboratory. IRIS-HEP Kickoff. September 7, 2018. Traditional Software Scalability. &. Caching. Noah Mendelsohn. Tufts University. Email: . noah@cs.tufts.edu. Web: http://www.cs.tufts.edu/~noah. COMP 150-IDS: Internet Scale Distributed Systems . (Spring 2015). 2. Goals. Explore some general principles of performance,... Huawei. Liyan. Gong, . Fengwei . Qin . @China Mobile. Guangming. Yang @China Telecom. James Guichard @. Futurewei. Gyan Mishra . @Verizon. Tarek Saad @Cisco. Vishnu Beeram @Juniper. Scalability Considerations for .