high_scalability high_scalability-2010 high_scalability-2010-913 knowledge-graph by maker-knowledge-mining
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Introduction: Zynga Moves 1 Petabyte Of Data Daily; Adds 1,000 Servers A Week by Leena Rao. 10 percent of the world’s internet population (approximately 215 million monthly users) has played a Zynga game . Jeremy Cole writes an incredible article explaining why MySQL will swap on a NUMA system when there's apparently a lot of free RAM. The MySQL “swap insanity” problem and the effects of the NUMA architecture . These boxes are now essentially appliances, maybe it's time for a special built OS that doesn't try to act like a timesharing system sharing scarce resources? Linux Kernel Tuning for C500k by Jared "Lucky" Kuolt. Instead of running 100 servers with 10,000 connections each, we’d rather run 2 servers with 500,000 connections apiece . A Microsoft case study on using Azure: Game Developer Meets Demand and Prepares for Success with Scalable Cloud Solution . Good, we don't see enough on Azure as a viable option. The SMAQ stack for big data by Edd Dumbill. Storage, MapReduce and
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1 10 percent of the world’s internet population (approximately 215 million monthly users) has played a Zynga game . [sent-2, score-0.479]
2 Jeremy Cole writes an incredible article explaining why MySQL will swap on a NUMA system when there's apparently a lot of free RAM. [sent-3, score-0.555]
3 The MySQL “swap insanity” problem and the effects of the NUMA architecture . [sent-4, score-0.102]
4 These boxes are now essentially appliances, maybe it's time for a special built OS that doesn't try to act like a timesharing system sharing scarce resources? [sent-5, score-0.659]
5 Instead of running 100 servers with 10,000 connections each, we’d rather run 2 servers with 500,000 connections apiece . [sent-7, score-0.476]
6 A Microsoft case study on using Azure: Game Developer Meets Demand and Prepares for Success with Scalable Cloud Solution . [sent-8, score-0.089]
7 Good, we don't see enough on Azure as a viable option. [sent-9, score-0.104]
8 Very few applications can natively and easily scale to what we call cloud scale or web scale as they are out of the box. [sent-13, score-0.451]
9 It's not all about power after all, servers account for 57% of monthly data center costs, power is 13%. [sent-18, score-0.665]
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Introduction: Zynga Moves 1 Petabyte Of Data Daily; Adds 1,000 Servers A Week by Leena Rao. 10 percent of the world’s internet population (approximately 215 million monthly users) has played a Zynga game . Jeremy Cole writes an incredible article explaining why MySQL will swap on a NUMA system when there's apparently a lot of free RAM. The MySQL “swap insanity” problem and the effects of the NUMA architecture . These boxes are now essentially appliances, maybe it's time for a special built OS that doesn't try to act like a timesharing system sharing scarce resources? Linux Kernel Tuning for C500k by Jared "Lucky" Kuolt. Instead of running 100 servers with 10,000 connections each, we’d rather run 2 servers with 500,000 connections apiece . A Microsoft case study on using Azure: Game Developer Meets Demand and Prepares for Success with Scalable Cloud Solution . Good, we don't see enough on Azure as a viable option. The SMAQ stack for big data by Edd Dumbill. Storage, MapReduce and
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Introduction: It's HighScalability Time: 50 million in 50 days : Draw Something downloads; 40 million concurrent users : Skype Key to making sensors ubiquitous is getting the BOM cost down. Here's a dream way of making that happen: Bye-Bye Batteries: Radio Waves as a Low-Power Source . “Silicon technology has advanced to the point where even tiny amounts of energy can do useful work.” No batteries == cheaper, smaller products == ubiquity. The MySQL “swap insanity” problem and the effects of the NUMA architecture . Jeremy Cole with a spectacular article on the differences between NUMA and SMP/UMA systems and the mostly unsatisfactory tricks required to get MySQL to perform on NUMA systems. There are really two issues: the evils of an OS controlled swap and NUMA performance effects due to a single node (in the NUMA sense) running out of memory. This is the kind of stuff you only see when you push your systems to the edge. Also, Measuring NUMA effects with the STREAM benchmark , MongoDB
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Introduction: Release early and often. A/B testing. Creating a landing page and buying ads on AdSense. All are ways of providing quick feedback in order to validate an idea. If you are like Zynga, with 250 million active users a month, how do you cost effectively prove out a game that could flop or get 90 million users (like CityVille) in an instant? Zynga handles this problem inlle an innovative way, by inverting the typical cloud burst scenario that has excess traffic flowing from a datacenter to a cloud, to having a game start in the cloud and then moving to the datacenter once the game has proved popular enough to keep. This process is nicely described by Charles Babcock in Lessons From FarmVille: How Zynga Uses The Cloud , in an interview with Allan Leinwand, CTO of infrastructure engineering at Zynga. When paired down to its essence, Zynga's strategy goes something like this: Games are risky . Even with all their experience, Zynga can't know how many people will play a game or how
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Introduction: When you have a large population of servers you have both the opportunity and the incentive to perform interesting studies. Authors from Google and the University of California in Optimizing Google’s Warehouse Scale Computers: The NUMA Experience conducted such a study, taking a look at how jobs run on clusters of machines using a NUMA architecture. Since NUMA is common on server class machines it's a topic of general interest for those looking to maximize machine utilization across clusters. Some of the results are surprising: The methodology of how to attribute such fine performance variations to NUMA effects within such a complex system is perhaps more interesting than the results themselves. Well worth reading just for that story. The performance swing due to NUMA is up to 15% on AMD Barcelona for Gmail backend and 20% on Intel Westmere for Web-search frontend. Memory locality is not always King. Because of the interaction between NUMA and cache sharing/contention it
Introduction: Now that we have the C10K concurrent connection problem licked, how do we level up and support 10 million concurrent connections? Impossible you say. Nope, systems right now are delivering 10 million concurrent connections using techniques that are as radical as they may be unfamiliar. To learn how it’s done we turn to Robert Graham , CEO of Errata Security, and his absolutely fantastic talk at Shmoocon 2013 called C10M Defending The Internet At Scale . Robert has a brilliant way of framing the problem that I’ve never heard of before. He starts with a little bit of history, relating how Unix wasn’t originally designed to be a general server OS, it was designed to be a control system for a telephone network. It was the telephone network that actually transported the data so there was a clean separation between the control plane and the data plane. The problem is we now use Unix servers as part of the data plane , which we shouldn’t do at all. If we were des
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Introduction: You're in good hands with HighScalability : Netflix - Cassandra, AWS, 288 instances, 3.3 million writes per second . Quotable quotes: @bretlowery : "A #DBA walks into a #NoSQL bar, but turns and leaves because he couldn't find a table." @AdanVali : HP to Deploy Memristor Powered SSD Replacement Within 18 Months @eden : Ori Lahav: "When planning scalability, think x100, design x5 and deploy x1.5 of current traffic" @jkalucki : If you are IO bound, start with your checkbook! Everything I Ever Learned About JVM Performance Tuning @Twitter . Learn how to tune your Hotspot and other Javasutra secrets. By moving off the cloud Mixipanel may have lost their angel status. Why would they do such a thing? Read Why We Moved Off The Cloud for the details. The reason for the fall: highly variable performance. Highly variable performance is incredibly hard to code or design around (think a server that normally does 300 queries per second with low I/
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