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high_scalability 2008 knowledge graph

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1 high scalability-2008-12-30-Scalability Perspectives #5: Werner Vogels – The Amazon Technology Platform

Introduction: Scalability Perspectives is a series of posts that highlights the ideas that will shape the next decade of IT architecture. Each post is dedicated to a thought leader of the information age and his vision of the future. Be warned though – the journey into the minds and perspectives of these people requires an open mind. Werner Vogels Dr. Werner Vogels is Vice President & Chief Technology Officer at Amazon.com where he is responsible for driving the company’s technology vision, which is to continuously enhance the innovation on behalf of Amazon’s customers at a global scale. Prior to joining Amazon, he worked as a researcher at Cornell University where he was a principal investigator in several research projects that target the scalability and robustness of mission-critical enterprise computing systems. He is regarded as one of the world's top experts on ultra-scalable systems and he uses his weblog to educate the community about issues such as eventual consistency. Information

2 high scalability-2008-12-29-Platform virtualization - top 25 providers (software, hardware, combined)

Introduction: In this article they present the companies which offers means (mainly, the software and hardware) which powers most of the cloud computing hosting providers, namely virtualization solutions. Read the entire article about Platform virtualization - top 25 providers (software, hardware, combined) at MyTestBox.com - web software reviews, news, tips & tricks .

3 high scalability-2008-12-29-Paper: Spamalytics: An Empirical Analysisof Spam Marketing Conversion

Introduction: Under the philosophy that the best method to analyse spam is to become a spammer , this absolutely fascinating paper recounts how a team of UC Berkely researchers went under cover to infiltrate a spam network. Part CSI, part Mission Impossible, and part MacGyver, the team hijacked the botnet so that their code was actually part of the dark network itself. Once inside they figured out the architecture and protocols of the botnet and how many sales they were able to tally. Truly elegant work. Two different spam campaigns were run on a Storm botnet network of 75,800 zombie computers. Storm is a peer-to-peer botnet that uses spam to creep its tentacles through the world wide computer network. One of the campains distributed viruses in order to recruit new bots into the network. This is normally accomplished by enticing people to download email attachments. An astonishing one in ten people downloaded the executable and ran it, which means we won't run out of zombies soon. The downloade

4 high scalability-2008-12-29-100% on Amazon Web Services: Soocial.com - a lesson of porting your service to Amazon

Introduction: Simone Brunozzi, technology evangelist for Amazon Web Services in Europe, describes how Soocial.com was fully ported to Amazon web services. ---------------- This period of the year I decided to dedicate some time to better understand how our customers use AWS, therefore I spent some online time with Stefan Fountain and the nice guys at Soocial.com, a "one address book solution to contact management", and I would like to share with you some details of their IT infrastructure, which now runs 100% on Amazon Web Services! In the last few months, they've been working hard to cope with tens of thousands of users and to get ready to easily scale to millions. To make this possible, they decided to move ALL their architecture to Amazon Web Services. Despite the fact that they were quite happy with their previous hosting provider, Amazon proved to be the way to go. ----------------- Read the rest of the article here .

5 high scalability-2008-12-28-How to Organize a Database Table’s Keys for Scalability

Introduction: The key (no pun intended) to understanding how to organize your dataset’s data is to think of each shard not as an individual database, but as one large singular database. Just as in a normal single server database setup where you have a unique key for each row within a table, each row key within each individual shard must be unique to the whole dataset partitioned across all shards. There are a few different ways we can accomplish uniqueness of row keys across a shard cluster. Each has its pro’s and con’s and the one chosen should be specific to the problems you’re trying to solve.

6 high scalability-2008-12-22-SLAs in the SaaS space

Introduction: This may be a bit higher level then the general discussion here, but I think this is an important issue in how it relates to reliability and uptime. What kind of SLAs should we be expecting from SaaS services and platforms (e.g. AWS, Google App Engine, Google Premium Apps, salesforce.com, etc.)? Up to today, most SaaS services either have no SLAs or offer very weak penalties. What will it take to get these services up to the point where they can offer the SLAs that users (and more importantly, businesses) require? I presume most of the members here want to see more movement into the cloud and to SaaS services, and I'm thinking that until we see more substantial SLA guarantees, most businesses will continue to shy away as long as they can. Would love to hear what others think. Or am I totally off base?

7 high scalability-2008-12-21-The I.H.S.D.F. Theorem: A Proposed Theorem for the Trade-offs in Horizontally Scalable Systems

Introduction: Successful software design is all about trade-offs. In the typical (if there is such a thing) distributed system, recognizing the importance of trade-offs within the design of your architecture is integral to the success of your system. Despite this reality, I see time and time again, developers choosing a particular solution based on an ill-placed belief in their solution as a “silver bullet”, or a solution that conquers all, despite the inevitable occurrence of changing requirements. Regardless of the reasons behind this phenomenon, I’d like to outline a few of the methods I use to ensure that I’m making good scalable decisions without losing sight of the trade-offs that accompany them. I’d also like to compile (pun intended) the issues at hand, by formulating a simple theorem that we can use to describe this oft occurring situation.

8 high scalability-2008-12-20-Second Life Architecture - The Grid

Introduction: Update: Presentation: Second Life’s Architecture . Ian Wilkes, VP of Systems Engineering, describes the architecture used by the popular game named Second Life. Ian presents how the architecture was at its debut and how it evolved over years as users and features have been added. Second Life is a 3-D virtual world created by its Residents. Virtual Worlds are expected to be more and more popular on the internet so their architecture might be of interest. Especially important is the appearance of open virtual worlds or metaverses. What happens when video games meet Web 2.0? What happens is the metaverse . Information Sources Second Life runs MySQL Interview with Ian Wilkes TechTrends: Inside Linden Lab Town Hall with Cory Linden InformationWeek articles ( 1 , 2 ) and blog Second Life Wiki: Server Architecture Wikipedia: Second Life Server Second Life Blog Second Life: A Guide to Your Virtual World Platform

9 high scalability-2008-12-19-How to measure memory required for a user session

Introduction: hi, What are the practices followed, tools used to measure session memory requirement per user? Thanks, Unmesh

10 high scalability-2008-12-19-Gigaspaces curbs latency outliers with Java Real Time

Introduction: Today, most banks have migrated their internal software development from C/C++ to the Java language because of well-known advantages in development productivity (Java Platform), robustness & reliability (Garbage Collector) and platform independence (Java Bytecode). They may even have gotten better throughput performance through the use of standard architectures and application servers (Java Enterprise Edition). Among the few banking applications that have not been able to benefit yet from the Java revolution, you find the latency-critical applications connected to the trading floor. Why? Because of the unpredictable pauses introduced by the garbage collector which result in significant jitter (variance of execution time). In this post Frederic Pariente Engineering Manager at Sun Microsystems posted a summary of a case study on how the use of Sun Real Time JVM and GigaSpaces was used in the context of of a customer proof-of-concept this summer to ensure guaranteed latency per m

11 high scalability-2008-12-18-Risk Analysis on the Cloud (Using Excel and GigaSpaces)

Introduction: Every day brings news of either more failures of the financial systems or out-right fraud, with the $50 billion Bernard Madoff Ponzi scheme being the latest, breaking all records. This post provide a technical overview of a solution that was implemented for one of the largest banks in China. The solution illustrate how one can use Excel as a front end client and at the same time leverage cloud computing model and mapreduce as well as other patterns to scale-out risk calculations. I'm hoping that this type of approach will reduce the chances for seeing this type of fraud from happening in the future.

12 high scalability-2008-12-17-Scalability Strategies Primer: Database Sharding

Introduction: This article is a primer, intended to shine some much needed light on the logical, process oriented implementations of database scalability strategies in the form of a broad introduction. More specifically, the intent is to elaborate on the majority of these implementations by example.

13 high scalability-2008-12-17-Ringo - Distributed key-value storage for immutable data

Introduction: Ringo is an experimental, distributed, replicating key-value store based on consistent hashing and immutable data. Unlike many general-purpose databases, Ringo is designed for a specific use case: For archiving small (less than 4KB) or medium-size data items (<100MB) in real-time so that the data can survive K - 1 disk breaks, where K is the desired number of replicas, without any downtime, in a manner that scales to terabytes of data. In addition to storing, Ringo should be able to retrieve individual or small sets of data items with low latencies (<10ms) and provide a convenient on-disk format for bulk data access. Ringo is compatible with the map-reduce framework Disco and it was started at Nokia Research Center Palo Alto.

14 high scalability-2008-12-16-[ANN] New Open Source Cache System

Introduction: The SHOP.COM Cache System is now available at http://code.google.com/p/sccache/ The SHOP.COM Cache System is an object cache system that... * is an in-process cache and external, shared Cache * is horizontally scalable * stores cached objects to disk * supports associative keys * is non-transactional * can have any size key and any size data * does auto-GC based on TTL * is container and platform neutral It was built in-house at SHOP.COM (by me) and has powered our website for years. We are open-sourcing it in the hope that it will be useful to others and to get some help in its maintenance. This is our first open source attempt and we'd appreciate any help and comments.

15 high scalability-2008-12-16-Facebook is Hiring

Introduction: I thought with the job situation these days that people might be interested in some open jobs at Facebook. Here's what's available: Facebook is hiring! We are looking for a Systems Engineer/Architect and Site Reliability Engineer. I have attached the job descriptions below. If you are interested, please contact Michelle Bostock mbostock-at-facebook.com. Thanks and Happy Holidays! Systems Architect Palo Alto, CA Description Facebook is seeking a seasoned Systems Architect to join the Operations team. The position is full-time and is based in our main office in downtown Palo Alto and will report to the Manager of Systems Operations. Responsibilities * Analyze application flow and infrastructure design to improve performance and scalability of the site * Collaborate on design of services infrastructure from servers to networking * Monitor, analyze, and make recommendations as appropriate to improve site stability and availability * Evaluate hardware and softwar

16 high scalability-2008-12-14-Scaling MySQL on a 256-way T5440 server using Solaris ZFS and Java 1.7

Introduction: How to scale MySQL on a 32 core system with 256 threads? Diagonal scalability in a box. An impressive benchmark that achieved more than 79,000 SQL queries per second on a single 4 RU server! Is this real? If so what is the role of good old horizontal scalability? The goals of the benchmark: Reach a high throughput of SQL queries on a 256-way Sun SPARC Enterprise T5440 Do it 21st century style i.e. with MySQL and ZFS , not 20th century style i.e with OraSybInf... and VxFS Do it with minimal tuning i.e as close as possible as out-of-the-box

17 high scalability-2008-12-13-Strategy: Facebook Tweaks to Handle 6 Time as Many Memcached Requests

Introduction: Our latest strategy is taken from a great post by Paul Saab of Facebook , detailing how with changes Facebook has made to memcached they have: ...been able to scale memcached to handle 200,000 UDP requests per second with an average latency of 173 microseconds. The total throughput achieved is 300,000 UDP requests/s, but the latency at that request rate is too high to be useful in our system. This is an amazing increase from 50,000 UDP requests/s using the stock version of Linux and memcached. To scale Facebook has hundreds of thousands of TCP connections open to their memcached processes. First, this is still amazing. It's not so long ago you could have never done this. Optimizing connection use was always a priority because the OS simply couldn't handle large numbers of connections or large numbers of threads or large numbers of CPUs. To get to this point is a big accomplishment. Still, at that scale there are problems that are often solved. Some of the problem Facebook faced a

18 high scalability-2008-12-09-Rules of Thumb in Data Engineering

Introduction: This is an interesting and still relevant research paper by Jim Gray, Prashant Shenoy at Microsoft Research that examines the rules of thumb for the design of data storage systems. It looks at storage, processing, and networking costs, ratios, and trends with a particular focus on performance and price/performance. Jim Gray has an updated presentation on this interesting topic: Long Term Storage Trends and You . Robin Harris has a great post that reflects on the Rules of Thumb whitepaper on his StorageMojo blog: Architecting the Internet Data Center - Parts I-IV .

19 high scalability-2008-12-06-Paper: Real-world Concurrency

Introduction: An excellent article by Bryan Cantrill and Jeff Bonwick on how to write multi-threaded code. With more processors and no magic bullet solution for how to use them, knowing how to write multiprocessor code that doesn't screw up your system is still a valuable skill. Some topics: Know your cold paths from your hot paths. Intuition is frequently wrong—be data intensive. Know when—and when not—to break up a lock. Be wary of readers/writer locks. Consider per-CPU locking. Know when to broadcast—and when to signal. Learn to debug postmortem. Design your systems to be composable. Don't use a semaphore where a mutex would suffice. Consider memory retiring to implement per-chain hash-table locks. Be aware of false sharing. Consider using nonblocking synchronization routines to monitor contention. When reacquiring locks, consider using generation counts to detect state change. Use wait- and lock-free structures only if you absolutely must. Prepare for the th

20 high scalability-2008-12-05-Sprinkle - Provisioning Tool to Build Remote Servers

Introduction: At 37 Signals Joshua Sierles describes how 37 Signals uses Sprinkle to configure their servers within EC2. Sprinkle defines a domain specific meta-language for describing and processing the installation of software . You can find an interesting discussion of Sprinkle's creation story by the creator himself, Marcus Crafter, in Sprinkle Some Powder! . Marcus divides provisioning tools into two categories: Task Based - the tool issues a list of commands to run on the remote system, either remotely via a network connection or smart client. Policy/state Based - the tool determines what needs to be run on the remote system by examining its current and final state. Sprinkle combines both models together in a chocolate-in-my-peanut-butter approach using normal Ruby code as the DSL (domain specific language) to declaratively describe remote system configurations. 37 Signals likes the use of Ruby as the DSL because it makes learning a separate syntax unnecessary. I've successfu