Amazon Dynamodb
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Reliability and Security of Large Scale Data Storage in Cloud Computing C.W
This article is part of the Reliability Society 2010 Annual Technical Report Reliability and Security of Large Scale Data Storage in Cloud Computing C.W. Hsu ¹¹¹ C.W. Wang ²²² Shiuhpyng Shieh ³³³ Department of Computer Science Taiwan Information Security Center at National Chiao Tung University NCTU (TWISC@NCTU) Email: ¹[email protected] ³[email protected] ²[email protected] Abstract In this article, we will present new challenges to the large scale cloud computing, namely reliability and security. Recent progress in the research area will be briefly reviewed. It has been proved that it is impossible to satisfy consistency, availability, and partitioned-tolerance simultaneously. Tradeoff becomes crucial among these factors to choose a suitable data access model for a distributed storage system. In this article, new security issues will be addressed and potential solutions will be discussed. Introduction “Cloud Computing ”, a novel computing model for large-scale application, has attracted much attention from both academic and industry. Since 2006, Google Inc. Chief Executive Eric Schmidt introduced the term into industry, and related research had been carried out in recent years. Cloud computing provides scalable deployment and fine-grained management of services through efficient resource sharing mechanism (most of them are for hardware resources, such as VM). Convinced by the manner called “ pay-as-you-go ” [1][2], companies can lower the cost of equipment management including machine purchasing, human maintenance, data backup, etc. Many cloud services rapidly appear on the Internet, such as Amazon’s EC2, Microsoft’s Azure, Google’s Gmail, Facebook, and so on. However, the well-known definition of the term “Cloud Computing ” was first given by Prof. -
Performance at Scale with Amazon Elasticache
Performance at Scale with Amazon ElastiCache July 2019 Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Contents Introduction .......................................................................................................................... 1 ElastiCache Overview ......................................................................................................... 2 Alternatives to ElastiCache ................................................................................................. 2 Memcached vs. Redis ......................................................................................................... 3 ElastiCache for Memcached ............................................................................................... 5 Architecture with ElastiCache for Memcached ............................................................... -
Amazon Documentdb Deep Dive
DAT326 Amazon DocumentDB deep dive Joseph Idziorek Antra Grover Principal Product Manager Software Development Engineer Amazon Web Services Fulfillment By Amazon © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Agenda What is the purpose of a document database? What customer problems does Amazon DocumentDB (with MongoDB compatibility) solve and how? Customer use case and learnings: Fulfillment by Amazon What did we deliver for customers this year? What’s next? © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Purpose-built databases Relational Key value Document In-memory Graph Search Time series Ledger Why document databases? Denormalized data Normalized data model model { 'name': 'Bat City Gelato', 'price': '$', 'rating': 5.0, 'review_count': 46, 'categories': ['gelato', 'ice cream'], 'location': { 'address': '6301 W Parmer Ln', 'city': 'Austin', 'country': 'US', 'state': 'TX', 'zip_code': '78729'} } Why document databases? GET https://api.yelp.com/v3/businesses/{id} { 'name': 'Bat City Gelato', 'price': '$', 'rating': 5.0, 'review_count': 46, 'categories': ['gelato', 'ice cream'], 'location': { 'address': '6301 W Parmer Ln', 'city': 'Austin', 'country': 'US', 'state': 'TX', 'zip_code': '78729'} } Why document databases? response = yelp_api.search_query(term='ice cream', location='austin, tx', sort_by='rating', limit=5) Why document databases? for i in response['businesses']: col.insert_one(i) db.businesses.aggregate([ { $group: { _id: "$price", ratingAvg: { $avg: "$rating"}} } ]) db.businesses.find({ -
A Motion Is Requested to Authorize the Execution of a Contract for Amazon Business Procurement Services Through the U.S. Communities Government Purchasing Alliance
MOT 2019-8118 Page 1 of 98 VILLAGE OF DOWNERS GROVE Report for the Village Council Meeting 3/19/2019 SUBJECT: SUBMITTED BY: Authorization of a contract for Amazon Business procurement Judy Buttny services Finance Director SYNOPSIS A motion is requested to authorize the execution of a contract for Amazon Business procurement services through the U.S. Communities Government Purchasing Alliance. STRATEGIC PLAN ALIGNMENT The goals for 2017-2019 includes Steward of Financial Sustainability, and Exceptional, Continual Innovation. FISCAL IMPACT There is no cost to utilize Amazon Business procurement services through the U.S. Communities Government Purchasing Alliance. RECOMMENDATION Approval on the March 19, 2019 Consent Agenda. BACKGROUND U.S. Communities Government Purchasing Alliance is the largest public sector cooperative purchasing organization in the nation. All contracts are awarded by a governmental entity utilizing industry best practices, processes and procedures. The Village of Downers Grove has been a member of the U.S. Communities Government Purchasing Alliance since 2008. Through cooperative purchasing, the Village is able to take advantage of economy of scale and reduce the cost of goods and services. U.S. Communities has partnered with Amazon Services to offer local government agencies the ability to utilize Amazon Business for procurement services at no cost to U.S. Communities members. Amazon Business offers business-only prices on millions of products in a competitive digital market place and a multi-level approval workflow. Staff can efficiently find quotes and purchase products for the best possible price, and the multi-level approval workflow ensures this service is compliant with the Village’s competitive process for purchases under $7,000. -
The Complete Guide to Social Media from the Social Media Guys
The Complete Guide to Social Media From The Social Media Guys PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Mon, 08 Nov 2010 19:01:07 UTC Contents Articles Social media 1 Social web 6 Social media measurement 8 Social media marketing 9 Social media optimization 11 Social network service 12 Digg 24 Facebook 33 LinkedIn 48 MySpace 52 Newsvine 70 Reddit 74 StumbleUpon 80 Twitter 84 YouTube 98 XING 112 References Article Sources and Contributors 115 Image Sources, Licenses and Contributors 123 Article Licenses License 125 Social media 1 Social media Social media are media for social interaction, using highly accessible and scalable publishing techniques. Social media uses web-based technologies to turn communication into interactive dialogues. Andreas Kaplan and Michael Haenlein define social media as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, which allows the creation and exchange of user-generated content."[1] Businesses also refer to social media as consumer-generated media (CGM). Social media utilization is believed to be a driving force in defining the current time period as the Attention Age. A common thread running through all definitions of social media is a blending of technology and social interaction for the co-creation of value. Distinction from industrial media People gain information, education, news, etc., by electronic media and print media. Social media are distinct from industrial or traditional media, such as newspapers, television, and film. They are relatively inexpensive and accessible to enable anyone (even private individuals) to publish or access information, compared to industrial media, which generally require significant resources to publish information. -
Amazon Elasticache Deep Dive Powering Modern Applications with Low Latency and High Throughput
Amazon ElastiCache Deep Dive Powering modern applications with low latency and high throughput Michael Labib Sr. Manager, Non-Relational Databases © 2020, Amazon Web Services, Inc. or its Affiliates. Agenda • Introduction to Amazon ElastiCache • Redis Topologies & Features • ElastiCache Use Cases • Monitoring, Sizing & Best Practices © 2020, Amazon Web Services, Inc. or its Affiliates. Introduction to Amazon ElastiCache © 2020, Amazon Web Services, Inc. or its Affiliates. Purpose-built databases © 2020, Amazon Web Services, Inc. or its Affiliates. Purpose-built databases © 2020, Amazon Web Services, Inc. or its Affiliates. Modern real-time applications require Performance, Scale & Availability Users 1M+ Data volume Terabytes—petabytes Locality Global Performance Microsecond latency Request rate Millions per second Access Mobile, IoT, devices Scale Up-out-in E-Commerce Media Social Online Shared economy Economics Pay-as-you-go streaming media gaming Developer access Open API © 2020, Amazon Web Services, Inc. or its Affiliates. Amazon ElastiCache – Fully Managed Service Redis & Extreme Secure Easily scales to Memcached compatible performance and reliable massive workloads Fully compatible with In-memory data store Network isolation, encryption Scale writes and open source Redis and cache for microsecond at rest/transit, HIPAA, PCI, reads with sharding and Memcached response times FedRAMP, multi AZ, and and replicas automatic failover © 2020, Amazon Web Services, Inc. or its Affiliates. What is Redis? Initially released in 2009, Redis provides: • Complex data structures: Strings, Lists, Sets, Sorted Sets, Hash Maps, HyperLogLog, Geospatial, and Streams • High-availability through replication • Scalability through online sharding • Persistence via snapshot / restore • Multi-key atomic operations A high-speed, in-memory, non-Relational data store. • LUA scripting Customers love that Redis is easy to use. -
Amazon Mechanical Turk Developer Guide API Version 2017-01-17 Amazon Mechanical Turk Developer Guide
Amazon Mechanical Turk Developer Guide API Version 2017-01-17 Amazon Mechanical Turk Developer Guide Amazon Mechanical Turk: Developer Guide Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Amazon Mechanical Turk Developer Guide Table of Contents What is Amazon Mechanical Turk? ........................................................................................................ 1 Mechanical Turk marketplace ....................................................................................................... 1 Marketplace rules ............................................................................................................... 2 The sandbox marketplace .................................................................................................... 2 Tasks that work well on Mechanical Turk ...................................................................................... 3 Tasks can be completed within a web browser ....................................................................... 3 Work can be broken into distinct, bite-sized tasks ................................................................. -
Analytics Lens AWS Well-Architected Framework Analytics Lens AWS Well-Architected Framework
Analytics Lens AWS Well-Architected Framework Analytics Lens AWS Well-Architected Framework Analytics Lens: AWS Well-Architected Framework Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Analytics Lens AWS Well-Architected Framework Table of Contents Abstract ............................................................................................................................................ 1 Abstract .................................................................................................................................... 1 Introduction ...................................................................................................................................... 2 Definitions ................................................................................................................................. 2 Data Ingestion Layer ........................................................................................................... 2 Data Access and Security Layer ............................................................................................ 3 Catalog and Search Layer ................................................................................................... -
Distributed Hash Tables Chord and Dynamo (Lecture 19, Cs262a)
Distributed Hash Tables Chord and Dynamo (Lecture 19, cs262a) Ion Stoica, UC Berkeley October 31, 2016 Today’s Papers Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications, Ion Stoica, Robert Morris, David Karger, M. Frans Kaashoek, Hari Balakrishnan, SIGCOMM’02 (https://pdos.csail.mit.edu/papers/chord:sigcomm01/chord_sigcomm.pdf) Dynamo: Amazon's Highly Available Key-value Store, Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, Gunavardhan Kakulapati, Avinash Lakshman, Alex Pilchin, Swaminathan, Sivasubramanian, Peter Vosshall, and Werner Vogels, SOSP’07 (www.allthingsdistributed.com/files/amazon-dynamo-sosp2007.pdf) Key Value Storage Interface – put(key, value); // insert/write “value” associated with “key” – value = get(key); // get/read data associated with “key” Abstraction used to implement – File systems: value content à block – Sometimes as a simpler but more scalable “database” Can handle large volumes of data, e.g., PBs – Need to distribute data over hundreds, even thousands of machines Key Values: Examples Amazon: – Key: customerID – Value: customer profile (e.g., buying history, credit card, ..) Facebook, Twitter: – Key: UserID – Value: user profile (e.g., posting history, photos, friends, …) iCloud/iTunes: – Key: Movie/song name – Value: Movie, Song Distributed file systems – Key: Block ID – Value: Block System Examples Google File System, Hadoop Dist. File Systems (HDFS) Amazon – Dynamo: internal key value store used to power Amazon.com (shopping cart) – Simple Storage System (S3) BigTable/Hbase: distributed, -
'Skip the Straw'
Today’s weather: High 88 Low 78 A shower & CHARLOTTE SUN thunderstorm GUNMAN IN TRADER JOE’S STANDOFF LOOKING AT MURDER CHARGE Pulitzer Prize winner A gunman who took dozens of people hostage at a Trader Joe’s store in Los Angeles was booked Sunday on suspicion of murder, after an employee 2016 was killed during the man’s shootout with police. See The News Wire Monday, July 23, 2018 VOL. 126 | NO. 204 www.yoursun.com AMERICA’S BEST COMMUNITY DAILY $1.50 AN EDITION OF THE SUN Program Report: Residents feeling aims to help inmates good, getting heavier By BETSY CALVERT them the Healthy Community based on an annual telephone period, the rate declined from STAFF WRITER Champion Recognition survey by the U.S. Centers for 82.9 to 80.5 percent. post-jail Award. Disease Control. Pepe credited county Charlotte County residents “I’m pleased to inform you According to that survey programs at the commission By ANNE EASKER are feeling better these days, we are moving the needle,” he for this county, 85 percent of meeting. STAFF WRITER even as they exercise less and said. adults said they were in good “The built-in environment weigh more. Pepe drew his conclusions to excellent health in 2016 — that you put in place is start- A new program at the Charlotte Those are some of the from the state Department of the most recent results avail- ing to pay off,” he said. County Jail aims to reduce recid- indicators that the county’s Health database that able. That’s an improvement That environment includes ivism by helping inmates learn interim health director, compares counties from 2013 when the rate was newly constructed sidewalks, to better navigate the world after Joseph Pepe, shared with and shows trends 80.9 percent, and 2010 when improved parks, plans for incarceration. -
Amazon Dynamodb Deep Dive: Advanced Design Patterns
Amazon DynamoDB deep dive: Advanced design patterns © 2020, Amazon Web Services, Inc. or its Affiliates. 自己紹介 成田 俊 id:oranie 経歴 • 前職のWeb系会社でインフラエンジニアを担当、主にMySQLや Cassandra運用などに携わる AWSJでの担当 • NoSQLサービス、DynamoDBをメインに技術支援を担当 © 2020, Amazon Web Services, Inc. or its Affiliates. Agenda • Overview of Amazon DynamoDB • Scaling NoSQL • NoSQL data modeling • 正規化と非正規化 • デザインパターン • 複合key, 階層的構造のデータ, リレーショナルなデータの表現 • 実際のアプリケーションにおけるモデリング © 2020, Amazon Web Services, Inc. or its Affiliates. Amazon DynamoDB あらゆる規模に対応する高速で柔軟なkey-value データベースサービス Performance Serverless architecture Enterprise Global replication at scale security あらゆる規模で一貫した1桁 ハードウェアのプロビジョニン すべてのデータを暗号化 複数の AWS リージョン間で ミリ秒の応答時間。事実上無 グ、ソフトウェアのパッチ適用、 AWS IAMとの完全統合によ 簡単にテーブルをレプリ 制限のスループットでアプリ アップグレードなし、自動ス り、堅牢なセキュリティを ケートすることで、ローカ ケーションを構築 ケールアップまたはスケールダ 実現 ルデータにすばやくアクセ ウン、データの継続的なバック スできるグローバルアプリ アップ ケーションを構築可能 © 2020, Amazon Web Services, Inc. or its Affiliates. © 2020, Amazon Web Services, Inc. or its Affiliates. メンテナンスフリー もしこれらを管理するコストが無ければ他に何が出来るか? セキュリティ 可用性 OSパッチ適用 高可用性を実現する設計 DBパッチ適用 モニタリング アクセスコントロール クロスリージョンレプリケーション 監査 性能 暗号化 パフォーマンスチューニング コンプライアンス対応 インデックス設計、作成 耐久性 In-memory上でキャッシュ維持 サーバ, ラック, データセンタ維持 拡張性 HW障害に伴うデータコピー キャパシティプランニング バックアップ・リストア ホスト構築、投入作業 障害ホストの修復、撤去作業 © 2020, Amazon Web Services, Inc. or its Affiliates. Table Table GSI1PK GSI2PK GSI3PK Items GSI1PK Attributes GSI1PK GSI2PK Partition Sort All items for key ==, <, >, >=, <= key key “begins with” “between” “contains” “in” 必須 オプション sorted results Key-value アクセスパターン 1:Nの関係性を表現 counts を実現 データの分布を決定 豊富なクエリでの条件指定が可能 -
October 24, 2013—Amazon.Com, Inc
AMAZON.COM ANNOUNCES THIRD QUARTER SALES UP 24% TO $17.09 BILLION SEATTLE—(BUSINESS WIRE)—October 24, 2013—Amazon.com, Inc. (NASDAQ: AMZN) today announced financial results for its third quarter ended September 30, 2013. Operating cash flow increased 48% to $4.98 billion for the trailing twelve months, compared with $3.37 billion for the trailing twelve months ended September 30, 2012. Free cash flow decreased 63% to $388 million for the trailing twelve months, compared with $1.06 billion for the trailing twelve months ended September 30, 2012. Free cash flow for the trailing twelve months ended September 30, 2013 includes fourth quarter 2012 cash outflows for purchases of corporate office space and property in Seattle, Washington, of $1.4 billion. Common shares outstanding plus shares underlying stock-based awards totaled 475 million on September 30, 2013, compared with 469 million one year ago. Net sales increased 24% to $17.09 billion in the third quarter, compared with $13.81 billion in third quarter 2012. Excluding the $332 million unfavorable impact from year-over-year changes in foreign exchange rates throughout the quarter, net sales grew 26% compared with third quarter 2012. Operating loss was $25 million in the third quarter, compared with an operating loss of $28 million in third quarter 2012. The unfavorable impact from year-over-year changes in foreign exchange rates throughout the quarter on operating loss was $7 million. Net loss was $41 million in the third quarter, or $0.09 per diluted share, compared with a net loss of $274 million, or $0.60 per diluted share, in third quarter 2012.