Announcement: ELB stickiness updates to support Feb 2020 Chromium CORs changes
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Spark Streamingã‹ã‚‰Amazon Kinesis Analyticsã¸ç§»è¡Œã™ã‚‹è©± - Gunosyデータ分æžãƒ–ãƒã‚°
ã¯ã˜ã‚ã« ã“ã‚“ã«ã¡ã¯ã€ãƒ‡ãƒ¼ã‚¿åˆ†æžéƒ¨ã®æ£®æœ¬ã§ã™ã€‚主ãªæ¥å‹™ã¯è¨˜äº‹é…信アルゴリズムã®æ”¹å–„ã¨ãƒã‚°åŸºç›¤ã®æ•´å‚™ã§ã™ã€‚ Gunosyã§ã¯ã€ãƒ¦ãƒ¼ã‚¶ãƒ¼ã¸ã‚ˆã‚Šè‰¯ã„記事をæä¾›ã™ã‚‹ãŸã‚ã«ã‚¢ã‚¯ã‚»ã‚¹ãƒã‚°ã‚’ストリーム処ç†ã—ã€é›†è¨ˆçµæžœã‚’記事é…信アルゴリズムã«æ´»ç”¨ã—ã¦ã„ã¾ã™ã€‚ ストリームãƒã‚°åŸºç›¤ã«ã¯Spark Streamingを利用ã—ã¦ã„ã¾ã™ãŒã€ç¾åœ¨Kinesis Analyticsã¸ç§»è¡Œä¸ã§ã™ã€‚ ã“ã®è¨˜äº‹ã§ã¯Kinesis Analyticsã¸ç§»è¡Œã™ã‚‹ç†ç”±ã‚„é‹ç”¨ä¸Šã®Tipsç‰ã«ã¤ã„ã¦ãŠè©±ã—ã¾ã™ã€‚ Spark Streamingを利用ã—ãŸã‚¹ãƒˆãƒªãƒ¼ãƒ ãƒã‚°åŸºç›¤æ§‹æˆ ç¾åœ¨ã®ã‚¹ãƒˆãƒªãƒ¼ãƒ ãƒã‚°åŸºç›¤ã¯Spark Streamingã§é›†è¨ˆã‚’è¡Œã„ã€çµæžœã‚’RDSã«ä¿å˜ã—ã¦ã„ã¾ã™ã€‚ ãªãœSpark Streamingã‹ã‚‰Kinesis Analyticsã¸ç§»è¡Œã™ã‚‹ã®ã‹ サーãƒãƒ¼ã‚³ã‚¹ãƒˆã¨é‹ç”¨ã‚³ã‚¹ãƒˆã®å‰Šæ¸›ã‚’目的ã¨ã—ã¦ã„ã¾ã™ã€‚ サーãƒãƒ¼ã‚³ã‚¹ãƒˆã«ã¤ã„
Apache Kafka vs Amazon Kinesis to Build a High...
Apache Kafka vs Amazon Kinesis to Build a High Performance Distributed SystemAt Keen IO, we’ve been running Apache Kafka in a pretty big production capacity for years, and are extremely happy with the technology. We also do some things with Amazon Kinesis and are excited to continue to explore it. Apache Kafka vs Amazon Kinesis For any given problem, if you’ve narrowed it down to choosing between
Amazon Kinesis Streamsã®ãƒªã‚·ãƒ£ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ãŒAPI一発ã§è¡Œãˆã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—㟠| DevelopersIO
Amazon Kinesis Streamer ã®çš†æ§˜ã“ã‚“ã«ã¡ã¯ã€‚ リシャーディングã®ã‚ã¾ã‚Šã®é¢å€’ãã•ã•ã‹ã‚‰ã€ãƒ”ークã«åˆã‚ã›ã¦ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã‚’固定ã—ã¦ã‚¹ãƒˆãƒªãƒ¼ãƒ é‹ç”¨ã—ãŸã‚Šã€ã‚·ãƒ£ãƒ¼ãƒ‰æ•°å¤‰æ›´ã®éš›ã¯åŒã˜åå‰ã§ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã ã‘変ãˆã¦ä½œã‚Šç›´ã—ã¦ããŸã¨ã„ã†æ–¹ãŒå¤šã„ã®ã§ã¯ãªã„ã§ã—ょã†ã‹ã€‚ 2016/11/16ã®ã‚µãƒ¼ãƒ“スアップデートã«ã‚ˆã‚Šã€ã‚¹ãƒˆãƒªãƒ¼ãƒ ã®ãƒªã‚·ãƒ£ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ãŒ API 一発ã§å®Ÿè¡Œå‡ºæ¥ã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—ãŸã€‚ トラフィックã«åˆã‚ã›ã¦ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã‚’ダイナミックã«ã‚ªãƒ¼ãƒˆã‚¹ã‚±ãƒ¼ãƒ«ã•ã›ã‚‹ãªã©ã€å¤¢åºƒãŒã‚‹ API ã§ã™ã€‚ 早速試ã—ã¦ã¿ã¾ã—ãŸã€‚ 旧方å¼ã®ãƒªã‚·ãƒ£ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°:SplitShard API ç·¨ Amazon Kinesis Streams ã®ã‚¹ãƒˆãƒªãƒ¼ãƒ ã¯ã‚·ãƒ£ãƒ¼ãƒ‰ã‚’æŸããŸã‚‚ã®ã§ã‚ã‚Šã€ã‚·ãƒ£ãƒ¼ãƒ‰1本辺りã®æ€§èƒ½ä¸Šé™ãŒæ±ºã¾ã£ã¦ã„ã‚‹ãŸã‚ã€ã‚¹ãƒˆãƒªãƒ¼ãƒ ã®ã‚ャパシティを増やã—ãŸã‘ã‚Œã°ã€ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã‚’増やã™ã“ã¨ã«ãªã‚Šã¾ã™ã€‚ AWS B
［レãƒãƒ¼ãƒˆï¼½ã‚µãƒ¼ãƒãƒ¬ã‚¹ã‚¢ãƒ¼ã‚テクãƒãƒ£ã§å®Ÿç¾ã—ãŸã€ŽM-1グランプリ2015ã€æ•—者復活戦投票システム#AWSRoadshow | DevelopersIO
［レãƒãƒ¼ãƒˆï¼½ã‚µãƒ¼ãƒãƒ¬ã‚¹ã‚¢ãƒ¼ã‚テクãƒãƒ£ã§å®Ÿç¾ã—ãŸã€ŽM-1グランプリ2015ã€æ•—者復活戦投票システム#AWSRoadshow ã¯ã˜ã‚ã« ã“ã‚“ã«ã¡ã¯ã€ä¸å±±ã§ã™ã€‚ 2016å¹´11月22æ—¥(ç«)ãƒãƒ¼ãƒ“スホールã«ã¦è¡Œã‚ã‚ŒãŸAWS Cloud Roadshow 2016 大阪ã«å‚åŠ ã—ã¦ãã¾ã—ãŸã€‚本エントリã§ã¯15:00ã‹ã‚‰å°Žå…¥äº‹ä¾‹ãƒˆãƒ©ãƒƒã‚¯ã§ç™ºè¡¨ã•ã‚ŒãŸã‚µãƒ¼ãƒãƒ¬ã‚¹ã‚¢ãƒ¼ã‚テクãƒãƒ£ã§å®Ÿç¾ã—ãŸã€ŽM-1グランプリ2015ã€æ•—者復活戦投票システムã¨ã„ã†ã‚»ãƒƒã‚·ãƒ§ãƒ³ã®å†…容ã«ã¤ã„ã¦ãƒ¬ãƒãƒ¼ãƒˆã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚ 資料 ※ 資料ãŒã‚¢ãƒƒãƒ—ã•ã‚Œæ¬¡ç¬¬åæ˜ ã„ãŸã—ã¾ã™ã€‚ スピーカー å°å— 英å¸ã•ã¾ æœæ—¥æ”¾é€æ ªå¼ä¼šç¤¾ 技術局 開発部 サーãƒã‚µã‚¤ãƒ‰ã‹ã‚‰ã‚¢ãƒ—リ開発ã¾ã§å¹…広ã担当 アジェンダ æœæ—¥æ”¾é€ã«ã¤ã„㦠M-1グランプリ敗者復活戦ã«ã¤ã„㦠開発当時ã®çŠ¶æ³ システムã®æ¦‚è¦ ã‚µãƒ¼ãƒãƒ¼ãƒ¬ã‚¹ã‚¢ãƒ¼ã‚テクãƒãƒ£ã‚’採用ã—ãŸç†ç”± Kinesis/Kines
Kafkaã¨AWS Kinesisã®æ¯”較
This document compares Apache Kafka and AWS Kinesis for message streaming. It outlines that Kafka is an open source publish-subscribe messaging system designed as a distributed commit log, while Kinesis provides streaming data services. It also notes some key differences like Kafka typically handling over 8000 messages/second while Kinesis can handle under 100 messages/second.Read less
Amazon Kinesis Streamsã®ã‚µãƒ¼ãƒ“ス制é™ã«ã¤ã„㦠| DevelopersIO
Amazon Kinesis Streamsを構築・é‹ç”¨ã™ã‚‹ã¨ã€æ€ã„ã‚‚ã‹ã‘ãªã„サービス制é™ã«éé‡ã™ã‚‹ã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ 本日ã¯2016å¹´05月時点ã§ã®ã‚µãƒ¼ãƒ“ス制é™ã«ã¤ã„ã¦ã”紹介ã—ã¾ã™ã€‚ ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ä¸Šé™ æ±äº¬ãƒªãƒ¼ã‚¸ãƒ§ãƒ³ã®å ´åˆã€ãƒªãƒ¼ã‚¸ãƒ§ãƒ³ã‚ãŸã‚Šã®ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã®ãƒ‡ãƒ•ã‚©ãƒ«ãƒˆä¸Šé™å€¤ã¯25ã§ã™ã€‚ ã“ã®å€¤ã¯ã‚¹ãƒˆãƒªãƒ¼ãƒ ã”ã¨ã®ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ã§ã¯ãªãã€ãƒªãƒ¼ã‚¸ãƒ§ãƒ³ã”ã¨ã®ã‚·ãƒ£ãƒ¼ãƒ‰ç·æ•°ã§ã™ã€‚ 例ãˆã°ã€ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ä¸Šé™25ã®ãƒªãƒ¼ã‚¸ãƒ§ãƒ³ã§ã€ã‚·ãƒ£ãƒ¼ãƒ‰æ•°10ã®ã‚¹ãƒˆãƒªãƒ¼ãƒ ã‚’1個作æˆã—ã¦ã„ã‚‹å ´åˆã€æ–°è¦ã‚¹ãƒˆãƒªãƒ¼ãƒ ã®ã‚·ãƒ£ãƒ¼ãƒ‰æ•°ä¸Šé™ã¯25−10ï¼15ã§ã™ã€‚ ã¾ãŸã€ACTIVE(=データを新è¦ã«å—ã‘付ã‘ã‚‹)シャードã ã‘ãŒä¸Šé™å¯¾è±¡ã¨ã—ã¦ã‚«ã‚¦ãƒ³ãƒˆã•ã‚Œã¾ã™ã€‚ 例ãˆã°ã€ã‚·ãƒ£ãƒ¼ãƒ‰æ•°10ã®ã‚¹ãƒˆãƒªãƒ¼ãƒ をシャード分割ã—ã¦ã‚·ãƒ£ãƒ¼ãƒ‰æ•°20ã«ã™ã‚‹å ´åˆã€ ACTIVE シャード : 20 CLOSED シャード : 10 ã¨ãªã‚ŠACTIVE/CLOSEDãªã‚·ãƒ£ãƒ¼ãƒ‰ç·æ•°
Kinesis vs-kafka-and-kafka-deep-dive
This document provides a summary of Amazon Kinesis and Apache Kafka, two platforms for processing real-time streaming data at large scale. It describes key features of each system such as durability, interfaces, processing options, and deployment. Kinesis is a fully managed cloud service that provides high durability for data across AWS availability zones. Kafka is an open source platform that off
AWS Black Belt Tech シリーズ 2015 - Amazon Kinesis
AWS Black Belt Tech Webinar 2015 Amazon Kinesis 次回ã®Webinarã¯ã€ä¸‹è¨˜ã‚ˆã‚Šã”確èªãã ã•ã„。 http://aws.amazon.com/jp/about-aws/events/#webinar ★AWS Black Belt Tech Webinarã¨ã¯ AWSã®ã‚½ãƒªãƒ¥ãƒ¼ã‚·ãƒ§ãƒ³ã‚¢ãƒ¼ã‚テクトã€TechメンãƒãŒAWSã®ãƒ—ãƒãƒ€ã‚¯ãƒˆ/ã‚½ãƒªãƒ¥ãƒ¼ã‚·ãƒ§ãƒ³ã‚’æ·±å €ã‚Šã—ã¦è§£èª¬ã—ã€å‚åŠ ã•ã‚Œã¦ã„る皆ã•ã¾ã‹ã‚‰ã®è³ªå•ã«ãŠç”ãˆã™ã‚‹ç„¡æ–™ã®Webinar(Webセミナー）ã§ã™ã€‚ 毎週水曜日(ç¥æ—¥ãªã©ã‚’除ã)ã€æ—¥æœ¬æ™‚é–“ã®18:00ã‹ã‚‰ç´„1時間ã«ã‚ãŸã£ã¦ãŠé€ã‚Šã—ã¦ã„ã¾ã™ã€‚Read less
API Gateway / Lambda / Kinesis を使ã£ãŸã‚¹ãƒˆãƒªãƒ¼ãƒŸãƒ³ã‚°ãªãƒãƒƒãƒå®Ÿè¡ŒåŸºç›¤ã®å®Ÿè£…
AWSモãƒã‚¤ãƒ«/IoTサービス徹底攻略ï¼ï¼ http://classmethod.connpass.com/event/22060/ 2015å¹´11月21日（土）
S3ã€Kinesis/DynamoDB Streamsã§ã®Lambdaãƒªãƒˆãƒ©ã‚¤å‡¦ç† - Qiita
ã“ã¡ã‚‰ã®è¨˜äº‹ã®å†…容ã¨ç¾åœ¨ã®ãƒªãƒˆãƒ©ã‚¤å‹•ä½œã¯ç•°ãªã£ã¦ã„ã¾ã™ã€‚ 詳細ã¯ä¸‹è¨˜ã®å…¬å¼ãƒ‰ã‚ュメントをå‚ç…§ã—ã¦ãã ã•ã„。 エラー時ã®ãƒªãƒˆãƒ©ã‚¤ - AWS Lambdaå…¬å¼ãƒ‰ã‚ュメント AWS Lambda ã®ã‚¤ãƒ™ãƒ³ãƒˆã‚½ãƒ¼ã‚¹ã”ã¨ã®å‘¼ã³å‡ºã—タイプ - Qiita æ¦‚è¦ Lambda ファンクション内㧠context.done() ã®ç¬¬1引数㫠null 以外ã®å€¤ã‚’渡ã™ã¨å‡¦ç†å¤±æ•—ã¨ãªã‚Šãƒªãƒˆãƒ©ã‚¤ãŒç™ºç”Ÿã™ã‚‹ã€‚ å„イベントソースã«ã‚ˆã‚‹ãƒªãƒˆãƒ©ã‚¤å‡¦ç†ã‚’調ã¹ã¦ã¿ãŸã€‚ 処ç†å¤±æ•—時ã«ã¯ 3 分後ã«å†åº¦ãƒ•ã‚¡ãƒ³ã‚¯ã‚·ãƒ§ãƒ³ãŒå‘¼ã³å‡ºã•ã‚Œã‚‹ã€‚ context.invokeid ã¯å‰å›žã¨åŒã˜å€¤ã«ãªã‚‹ã€‚ リトライをå«ã‚ã¦æœ€å¤§ 3 回実行ã•ã‚Œã‚‹ã€‚ ETagã®æ¯”較 US Standard ã¯å…¨ã¦ã®æ“作ã§çµæžœæ•´åˆæ€§ã€ãれ以外ã®ãƒªãƒ¼ã‚¸ãƒ§ãƒ³ã§ã¯æ–°è¦ä½œæˆä»¥å¤–ã®æ“作ã§çµæžœæ•´åˆæ€§ã‚’ã‚‚ã£ã¦å‹•ä½œã™ã‚‹ã€‚ Lambda ã«é™ã‚‰ãš S3 ã®ã‚ªãƒ–ジェクトをå–å¾—ã™ã‚‹å ´
CloudWatch Logs Subscriptionsを利用ã—ãŸZabbixã¸ã®ãƒã‚°è»¢é€ï½œDevelopers.IO
ã¯ã˜ã‚㫠先日ã€CloudWatch Logs Subscriptionsã¨ã„ã†æ–°æ©Ÿèƒ½ã®ç™ºè¡¨ãŒã‚ã‚Šã¾ã—ãŸã€‚ CloudWatch Logsã«è¨˜éŒ²ã•ã‚ŒãŸãƒã‚°ã‚¤ãƒ™ãƒ³ãƒˆã‚’リアルタイムã«Kinesisã¸æŠ•å…¥ã™ã‚‹æ©Ÿèƒ½ã§ã™ã€‚ ã“ã‚Œã¾ã§ã¯ã€ãƒã‚°ã‚¤ãƒ™ãƒ³ãƒˆã‚’å–å¾—ã™ã‚‹å ´åˆã€CloudWatch Logsã®GetLogEvents APIã«ã‚¢ã‚¯ã‚»ã‚¹ã—一括ã§ãƒã‚°ã‚’å–å¾—ã™ã‚‹ã—ã‹ã‚ã‚Šã¾ã›ã‚“ã§ã—ãŸã€‚ ãã—ã¦ã€ã“ã®GetLogEvents APIã«ã¯1アカウントã‚ãŸã‚Šç§’é–“10リクエストã¾ã§(上é™ç·©å’Œå¯)ã¨ã„ã†åˆ¶é™ãŒã‚ã‚Šã€å¤šãã®ç¨®é¡žã®ãƒã‚°ã‚’常ã«å–å¾—ã—続ã‘ãŸã„å ´åˆã¯æ³¨æ„ãŒå¿…è¦ã§ã—ãŸã€‚ 今回ã€CloudWatch Logsã‹ã‚‰Kinesisã«ãƒã‚°ã‚¤ãƒ™ãƒ³ãƒˆã‚’投入å¯èƒ½ã«ãªã£ãŸã“ã¨ã«ã‚ˆã‚Šã€Kinesisストリームをãƒãƒ¼ãƒªãƒ³ã‚°ã™ã‚‹ã ã‘ã§å¸¸ã«æœ€æ–°ã®ãƒ‡ãƒ¼ã‚¿ã‚’å–å¾—ã§ãるよã†ã«ãªã‚Šã¾ã—ãŸã€‚ ã¾ãŸã€Kinesisã¯Lambdaã®ã‚¤ãƒ™ãƒ³ãƒˆã‚½ãƒ¼ã‚¹ã¨
JAWS-UG CLI #22 Amazon Kinesis
4. AWS CLI ç›´è¿‘ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚¢ãƒƒãƒ— • 1.7.35 2015/06/18 – Feature: aws ecs Add support for DeregisterTaskDefintion and environment variable overrides. • 1.7.34 2015/06/12 – Feature: nstallation Fix bundled installer when running python 2.6 (issue 1381) – Feature: Installation Fix minimum required version of pip to install the AWS CLI using python2.6 (issue 1383) • 1.7.33 2015/06/12 – Feature: aws autoscaling A
Kinesisã‹S3ã‹
Kinesisを触ã£ã¦ã¯ã¿ãŸã‚‚ã®ã®ã€ç‰¹åˆ¥ã€Œã“ã‚Œã¯ä½¿ã„ã‚„ã™ã„ï¼ã€ã¨ã„ã†å°è±¡ã§ã¯ãªã‹ã£ãŸã€‚ Kinesisã®ç”¨é€”ã¯è¦ã™ã‚‹ã« AWSã«ã‚¬ãƒ³ã‚¬ãƒ³ãƒ‡ãƒ¼ã‚¿ã‚’é€ã‚‹ AWSå´ã§ã¯ã€é€ã‚‰ã‚Œã¦ããŸãƒ‡ãƒ¼ã‚¿ã‚’片ã£ç«¯ã‹ã‚‰å‡¦ç†ã™ã‚‹ AWSå´ã«ç€ã„ãŸãƒ‡ãƒ¼ã‚¿ã¯å‡¦ç†ã—よã†ãŒã—ã¾ã„ãŒä¸€å®šæœŸé–“(ç¾åœ¨ã¯24時間)ã§æ¶ˆãˆã‚‹ ã¨ã„ã†ã‚‚ã®ã€‚ ã—ã‹ã—ã€AWSã¸ã®é€ä¿¡ã¯å˜ç´”ã«HTTPSã®POSTリクエストã§ã‚ã‚Šã€ã•ã‚‰ã«Base64エンコードã•ã‚Œã¦ã„ã‚‹ã¨ã„ã†ã“ã¨ã§ç‰¹ã«åŠ¹çŽ‡çš„ãªæ–¹æ³•ã§ã¯ãªã„。むã—ã‚効率をã¾ã£ãŸã考慮ã—ã¦ãŠã‚‰ãšã€ã‚·ãƒ³ãƒ—ルã•ã€æ‰±ã„ã‚„ã™ã•ã«å¾¹ã—ã¦ã„る。 HTTPSã®POSTリクエストã§ã‚ã‚‹ã«ã‚‚é–¢ã‚らãšã‚µã‚¤ã‚ºä¸Šé™(ç¾åœ¨ã¯50KB)ãŒãã¤ã„ã®ã§ã€å°ã•ãªãƒ‡ãƒ¼ã‚¿ã‚’é€ã‚‹ç”¨é€”ã«é™å®šã•ã‚Œã‚‹ã€‚ 個人的ã«æ•°å～百å°ç¨‹åº¦ã®ã‚µãƒ¼ãƒã‹ã‚‰AWSã¸ã®ãƒã‚°ã®é›†ç´„(Log Aggregation)を計画ã—ã¦ã„ã‚‹ã®ã ãŒã€Kinesisã®ç”¨é€”ã«ã´ã£ãŸã‚Šã‹ï¼Ÿã¨è€ƒãˆãŸä¸€æ–¹
Amazon Kinesisã®ãƒ¬ã‚³ãƒ¼ãƒ‰ã«ã‚¿ã‚¤ãƒ スタンプ属性ãŒè¿½åŠ ã•ã‚Œã¾ã—㟠| DevelopersIO
ã©ã‚‚ã€å¤§ç€§ã§ã™ã€‚ 昨日ã€Amazon Kinesisã®ã‚¢ãƒƒãƒ—デートãŒã‚りレコードã«ã‚¿ã‚¤ãƒ スタンプ属性ãŒè¿½åŠ ã•ã‚Œã¾ã—ãŸã€‚ Amazon Kinesis Server-side Timestamp レコードã®ApproximateArrivalTimestamp属性ã«KinesisãŒãƒ¬ã‚³ãƒ¼ãƒ‰ã‚’å—ä¿¡ã—ãŸãŠãŠã‚ˆãã®æ™‚刻ãŒUNIXタイムスタンプã®å½¢å¼ã§å«ã¾ã‚Œã¾ã™ã€‚AWS CLIã§GetRecordsをコールã—ã¦ã¿ã¾ã—ãŸã€‚ $ aws kinesis get-shard-iterator --stream-name OtakiTest --shard-id shardId-000000000000 --shard-iterator-type TRIM_HORIZON XXXXXXXXXX $ aws kinesis get-records --shard-iterator XXXXXXXXXX { "
Streaming Petabytes of Data in Realtime with Kinesis - NextRoll
AdRoll’s real-time data pipeline drives many systems crucial to our business. These systems inform the decisions made by our real-time bidding infrastructure in response to the tens of billions of daily requests we receive from ad exchanges. They also refresh our predictive models, guard against overspend, and deliver up to the minute campaign metrics through our dashboard. To function properly th
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AWS News Blog Amazon Kinesis Update – Simplified Capture of Streaming Data Amazon Kinesis is a managed service designed to handle real-time streaming of big data. It can accept any amount of data, from any number of sources, scaling up and down as needed (see my introductory post for more information on Kinesis). Developers can use the Kinesis Client Library (KCL) to simplify the implementation of
Amazon Kinesis: Real-time Streaming Big data Processing Applications (BDT311) | AWS re:Invent 2013
Amazon Kinesis: Real-time Streaming Big data Processing Applications (BDT311) | AWS re:Invent 2013 "This presentation will introduce Kinesis, the new AWS service for real-time streaming big data ingestion and processing. We’ll provide an overview of the key scenarios and business use cases suitable for real-time processing, and how Kinesis can help customers shift from a traditional batch-oriented
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amazon-kinesis-producer/aggregation-format.md at master · awslabs/amazon-kinesis-producer
Amazon Kinesis Data Streams
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