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2023å¹´5月ã€Twitter（ç¾X）ãŒæä¾›ã™ã‚‹APIãŒçªå¦‚ã¨ã—ã¦æœ‰æ–™åŒ–ã—ã€2009å¹´ã‹ã‚‰å€‹äººã«ã‚ˆã‚Šé‹å–¶ã•ã‚Œã¦ããŸTwilogãŒã‚µãƒ¼ãƒ“スã®çµ‚了を発表ã—ã¾ã—ãŸã€‚ ãã“ã«æ‰‹ã‚’å·®ã—伸ã¹ã‚‹1ã¤ã®ä¼æ¥ãŒã‚ã‚Šã¾ã—ãŸã€‚ãã†ã€Twitter関連ä¼æ¥ã®Togetterã§ã™ã€‚ è¯éº—ãªè²·åŽã‚¨ãƒ”ソードã®è£å´ã§ã€Twilogã®çµ±åˆãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆãŒã‚¹ã‚¿ãƒ¼ãƒˆã—ã¾ã™ã€‚ Rubyã‹ã‚‰PHPã¸ã®ãƒ•ãƒ«ã‚¹ã‚¯ãƒ©ãƒƒãƒã§ã®ã‚³ãƒ¼ãƒ‰ç§»è¡Œ 15年間貯ã‚続ã‘ãŸãƒ†ãƒ©ãƒã‚¤ãƒˆç´šã®DBã®ç§»ç®¡ä½œæ¥ コストを抑ãˆã¦AWS環境ã¸ç§»ç®¡ã™ã‚‹ãŸã‚ã®è©¦è¡ŒéŒ¯èª¤ ãªã©ãªã©ã€1å¹´é–“ã«åŠã‚“ã 移行作æ¥ã®å…¨å®¹ã«ã¤ã„ã¦ãŠè©±ã—ã—ã¾ã™ã€‚ Twitter（X） : yositosi（@yositosi） https://x.com/yositosi アオヤマ ミント（@MintoAoyama） https://x.com/MintoAoyama
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OGPã‚’è¨å®šã—よã†ï¼SNSã§ã‚·ã‚§ã‚¢ã•ã‚Œã‚„ã™ã„è¨å®šæ–¹æ³•ã¨ã¯ï¼Ÿ
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Scala School - An introduction to Finagle
Finagle is Twitter’s RPC system. This blog post explains its motivations and core design tenets, the finagle README contains more detailed documentation. Finagle aims to make it easy to build robust clients and servers. REPL Futures: Sequential composition, Concurrent composition, Composition Example: Cached Rate Limit, Composition Example: Web Crawlers Service Client Example Server Example Filter
Quickstart — Finagle 24.2.0 documentation
Quickstart¶ In this section we’ll use Finagle to build a very simple HTTP server that is also an HTTP client — an HTTP proxy. We assume that you are familiar with Scala (if not, may we recommend Scala School). The entire example is available, together with a self-contained script to launch sbt, in the Finagle git repository: $ git clone https://github.com/twitter/finagle.git $ cd finagle/doc/src/s
MetricsDB: TimeSeries Database for storing metrics at Twitter
Infrastructure MetricsDB: TimeSeries Database for storing metrics at Twitter We covered Observability Engineering’s high level overview in blog posts earlier here and its follow up here. Our time series metric ingestion service grew to more than 5 billion metrics per minute, stores 1.5 petabytes of logical time series data, and handles 25K query requests per minute. Historically, we used Manhattan
ZooKeeper at Twitter
ZooKeeper is a critical piece of Twitter’s infrastructure, one that is fundamental to the operation of our services. Like many systems at Twitter, ZooKeeper operates at a very large scale, with hundreds of ZooKeeper instances active at a given time. How did we get there? It wasn’t overnight and it wasn’t always a smooth ride. This blog post describes how we use ZooKeeper, along with the challenges
Twitter ML Platform
Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. As part of its purpose of advancing AI for Twitter in an ethical way, Twitter Cortex is the core team responsible for facilitating machine learning endeavors within the company. With first-hand experience running machine learning models in production, Cortex seeks
The Infrastructure Behind Twitter: Scale
Overview of Twitter Fleet Twitter came of age when hardware from physical enterprise vendors ruled the data center. Since then we’ve continually engineered and refreshed our fleet to take advantage of the latest open standards in technology and hardware efficiency in order to deliver the best possible experience. Our current distribution of hardware is shown below: Network Traffic We started to mi
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snowflake ã¯ã€Twitter 社ãŒä½œæˆã—ãŸã€ãƒ¦ãƒ‹ãƒ¼ã‚¯ãªID生æˆã®ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚µãƒ¼ãƒ“スã§ã™ã€‚ã„ãã¤ã‹ã®ç°¡å˜ãªä¿è¨¼ã§é«˜ã„スケーラビリティを実ç¾ã—ã¦ã„ã¾ã™ã€‚Twitter 社ãŒã€MySQLã‹ã‚‰ Cassandra ã«ç§»è¡Œã™ã‚‹ã«ã‚ãŸã£ã¦ã€Cassandra ã«ã‚·ãƒ¼ã‚±ãƒ³ã‚·ãƒ£ãƒ«ãª id 生æˆã®ä»•çµ„ã¿ãŒç„¡ã‹ã£ãŸã“ã¨ã‹ã‚‰ä½œæˆã—ãŸãã†ã§ã™ã€‚ snowflake ã«ã¤ã„ã¦ã¯Twitter IDs, JSON and Snowflakeã«æ›¸ã„ã¦ã‚ã‚Šã¾ã™ã€‚ snowflake ã®ã‚³ãƒ¼ãƒ‰ã¯ã€Apache License, Version 2.0 ã§Snowflakeã«å…¬é–‹ã•ã‚Œã¦ã„ã¾ã™ã€‚ スケーラブルãªæŽ¡ç•ªã€èƒŒæ™¯çš„ãªè©± Cloudã§ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã®ã‚るサービスを見æ®ãˆã¦ã‚³ãƒ¼ãƒ‰ã‚’書ã„ã¦ã„ã‚‹ã¨æŽ¡ç•ªã«é–¢ã™ã‚‹å•é¡ŒãŒå¿…ãšå‡ºã¦ãã¾ã™ã€‚従æ¥ã€RDBã®è‡ªå‹•æŽ¡ç•ªãªã©ã«é ¼ã£ã¦ã„ãŸã®ãŒã‚³ã‚¹ãƒˆã€ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã€è€éšœå®³æ€§ã®è¦³ç‚¹ã‹
Presto at Twitter
The document discusses the evolution and deployment of Presto at Twitter, highlighting its selection over other technologies due to its high maturity, customer feedback, and community support. It outlines the integration challenges, monitoring, log collection, and authorization issues faced during the transition from alpha to production, along with the adjustments made to improve stability. Future
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Hacker News on Twitter: "Distributed Systems: A free online class: https://t.co/cVY9Xsnh0P Comments: https://t.co/wWA2bVvJW4"
GitHub - nornagon/twitter-bookmark-archiver: Download your Twitter bookmarks and associated media
ニコã¡ã‚ƒã‚“@2yç”·ã®åママã•ã‚“ã¯Twitterを使ã£ã¦ã„ã¾ã™: 「自転車ã§å供を病院ã«é€£ã‚Œã¦è¡Œã途ä¸ã€ç‹ã„通路ã ã£ãŸã®ã§æ³¨æ„å–šèµ·ã®ãŸã‚一度ベルを鳴らã—ãŸã ã‘ãªã®ã«ã€å‰ã‚«ã‚´ã‚’æ•ã¾ã‚Œé›¢ã—ã¦ãã‚Œã¾ã›ã‚“ã§ã—ãŸã€‚ 挙å¥å供をå‰ã«ã—ã¦å¤§å£°ã§æ€’é³´ã‚Šã€æ€¯ãˆãŸåä¾›ã¯æ³£ã出ã—ã¦ã—ã¾ã„ã¾ã—ãŸã€‚ æµæ¯”寿ã§ã®ãƒ™ãƒ“ーカーã®äº‹ã¨ã„ã„ã€ã“ã†ã„ã†äººå¢—ãˆã¦ã¾ã›ã‚“？ https://t.co/86rBl1G5MQ〠/ Twitter
Twitterã®ã‚¤ãƒ¼ãƒãƒ³ãƒ»ãƒžã‚¹ã‚¯æ°ã€é›£ç—…ã®ç¤¾å“¡ã«è§£é›‡å‘Šã’「障害を言ã„訳ã«åƒã‹ãªã„ã€ã€Œæœ€æ‚ªã€ã¨ç½µå€’。多é¡ã®æ”¯æ‰•ç¾©å‹™ã‚’å‰ã«è¬ç½ª | テクノエッジ TechnoEdge
GitHub - twitter/pelikan: Pelikan is Twitter's unified cache backend
Sticky footer · Twitter Bootstrap
Dashboard Template for Bootstrap
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