Zipkin is a distributed tracing system that helps us gather timing data for all the disparate services at Twitter. It manages both the collection and lookup of this data through a Collector and a Query service. We closely modelled Zipkin after the Google Dapper paper. Follow @ZipkinProject for updates. Why distributed tracing? Collecting traces helps developers gain deeper knowledge about how cer
TwitterServer¶ TwitterServer defines a template from which servers at Twitter are built. It provides common application components such as an administrative HTTP server, tracing, stats, etc. These features are wired in correctly for use in production at Twitter. Getting Started¶ TwitterServer is published to Maven central: <dependency> <groupId>com.twitter</groupId> <artifactId>twitter-server_2.12
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
Effective Scala Marius Eriksen, Twitter Inc. marius@twitter.com (@marius) [translated by Yuta Okamoto (@okapies) and Satoshi Kobayashi (@scova0731)] Table of Contents 序章 書式: ホワイトスペース, 命名, インポート, 中カッコ, パターンマッチ, コメント 型とジェネリクス: 戻り型アノテーション, 変位, 型エイリアス, 暗黙 コレクション: 階層, 使う, スタイル, 性能, Java コレクション 並行性: Future, コレクション 制御構造: 再帰, Return, forループと内包, require と assert 関数型プログラミング: 代数的データ型としてのケースクラス, Option, パターンマ
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