ClockBound allows you to generate and compare bounded timestamps that include accumulated error as reported from the local chronyd process. On every request, ClockBound uses two pieces of information: the current time and the associated absolute error range, which is also known as the clock error bound. This means that the “true” time of a ClockBound timestamp is within a set range. Using ClockBou
Summary statistics such as the mean and variance are easily maintained for large, distributed data streams, but order statistics (i.e., sample quantiles) can only be approximately summarized. There is extensive literature on maintaining quantile sketches where the emphasis has been on bounding the rank error of the sketch while using little memory. Unfortunately, rank error guarantees do not precl
Strong consistency replication helps keep application logic simple and provides significant benefits for correctness and manageability. Unfortunately, the adoption of strongly-consistent replication protocols has been curbed due to their limited scalability and performance. To alleviate the leader bottleneck in strongly-consistent replication protocols, we introduce Pig, an in-protocol communicati
A key concern in modern distributed systems is to avoid the cost of coordination while maintaining consistent semantics. Until recently, there was no answer to the question of when coordination is actually required. In this paper we present an informal introduction to the CALM Theorem, which answers this question precisely by moving up from traditional storage consistency to consider properties of
TL;DR 分散システムにおいてキューを導入する場合、本当にキューが必要なのか再考すべき。そこが地獄の入り口だから。 システムの抽象 コンピュータの世界は、本来は0と1の信号の羅列が飛び交う無機質なものである。でも人類は信号だけですべてを語らず、様々な喩えを定義してきた。それはデスクトップ・ウィンドウ・マウスカーソルといったグラフィカルな表現に留まらず、パケットやカプセル化といった用語にロック・キュー・リスト・木などのアルゴリズムやデータ構造の世界にも自然に溶け込んでいる。これらはすべて人間の理解を助けるための喩え話に過ぎず、この喩えこそが人間のより直感的な理解をもたらす一方で、発想の制約を生み出してきた。 人間が大きなシステムを作るときも何らかの喩えを用いてシステム全体を整理する。アーキテクチャの「ポンチ絵」を描いて情報共有をするのは企業に勤めていれば経験した人も多いだろう。パワーポイン
 TL;DR; 「分散ロック」が分散システムの設計図に登場した時 だいたいその設計は間違っていて本当に必要なものはトランザクションだ 並行システムを実装する際にロックを用いるのはとても自然なことだ。 僕も普段はロックフリー系のアルゴリズムに詳しいと言われがちだが知識量でいったら実はロック系の方が多く蓄えているかも知れない。 分散システムは並行システムであることが多いので、その中にロックが登場するのはとても自然な発想である。 よく「分散」「並行」「並列」の言葉の定義がごっちゃになっているケースがあり、この記事の主題にしたいわけではないので深くは言及しないが、分散システムは環境などの要因で突如として参加者が音信不通になったり復活したりする点で並行システムと大きく異なる。 並行システムと同じノリで分散システムを設計しようとした際に陥る頻出の過ちが「分散ロック」である。そのアイデアはとても簡単で
PRINCIPLES OF CHAOS ENGINEERING Last Update: 2019 March (changes) Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production. Advances in large-scale, distributed software systems are changing the game for software engineering. As an industry, we are quick to adopt practices that increase
9. NIPS’17 Workshop: DL at Supercomputer Scale • 1:30 - 1:50 - Azalia Mirhoseini - “Learning Device Placement” • 1:50 - 2:10 - Gregory Diamos - “Scaling and Sparsity” • 2:10 - 2:30 - Scott Gray - “Small World Network Architectures” • 2:30 - 2:50 - Timothy Lillicrap - “Scalable RL & AlphaGo” • 3:20 - 3:40 - Thorsten Kurth - “Scaling Deep Learning to 15 PetaFlops” • 3:40 - 4:00 - Simon Knowles - “Sc
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute: Learn more about Ray AI Libraries: Data: Scalable Datasets for ML Train: Distributed Training Tune: Scalable Hyperparameter Tuning RLlib: Scalable Reinforcement Learning Serve: Scalable and Programmable Serving Or more about Ray Core an
Global-scale applications, such as virtual wallets, advertising platforms, social networks, online games, or collaboration networks, require consistency across distributed data items. As networked users, objects, devices, and sensors proliferate, the consistency issue is increasingly acute for the software industry. Both sides of the classical alternative, requiring to choose between consistency a
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? TL;DR; Eventual Consistencyとか言いながらどうせもっとまともな一貫性実装してることはよくあるんだからみんな適切な名前を使おうぜ。 なぜこの記事を書くのか NoSQLの文脈においてスケーラビリティとのトレードオフでEventual Consistencyという用語は結構な頻度で出てくる。 ACIDに対抗してBASE(Basicaly Avalilable, Soft state, Eventual consistency)なんて言葉が出てきたり、CAP定理の中のAとPだと言ってみたり、分散システムのスケーラビリテ
Amazon Aurora Unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility Amazon Aurora provides unparalleled high-performance and availability at global scale with full MySQL and PostgreSQL compatibility, at 1/10th the cost of commercial databases. Aurora has 5x the throughput of MySQL and 3x of PostgreSQL. Aurora has broad compliance standards and
Robust Distributed System Nucleus (rDSN) is a framework for quickly building robust distributed systems. It has a microkernel for pluggable components, including applications, distributed frameworks, devops tools, and local runtime/resource providers, enabling their independent development and seamless integration. The project was originally developed for Microsoft Bing, and now has been adopted i
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