Distributed Tracing in Practice: Instrumenting, Analyzing, and Debugging Microservices
Parker, Austin, Spoonhower, Daniel, Mace, Jonathan
- 出版商: O'Reilly
- 出版日期: 2020-05-19
- 定價: $2,580
- 售價: 9.5 折 $2,451
- 貴賓價: 9.0 折 $2,322
- 語言: 英文
- 頁數: 315
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1492056634
- ISBN-13: 9781492056638
-
相關分類:
Microservices 微服務、SOA
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相關主題
商品描述
Most applications today are distributed in some fashion. Monitoring the health and performance of these distributed architectures requires a new approach. Enter distributed tracing, a method of profiling and monitoring applications--especially those that use microservice architectures. There's just one problem: distributed tracing can be hard. But it doesn't have to be.
With this practical guide, you'll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful, operational insights. If you want to start implementing distributed tracing, this book tells you what you need to know.
You'll learn:
- The pieces of a distributed tracing deployment: Instrumentation, data collection, and delivering value
- Best practices for instrumentation (the methods for generating trace data from your service)
- How to deal with or avoid overhead, costs, and sampling
- How to work with spans (the building blocks of request-based distributed traces) and choose span characteristics that lead to valuable traces
- Where distributed tracing is headed in the future
商品描述(中文翻譯)
現今大多數應用程式都以某種方式進行分散部署。監控這些分散式架構的健康狀態和性能需要一種新的方法。這就是分散式追蹤,一種用於分析和監控應用程式的方法,尤其適用於使用微服務架構的應用程式。然而,分散式追蹤有一個問題:它可能很困難。但這並非必然。
這本實用指南將教你什麼是分散式追蹤,以及如何使用它來了解軟體的性能和運作情況。LightStep 的關鍵人物將帶領你進行代碼追蹤的儀器化,收集儀器化產生的數據,並將其轉化為有用的運營洞察。如果你想開始實施分散式追蹤,這本書將告訴你需要知道的一切。
你將學到:
- 分散式追蹤部署的組成部分:儀器化、數據收集和提供價值
- 儀器化的最佳實踐(從服務中生成追蹤數據的方法)
- 如何處理或避免開銷、成本和抽樣
- 如何使用 span(基於請求的分散式追蹤的構建塊)並選擇能產生有價值追蹤的 span 特性
- 分散式追蹤未來的發展方向
作者簡介
Austin Parker is an Open Source Software Engineer at LightStep, where he works as a core contributor and maintainer to the OpenTracing project. Prior to LightStep, he was a Software Architect at Apprenda building enterprise platforms using Kubernetes.
Daniel Spoonhower is a co-founder at LightStep, where he's building performance management tools for modern software systems. Previously, Spoons spent almost six years at Google where he worked on developer tools as part of both Google's internal infrastructure and Cloud Platform teams. He has published papers on the performance of parallel programs, garbage collection, and real-time programming. He has a PhD in programming languages from Carnegie Mellon University but still hasn't found one he loves.
Jonathan Mace is a tenure track faculty member at the Max Planck Institute for Software Engineering. His areas of research include cloud systems, distributed systems, networking, and operating systems.
Ben Sigelman is the CEO and co-founder of LightStep, co-creator of Dapper (Google's distributed tracing tool that helps developers make sense of their large-scale distributed systems), and co-creator of the open-source OpenTracing API standard (a project within the CNCF).
Rebecca Isaacs is a software engineer currently focused on the performance tuning and debugging of large-scale data center services. She was previously a research scientist, most recently at Google. She first started thinking about tracing for distributed systems over 15 years ago while at Microsoft Research, which she joined after obtaining a PhD from Cambridge University and a BSc from the University of Glasgow.
作者簡介(中文翻譯)
Austin Parker是LightStep的開源軟體工程師,他在OpenTracing專案中擔任核心貢獻者和維護者的角色。在加入LightStep之前,他在Apprenda擔任軟體架構師,使用Kubernetes建立企業平台。
Daniel Spoonhower是LightStep的共同創辦人,他正在開發針對現代軟體系統的性能管理工具。之前,Spoons在Google工作了近六年,他在Google的內部基礎設施和雲平台團隊中負責開發者工具。他發表過關於並行程式、垃圾回收和實時程式的論文。他在卡內基梅隆大學獲得了編程語言的博士學位,但仍然沒有找到他喜愛的一種語言。
Jonathan Mace是馬克斯普朗克軟體工程研究所的終身職教職成員。他的研究領域包括雲系統、分散系統、網路和作業系統。
Ben Sigelman是LightStep的首席執行長和共同創辦人,也是Dapper的共同創作者(Dapper是Google的分散追蹤工具,幫助開發者理解大規模分散系統)以及開源的OpenTracing API標準的共同創作者(這是CNCF內的一個專案)。
Rebecca Isaacs是一位軟體工程師,目前專注於調優和除錯大規模資料中心服務的性能。她之前是一位研究科學家,最近在Google工作。她在加入Microsoft Research之前,於劍橋大學獲得博士學位並在格拉斯哥大學獲得學士學位時,就開始思考分散系統的追蹤問題已經超過15年了。