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Charity Majors

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cofounder and CTO Honeycomb

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Observability Engineering, 2nd Edition

Observability is the only way to engineer, manage, and improve the business-critical systems that customers depend on every day—and as the complexity of software grows, so does the need for observability. With this thoroughly revised second edition, authors Charity Majors, Liz Fong-Jones, and George Miranda take inventory of the current state of the field and explain how practitioners can evolve their observability practices from collecting separate, disparate signals to unified data workflows. This book is for any software engineering team, large or small, that must understand the unique customer experience in order to ship quality code and features that customers want, at the right velocity. You'll discover the value that observable systems bring and learn concrete steps you can follow to achieve an observability-driven development practice yourself. And four completely new chapters explore recent trends such as large language models, frontend observability, cost optimization/performance engineering, and practical open source tooling. Understand the impact observability has across the entire software development lifecycle Learn how and why different functional teams use observability with service-level objectives Implement modern observability practices in your organization Maximize the cost-effectiveness of observability tooling Produce quality code for context-aware system debugging and maintenance Use data-rich analytics to quickly find answers when maintaining site reliability

Supported by Our Partners • Sonar —  Trust your developers – verify your AI-generated code. • Vanta —Automate compliance and simplify security with Vanta. — In today's episode of The Pragmatic Engineer, I'm joined by Charity Majors, a well-known observability expert – as well as someone with strong and grounded opinions. Charity is the co-author of "Observability Engineering" and brings extensive experience as an operations and database engineer and an engineering manager. She is the cofounder and CTO of observability scaleup Honeycomb. Our conversation explores the ever-changing world of observability, covering these topics: • What is observability? Charity’s take • What is “Observability 2.0?” • Why Charity is a fan of platform teams • Why DevOps is an overloaded term: and probably no longer relevant • What is cardinality? And why does it impact the cost of observability so much? • How OpenTelemetry solves for vendor lock-in  • Why Honeycomb wrote its own database • Why having good observability should be a prerequisite to adding AI code or using AI agents • And more! — Timestamps (00:00) Intro  (04:20) Charity’s inspiration for writing Observability Engineering (08:20) An overview of Scuba at Facebook (09:16) A software engineer’s definition of observability  (13:15) Observability basics (15:10) The three pillars model (17:09) Observability 2.0 and the shift to unified storage (22:50) Who owns observability and the advantage of platform teams  (25:05) Why DevOps is becoming unnecessary  (27:01) The difficulty of observability  (29:01) Why observability is so expensive  (30:49) An explanation of cardinality and its impact on cost (34:26) How to manage cost with tools that use structured data  (38:35) The common worry of vendor lock-in (40:01) An explanation of OpenTelemetry (43:45) What developers get wrong about observability  (45:40) A case for using SLOs and how they help you avoid micromanagement  (48:25) Why Honeycomb had to write their database  (51:56) Companies who have thrived despite ignoring conventional wisdom (53:35) Observability and AI  (59:20) Vendors vs. open source (1:00:45) What metrics are good for  (1:02:31) RUM (Real User Monitoring)  (1:03:40) The challenges of mobile observability  (1:05:51) When to implement observability at your startup  (1:07:49) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • How Uber Built its Observability Platform https://newsletter.pragmaticengineer.com/p/how-uber-built-its-observability-platform  • Building an Observability Startup https://newsletter.pragmaticengineer.com/p/chronosphere  • How to debug large distributed systems https://newsletter.pragmaticengineer.com/p/antithesis  • Shipping to production https://newsletter.pragmaticengineer.com/p/shipping-to-production  — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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session
with Guillermo Rauch (Vercel) , Steve McGhee (Google) , Kaslin Fields (Google Cloud) , Charity Majors (Honeycomb) , Josh Long (Broadcom) , Femi Akinde (Google Cloud) , Richard Seroter (Google Cloud) , Brad Calder (Google Cloud) , Chloe Condon (Google Cloud) , Philipp Schmid (Google DeepMind) , Chen Goldberg (Google Cloud)

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Observability Engineering

Observability is critical for building, changing, and understanding the software that powers complex modern systems. Teams that adopt observability are much better equipped to ship code swiftly and confidently, identify outliers and aberrant behaviors, and understand the experience of each and every user. This practical book explains the value of observable systems and shows you how to practice observability-driven development. Authors Charity Majors, Liz Fong-Jones, and George Miranda from Honeycomb explain what constitutes good observability, show you how to improve upon what you're doing today, and provide practical dos and don'ts for migrating from legacy tooling, such as metrics, monitoring, and log management. You'll also learn the impact observability has on organizational culture (and vice versa). You'll explore: How the concept of observability applies to managing software at scale The value of practicing observability when delivering complex cloud native applications and systems The impact observability has across the entire software development lifecycle How and why different functional teams use observability with service-level objectives How to instrument your code to help future engineers understand the code you wrote today How to produce quality code for context-aware system debugging and maintenance How data-rich analytics can help you debug elusive issues