A reading list for services engineering, with a focus on cloud infrastructure services.
We welcome suggestions.
- Fault Injection in Production (Allspaw)
- Making Reliable Distributed Systems in the Presence of Software Errors (Armstrong)
- Highly Available Transactions: Virtues and Limitations (Bailis et al.)
- The Incident Command System (Bigley and Roberts)
- The Chubby Lock Service for Loosely Coupled Distributed Systems (Burrows)
- Bigtable: a Distributed Storage System for Structured Data (Chang et al.)
- Spanner: Google’s Globally-Distributed Database (Corbett et al.)
- Dynamo: Amazon’s Highly Available Key-Value Store (DeCandia et al.)
- MapReduce: Simplified Data Processing on Large Clusters (Dean and Ghemawat)
- The Google File System (Ghemawat et al.)
- On Designing and Deploying Internet Scale Services (Hamilton)
- Kafka: A Distributed Messaging System for Log Processing (Kreps et al.)
- Weathering the Unexpected (Krishnan)
- The Unified Logging Infrastructure for Data Analytics at Twitter (Lee et al.)
- Automatic Management of Partitioned, Replicated Search Services (Leibert et al.)
- Learning to Embrace Failure (Limoncelli et al.)
- Scaling Big Data Mining Infrastructure: The Twitter Experience (Lin and Rayboy)
- Dremel: Interactive Analysis of Web-Scale Datasets (Melnik et al.)
- Out of the Tar Pit (Moseley and Marks)
- The Log-Structured Merge-Tree (O'Neil et al.)
- In Search of an Understandable Consensus Algorithm (Ongaro and Ousterhout)
- Failure Trends in a Large Disk Drive Population (Pinheiro et al.)
- Fallacies of Distributed Computing Explained (Rotem-Gal-Oz)
- F1 - The Fault-Tolerant Distributed RDBMS Supporting Google’s Ad Business (Shute et al.)
- Dapper, A Large Scale Distributed Systems Tracing Infrastructure (Sigelman et al.)
- Resident Distributed Datasets: a Fault-Tolerant Abstraction for In-Memory Cluster Computing (Zahari et al.)
- The Human Side of Postmortems (Zwieback)
- Crew Resource Management: a Positive Change for the Fire Service
- Resilience Engineering: Part I, Part II (Allspaw)
- Systems Engineering: a Great Definition (Allspaw)
- Chaos Monkey Released Into The Wild (Bennett and Tseitlin)
- Some Rules for Engineering and Operations (Black)
- Service Level Disagreements Part I, Part II (Black)
- My Philosophy on Alerting (Ewaschuk)
- You Can’t Sacrifice Partition Tolerance (Hale)
- Customer Trust (Hamilton)
- Observations on Errors, Corrections, & Trust of Dependent Systems (Hamilton)
- Game Day Exercises at Stripe: Learning from
kill -9(Hedlund) - Life Beyond Distributed Transactions: An Apostate’s Opinion (Helland)
- Notes on Distributed Systems for Young Bloods (Hodges)
- The Network is Reliable (Kingsbury)
- The Trouble with Clocks (Kingsbury)
- Call Me Maybe: Final Thoughts (Kingsbury)
- Getting Real About Distributed Systems Reliability (Kreps)
- The Log: What every software engineer should know about real-time data's unifying abstraction (Kreps)
- Incident Response at Heroku (McGranaghan)
- On HTTP Load Testing (Nottingham)
- Observability at Twitter (Watson)
- Stevey’s Google Platforms Rant (Yegge)
- Design, Lessons, and Advice from Building Distributed Systems at Google (Dean)
- Service Design Best Practices (Hamilton)
- The Field Guide To Understanding Human Error (Dekker)
- Agile Retrospectives: Making Good Teams Great (Derby et al.)
- Better: A Surgeon’s Notes on Performance (Gawande)
- The Checklist Manifesto: How to Get Things Right (Gawande)
- High Performance Browser Networking (Grigorik)
- Resilience Engineering in Practice (Hollnagel et al.)
- Effective Monitoring and Alerting (Ligus)
- Release It!: Design and Deploy Production-Ready Software (Nygard)
- The Challenger Launch Decision (Vaughan)
- Managing the Unexpected (Weick and Sutcliffe)