mmcgrana/services-engineering

This repository is a curated reading list for engineers who build and operate cloud infrastructure services. It collects papers, blog posts, presentations, and books that cover the theory and practice of running large-scale distributed systems reliably. The papers section is the heaviest part of the list. It includes foundational technical papers from major technology companies describing systems like Google's Bigtable, Spanner, MapReduce, and the Google File System, as well as Amazon's Dynamo key-value store and the Kafka messaging system from LinkedIn. These papers are often referenced when engineers want to understand the design decisions behind widely used infrastructure. The list also includes papers on consensus algorithms, disk failure rates, distributed tracing, and the theory of complexity in software systems. The blog posts section takes a more practical angle, covering topics like how to think about alerting, how to run game-day exercises that deliberately break systems to find weaknesses, how to write useful postmortems after incidents, and common mistakes people make when reasoning about distributed systems. Several posts come from well-known engineers writing about their experience at Netflix, Stripe, Heroku, Twitter, and similar companies. The books section is short and leans toward the human and organizational side of reliability: how people understand and cause errors, how to run retrospectives, and how checklists improve performance under pressure. There are also a couple of more technical titles on browser networking and web operations. The list accepts community contributions and the README links to a contributing guide. It does not include code or tutorials, only pointers to external reading material.