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An updated and curated list of readings to illustrate best practices and patterns in building scalable, available, stable, performant, and intelligent large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users. Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some design principles and checking how scalability and performance problems are solved at tech companies. The section of intelligence are created for those who work with data and machine learning at big (data) and deep (learning) scale.
This is a collection of postmortem templates derived from various sources such as the Site Reliability Engineering book, The Practice of Cloud System Administration book and other online resources. It is possible to load the postmortem templates automatically without copy pasting from the files or manually writing the structure every time you want to author an incident report.
This is a list of common Disaster Recovery scenarios for software companies. It is nearly-impossible to cover all the scenarios that can happen. However, this list should include some common scenarios that can help companies kick-start their own set of policies.
This is a collection of ported Markdown templates included in "The Site Reliability Engineering Workbook" regarding the Service Level Objectives and Error Budget Policy documents. Full description of each section can be found in "The Site Reliability Engineering Workbook".