AWS re:Invent 2017: Models of Availability (ARC321) – #AWS

When engineering teams take on a new project, they often optimize for performance, availability, or fault tolerance. More experienced teams can optimize for these variables simultaneously. Netflix adds an additional variable: feature velocity. Most companies try to optimize for feature velocity through process improvements and engineering hierarchy, but Netflix optimizes for feature velocity through explicit architectural decisions. Mental models of approaching availability help us understand the tension between these engineering variables. For example, understanding the distinction between accidental complexity and essential complexity can help you decide whether to invest engineering effort into simplifying your stack or expanding the surface area of functional output. The Chaos team and the Traffic team interact with other teams at Netflix under an assumption of Essential Complexity. Incident remediation, approaches to automation, and diversity of engineering can all be understood through the perspective of these mental models. With insight and diligence, these models can be applied to improve availability over time and drift into success.

via Amazon Web Services

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- Launched in 2006, Amazon Web Services offers a robust, fully featured technology infrastructure platform in the cloud comprised of a broad set of compute, storage, database, analytics, application, and deployment services from data center locations in the U.S., Australia, Brazil, China, Germany, Ireland, Japan, and Singapore. More than a million customers, including fast-growing startups, large enterprises, and government agencies across 190 countries, rely on AWS services to innovate quickly, lower IT costs and scale applications globally. To learn more about AWS, visit http://aws.amazon.com.

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