Scaling up and out - and back down again - at a moment’s notice is essential for many large scale applications today. Scaling and performance at scale doesn’t have to be a nightmare, this collection covers concrete ways to ensure your distributed architecture is resilient, robust, and able to seamlessly interact with databases, APIs, and customers.
Scaling up and out - and back down again - at a moment’s notice is essential for many large scale applications today. Scaling and performance at scale doesn’t have to be a nightmare, this collection covers concrete ways to ensure your distributed architecture is resilient, robust, and able to seamlessly interact with databases, APIs, and customers.
MEAN Architecture 2.0 - Scott Davis (ThirstyHead.com) - Part 1
MEAN Architecture 2.0 - Scott Davis (ThirstyHead.com) - Part 2
Road traffic analysis and agile architectures - Kristoffer Dyrkorn (BEKK Consulting) - Part 1
Road traffic analysis and agile architectures - Kristoffer Dyrkorn (BEKK Consulting) - Part 2
Consistent hashing, shuffle sharding, and copysets: Practical tools for controlling failure - Wes Chow (Chartbeat)
It probably works: Deploying probabilistic algorithms on a large scale - Tyler McMullen (Fastly)
Beyond multitenancy: Introducing a new container-based application factory - Thierry Delprat (Nuxeo)
How to have your causality and wall clocks too - Jon Moore (Comcast Cable)
Leading simplicity - Sam Lambert (GitHub)
Apache Kafka and the stream data platform - Jay Kreps (Confluent)
Enhancing society with APIs at the New York Times - Scott Feinberg (The New York Times Company)
Building better distributed data pipelines - Patrick McFadin (DataStax)
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