Interesting Snippets from 2017-12-12

• How Etsy caches: hashing, Ketama, and cache smearing - Code as Craft

  While consistent hashing is efficient there is a drawback to having each key exist on only one server. Different keys are used for different purposes, and certain cache items will be read and written more than others. In our experience, cache key read rates follow a power law distribution: a handful of keys are used for a majority of reads, while the majority of keys are read a small number of times. With a large number of keys and a large pool, a good hash function will distribute the “hot keys”—the most active keys—among many servers, smoothing out the load.

• The Motherboard Guide to Avoiding State Surveillance - Motherboard

  A straightforward guide to privacy, messaging, and keeping yourself safe from passive and active surveillance.

• GitHub - qubole/rubix: Cache File System optimized for columnar formats and object stores

  RubiX provides disk or in-memory caching of data, which would otherwise be accessed over network when it resides in cloud store, thereby improving performance.

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