3 ms·

> all public github code In RAM.

• dbarlett 12y ago
  Some napkin math - as of late 2013, GitHub's main Elasticsearch cluster had ~128 shards of ~120 GB [1]. Obviously they have more data now, and it's not clear whether the number of shards includes replicas, but at current EC2 on-demand prices[2]: RAM: 63 r3.8xlarge @ $2.80/hr = $176.40/hr SSD: 5 i2.4xlarge @ $3.41/hr = $ 17.05/hr HDD: 1 hs1.8xlarge @ $4.60/hr = $ 4.60/hr [1] http://www.elasticsearch.org/case-study/github/ http://www.elasticsearch.org/case-study/github/ [2] http://aws.amazon.com/ec2/pricing/ http://aws.amazon.com/ec2/pricing/
  • yohanatan 12y ago
    A hybrid multi-layer cache system would likely be more cost effective and still perform nearly as well as dedicated RAM (depending on how the data is structured/sharded/queried).
  • X-Istence 12y ago
    We don't even need to keep ALL of it in memory, we would just need to keep everything for the current language we are developing in. Maybe one or two others. Say I am working on a Angular/Pyramid application, all I would need is JavaScript and Python loaded.