jm + discovery   3

newrelic/sidecar: Gossip-based service discovery. Docker native, but supports static discovery, too.
An AP gossip-based service-discovery sidecar process.
Services communicate to each other through an HAproxy instance on each host that is itself managed and configured by Sidecar. It is inspired by Airbnb's SmartStack. But, we believe it has a few advantages over SmartStack:

Native support for Docker (works without Docker, too!);
No dependence on Zookeeper or other centralized services;
Peer-to-peer, so it works on your laptop or on a large cluster;
Static binary means it's easy to deploy, and there is no interpreter needed;
Tiny memory usage (under 20MB) and few execution threads means its very light weight
clustering  docker  go  service-discovery  ap  sidecar  haproxy  discovery  architecture 
14 days ago by jm
Rendezvous hashing - Wikipedia, the free encyclopedia

Rendezvous or Highest Random Weight (HRW) hashing[1][2] is an algorithm that allows clients to achieve distributed agreement on a set of k options out of a possible set of n options. A typical application is when clients need to agree on which sites (or proxies) objects are to assigned to. When k is 1, it subsumes the goals of consistent hashing, using an entirely different method.
hrw  hashing  hashes  consistent-hashing  rendezvous-hashing  algorithms  discovery  distributed-computing 
april 2016 by jm
VividCortex uses K-Means Clustering to discover related metrics
After selecting an interesting spike in a metric, the algorithm can automate picking out a selection of other metrics which spiked at the same time. I can see that being pretty damn useful
metrics  k-means-clustering  clustering  algorithms  discovery  similarity  vividcortex  analysis  data 
march 2015 by jm

Copy this bookmark:



description:


tags: