It’s definitely interesting to see the different systems being built for monitoring across the different tech co’s. M3 aggregator, Uber’s metrics aggregation t

It’s definitely interesting to see the different systems being built for monitoring across the different tech co’s. M3 aggregator, Uber’s metrics aggregation tier is similar, except it has inbuilt replication and leader election on top of etcd to avoid any SPOF during deployments, failed instances, etc. Also it uses Cormode-Muthukrishnan for estimating percentiles by default, it has support for T-Digest too. Although these days submitting histogram bucket aggregates all the way from the client to aggregator then to storage is more popular as you can estimate percentiles across more dimensions and time windows at query time quite cheaply. You need to choose your buckets carefully though. It too is open source, but needs some help to make it plug into other stacks more easily: https://github.com/m3db/m3aggregator https://github.com/m3db/m3aggregator