go-metrics

Hello! - at moment logging is quite unstructured - just text entries, written into stdout or file. In future I am planning to move to something like this (https://github.com/Sirupsen/logrus) and improve log structure. - metrics exist in Centrifuge but the next step for Centrifugo (the only thing left to be fully compared with Python version). At moment external monitoring tools can be used for CPU and memory monitoring. I am planning to utilize this library for metrics - https://github.com/rcrowley/go-metrics - you can run several instances on different machines connected via Redis and load balance clients between them. But no sharding support out of the box. What do you think about this? I highly appreciate any feedback

https://github.com/rcrowley/go-metrics is one I've came across while researching potential Prometheus integrations, it seems to support a number of backends including Graphite and InfluxDB. One challenge with that model of metrics is that it assumes that the monitoring system doesn't have much ability to work with samples, so it makes up for this by calculating rates and quantiles in the client. This isn't as accurate as doing it in the server, and some instrumentation systems don't allow you to extract out the raw data to allow you to do it in the server. For example say you've a 1-minute rate exported/scraped every minute. If you miss a push/scrape you lose all information about that minute. Similarly if you're delayed by a second, you'll miss a spike just after the previous push/scrape. If instead you expose a monotonically increasing