Add changelog, update docs for 0.2.0

CHANGELOG.md

@@ -0,0 +1,12 @@
+# dynsampler-go changelog
+
+## 0.2.0 2019-07-31
+
+Features
+
+- Adds Exponential Moving Average (`EMASampleRate`) implementation with Burst Detection, based on the `AvgSampleRate` implementation. See docs for description.
+- Adds `SaveState` and `LoadState` to interface to enable serialization of internal state for persistence between process restarts.
+
+## 0.1.0 2019-05-22
+
+Versioning introduced.

README.md

@@ -21,3 +21,4 @@ Depending on the shape of your traffic, one may serve better than another, or yo
 * If your logging system has a strict cap on the rate it can receive events, use `TotalThroughput`, which will calculate sample rates based on keeping *the entire system's* representative event throughput right around (or under) particular cap.
 * If your system has a rough cap on the rate it can receive events and your partitioned keyspace is fairly steady, use `PerKeyThroughput`, which will calculate sample rates based on keeping the event throughput roughly constant *per key/partition* (e.g. per user id)
 * The best choice for a system with a large key space and a large disparity between the highest volume and lowest volume keys is `AvgSampleRateWithMin` - it will increase the sample rate of higher volume traffic proportionally to the logarithm of the specific key's volume. If total traffic falls below a configured minimum, it stops sampling to avoid any sampling when the traffic is too low to warrant it.
+* `EMASampleRate` works like `AvgSampleRate`, but calculates sample rates based on a moving average (Exponential Moving Average) of many measurement intervals rather than a single isolated interval. In addition, it can detect large bursts in traffic and will trigger a recalculation of sample rates before the regular interval.

doc.go

@@ -21,6 +21,8 @@ The following guidelines can help you choose a sampler. Depending on the shape o
 
 * The best choice for a system with a large key space and a large disparity between the highest volume and lowest volume keys is `AvgSampleRateWithMin` - it will increase the sample rate of higher volume traffic proportionally to the logarithm of the specific key's volume. If total traffic falls below a configured minimum, it stops sampling to avoid any sampling when the traffic is too low to warrant it.
 
+* `EMASampleRate` works like `AvgSampleRate`, but calculates sample rates based on a moving average (Exponential Moving Average) of many measurement intervals rather than a single isolated interval. In addition, it can detect large bursts in traffic and will trigger a recalculation of sample rates before the regular interval.
+
 Each sampler implementation below has additional configuration parameters and a
 detailed description of how it chooses a sample rate.