Monitor event loop by looking for skew

If we monitor with setImmediate, we miss big blocking loops. For example,
suppose we have 1000 1ms loops then a single bad 1000ms loop. setImmediate
will only be called at the right time 1/1000 of the time (it has to be the
loop just before the bad one). So this monitoring method gives a good average
if the std dev is low, but doesn't pick up spikes.

Instead, we can monitor the skew from the expected time between setIntervals.
In the case above, with a setInterval for 1000ms, we will pick up a skew
proportional to the amount of time that it overlaps the bad loop. So 50%
change of picking up skew > 500ms, and thus getting a good sense of any
spikes.

libraries/metrics/event_loop.coffee

@@ -1,18 +1,16 @@
-seconds = 1000
-
 module.exports = EventLoopMonitor =
-	monitor: (logger) ->
-		interval = setInterval () ->
-			EventLoopMonitor.Delay()
-		, 1 * seconds
+	monitor: (logger, interval = 1000, log_threshold = 100) ->
 		Metrics = require "./metrics"
+		
+		previous = Date.now()
+		intervalId = setInterval () ->
+			now = Date.now()
+			offset = now - previous - interval
+			if offset > log_threshold
+				logger.warn {offset: offset}, "slow event loop"
+			previous = now
+			Metrics.timing("event-loop-millsec", offset)
+		, interval
+		
 		Metrics.registerDestructor () ->
-			clearInterval(interval)
-
-	Delay: () ->
-		Metrics = require "./metrics"
-		t1 = process.hrtime()
-		setImmediate () ->
-			delta = process.hrtime(t1)
-			responseTime = delta[0]*1e6 + delta[1]*1e-3
-			Metrics.timing("event-loop-microsec", responseTime)
+			clearInterval(intervalId)