(PFC307) Auto Scaling: A Machine Learning Approach | AWS re:Invent 2014
-
Upload
amazon-web-services -
Category
Technology
-
view
421 -
download
0
description
Transcript of (PFC307) Auto Scaling: A Machine Learning Approach | AWS re:Invent 2014
November 12, 2014, Las Vegas NV
Sumit Amar, Electronic Arts
var client = new Amazon.CloudWatch.AmazonCloudWatchClient();
var response = client.GetMetricStatistics(
new GetMetricStatisticsRequest
{
Dimensions = new List<Dimension> {
new Dimension { Name = "InstanceId", Value = instanceId } },
StartTime = startDate, //2014-11-05
EndTime = endDate.Date.AddDays(1).Date.AddMilliseconds(-1), //2014-11-06,
Namespace = "AWS/EC2",
Statistics = new List<string>{ "Average", "Maximum", "Minimum","Sum","SampleCount" },
MetricName = metricName, //CPUUtilization, DiskReadBytes, NetworkIn, more etc..
Period = interval, //seconds – pass 60 * 60 for an hourly range
});
//### CloudWatch GetMetricsStatistics returns unordered data points, ergo..
response.Datapoints.Sort((a,b) => a.Timestamp.CompareTo(b.Timestamp));
Y = a + b X
Time Actual(Y) Deviation X(from mid) XY X2 Yd
8am 83 -3 -249 9 72.22
9am 60 -2 -120 4 61.29
10am 54 -1 -54 1 50.36
11am 21 0 0 0 39.43
12p 22 1 22 1 28.50
1p 13 2 26 4 17.57
2p 23 3 69 9 6.64
N=7 ∑𝑌 = 276 ∑X=0 ∑XY=-306 ∑X2=28
Here: Y = a + b X
a = ∑𝑌/𝑁 = 276/7 = 39.43
b = ∑𝑋𝑌
∑𝑋2 = -306/28 = -10.93
Y = 39.43 – 10.93 X
For X = -3 (8am): Y8am = 39.43 – (10.93 * -3) = 72.22 and so on for other times.
∑Y = Na + b ∑X
∑XY = a ∑X + b ∑X2
∑Y = Na + b ∑X + c ∑X2
∑XY = a ∑X + b ∑X2 + c ∑X3
∑X2Y = a ∑X2 + b ∑X3 + c ∑X4
Yd = a + b X + c X2
∑Y = Na + c ∑X2
∑XY = b ∑X2
∑X2Y = a ∑X2 + c ∑X4
EWMA Article
EWMA on Wikipedia
k-NN lecture
k-NN on Wikipedia
MSE
SSE
Machine Learning Course
http://bit.ly/awsevals