Describe the role of CloudWatch Metrics Math when querying metrics data. Provide examples of formulas you have used in the past.
CloudWatch Metrics Math plays a crucial role in querying metrics data by allowing users to perform calculations on multiple metrics for real-time analysis and visualization. It enables the creation of custom expressions, aggregation, and transformation of metric data points.
In my experience, I have used several formulas:
1. Scaling : To convert bytes to gigabytes, I used the formula “m1 / 1024 / 1024 / 1024”, where m1 represents the original metric in bytes.
2. Summation : To calculate the total number of requests across different services, I used “SUM([m1, m2, m3])”, where m1, m2, and m3 are individual service request metrics.
3. Average : To find the average CPU utilization of an EC2 instance, I used “AVG(m1)”, where m1 is the CPUUtilization metric.
4. Rate of change : To determine the rate at which errors occur, I applied “RATE(m1)”, where m1 is the error count metric.
5. Percentage : To compute the cache hit ratio, I employed the expression “100 * (m1 / (m1 + m2))”, where m1 denotes cache hits and m2 signifies cache misses.
