Thursday, January 21, 2016

Frugal Cloud The In-Memory versus SSD Paging File

Many people remember the days when you could use a USB memory stick to boost the performance of Windows. This memory caused me to ask the question: Is there a potential cost saving with little performance impact by going sparse on physical memory and configuring a paging file.

For windows folks:

For Linux, see TechTalk Joe post. Note his "I/O requests on instance storage does not incur a cost. Only EBS volumes have I/O request charges." so it is not recommended to do if you are running with EBS only.

This approach is particularly significant when you are "just over" one the offering levels. 

For some configurations, you will not get a CPU boost - by using the paging files. I know recent experience with a commercial SAAS actually had high memory usage but very log CPU (3-5%, even during peak times!). Having 1/2 or even 1/4 the CPUs would not peg the CPU. The question then becomes whether the Paging File on a SSD drive would significantly drop performance (whether you can strip for extra performance across multiple SSD on cloud instances, is an interesting question). This is a question that can only be determined experimentally.

  • How the paging file is configured and the actual usage of memory by the application is key. Often 80-90% of the usage hits only 10% of the memory (Pareto rule). The result could be that the median (50%ile) time may be unchanged -- and time may increase only along the long tail of the response distribution (say top 3% may be longer).
These factors cannot be academically determined. They need to be determine experimentally.

If performance is acceptable, there is an immediate cost saving because when new instances are created due to load, they are cheaper instances.

Bottom line is always: Experiment,stress, time and compare cost. Between the pricing models, OS behaviors and application behaviors, there is no safe rule of thumb!

Second Rule: Always define SLA as the Median (50%-ile) and never as an average.  Web responses are long-tailed which makes the average(mean) very volatile. The median is usually very very stable.

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