homework lab9 aras umit

8/3/2019 Homework Lab9 Aras Umit

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Fall 2011Homework Lab 9Faik Aras TarhanUmit Cavus Buyuksahin


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OVERVIEW

To characterize Multi-tier enterprise software systems, it

is important to:

understand the peak capabilities of the system

locate and quantify performance bottlenecks (such asCPU/disk/network)

ensure the validity of the measured data

These goals can be achieved by a systematic

methodology which provides a basis for performance

comparison of different e-business middleware


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Which Approach and Why ?

Two approaches for systematic methodology

Stochastic Analysis

Queuing Operational Analysis

Second one was chosen by the paper since;

simple to measure for an N-tier system

allows to make use of operational laws, which have been

well understood for more than 30 years

application of these fundamental equations can provide

sanity- checks


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Queuing Model of a 3-Tier

System

consists of

a web server ( a script (e.g. ASP or JSP) or Java Servlet runs )

an application server (a business object (e.g. COM+, EJB))and a database server ( SQL,Oracle etc. )

also a client to generate the workload (e.g. HTTP request)


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Key Metrics and Basic

EquationsMetrics:

the throughput in requests per second (X), a measure of

work done by the system in terms of completed request

the response time in seconds (R), the average latency of arequest

the number of concurrent requests in the system (N)

Equations:

Utilization law: Ui = X * Di

Littles Law:N = X * R


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Experiment Tools and Setup

A stress test tool, called Web Application Stress tool(WAS), from Microsoft is used.

composes the number of concurrent threads that willmake requests

runs the script for some amount of time

measures:

performance data (e.g. CPU utilization, disk utilization )

throughput for the test (X)

(TTLB) response time for the test( If TTLB is big enough, client delay can be so negligible thatRand TTLB are considered as equal )


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General Calculation

ProcedureService demands for CPU, Disk, Network by the

Utilization Law

The average of the measured service demands for eachresource is calculated

The service demand values were inspected to find and

evaluate the performance bottlenecks

Littles Law is used to help sanity-check


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Experiment on Servlet A

Cpu is the

bottleneck

The service

demand is ~24 ms

Derived X matches

closely the

measured

throughput from

WAS


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Experiment on

Servlet AThe measurement is valid, as

verified by the equations.

The equations are applicable toreal world setups.

We have a way of comparing

workloads in terms of resource

usage.


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Experiment on Servlet BThe deviation of the two curvesindicates that there is indeed a

problem with the measurement

Running a large number of

threads on such a system meansthat the client system CPUs are

spending too much time in

context switching between

threads, rather than generatingrequests to the server

it is worthwhile to use Littles Law to validate measurements


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IIS Web Server Experiment (

with 20 KB HTML File)

the 100Mb/s network is the bottleneck resource

Xmax= 1/1.54 = 647 req/sec which is within 5% of

the measured peak throughput


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IIS Web Server Experiment (

with 500 B HTML File)

the CPU is the bottleneck

Even with three clients, CPU does not load up to 90%

Xmax= 1/Dmax while Dmax= 0.21ms Xmax= 4821req/sec

The measured peak throughput is 4289 req/sec which is a

discrepancy of about 11%


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Conclusion on IIS Web Server

ExperimentIn second experiment the stress clients were unable tosaturate the web server

Adding more client machines would reduce or eliminate

this discrepancy or

a larger file size would allow us to saturate the server,without adding more client systems

To sum up;

if we get a wider discrepancy between measurements andcalculated or expected data, we definitely need to dig deeperinto the causes for the discrepancy


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3-tier System Middleware

Comparisonare commonly used to separate business logic from thepresentation layer at the front end, and enterprise dataaccess at the back end

the CPU was the performance bottleneck for this test, thedata for the disk and network is not shown.

Observe in the next slide that the overall throughput X is alot higher for Middleware II compared to Middleware I (352req/sec vs. 100 req/sec)

It could be concluded that Middleware II is 3.5 times fasterthan Middleware I unless we dig deeper as concluded in theprevious slide


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Comparison


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Comparison ConclusionThe max throughput for Middleware is given by: Xmax

= 1/Dmax= 1/9.6 = 104 req/sec so the measurements

seem valid within a reasonable margin of error

the service demand for the application server is nearly

the same for both Middleware I and Middleware II

both technologies are actually equivalent in their

business logic performance!

Middleware II has the advantage is in the performance

of the web server compared to Middleware I


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Discussion

Measurements must be validated against expectations byusing Littles Law

If the measured and calculated values diverge significantly,further analysis is required

The client delay which is also called think time for a 3-tiersystem affects the slope of the throughput curve

As the delay is increased, the throughput curve shifts to theright

The maximum throughput of the system is still the same:Xmax= 1 / Dmax

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