PTT Presentation

7/31/2019 PTT Presentation

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1

Caution Signs Along the Road

There will be jolts and delays along

the way for electronic commerce:

congestion is the most obvious challenge.


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Introduction

Performance Analysis= Analysis + Computer System

Performance Analyst

= Mathematician + Computer Systems Person


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Resource Utilization: For any system to consume an

input and produce the designated output, certain

resources would be required. The amount of

resources consumed by the system during processing

that request, defines the resource utilization. There

can be different resources factored in, such as

processor, disk (i/o controller), memory etc.Utilization of 80% is considered an acceptable limit.

Normally utilization of 70% warrants ordering of

additional hardware.

Throughput: Throughput refers to the rate which the

system churns expected outputs when thedesignated input is fed in the system. In other words,

for an Enterprise Application, throughput can be

defined as the total number of business transactions

completed by the application in unit time (per second

or per hour).

Response Time: Response time specifies the

time taken by the system to respond backwith the expected output. For an enterprise

application Response time is defined as the

time taken to complete a single business

transaction. It is usually expressed in seconds


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System

Application

Machine

1. System Config

2. Topology

3. Network I /O

4. Disk I/O

5. Database Tuning6. OS

1. App Design

2. App Server Tuning

3. Drivers

4. Persistence

5. Clustering

1. JVM Selection

2. JVM Tuning

3. JVM Internals

4. JIT Compilation

5. Cache Architecture

6. SMP Scaling


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Performance Management Process Flow

These steps provide a highlevel process flow for performance management:

Develop a Management Concept of Operations Define the Required Features: Services, Scalability and Availability Objectives

Define Performance SLAs and Metrics

Measure Performance Gather Baseline Data Measure Availability

Measure Response Time

Measure Accuracy

Measure Utilization

Capacity Planning

Perform a Proactive Fault Analysis Use Thresholds for Proactive Fault Management

Management Implementation

Operation Metrics


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RequirementAnalysis

Architecture &

Design

Testing

Production

Construction

Technology StackPerformance Evaluation

Performance benchmark of a technologystack (combination of h/w + s/w platform)

Product Benchmark Baseline the performance levels for a

product / prototype

Component Performance

Test

Performance Test of a Component

Capacity Planning for shared components

Performance Test for

Application Release

Load Test realistic loads

Stress Test to determine breakpoint

Volume Test over growing data volumes

Sensitivity Test varying parameters

Scalability Test across scaled-up h/w

Endurance Test long periods

Performance Testing : An Engineering Perspective


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UNIT TEST

Test Results for Analysis

CoverageProfiler

CodeProfiler

MemoryProfiler

Services

UI

API

INTEGRATION TESTINTEGRATION LOAD

TEST

Services

UI

API

PRODUCTION

STAGING TEST

PRODUCTION

STAGING LOAD TEST

Internet

Tester

Isolated

Network

TestScrip

ts

1 3

4

5

2


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Analyze

Cost

Effectiveness

START

STOP

STOP

UnderstandSystem

Implement

Modification

FormulateImprovement

Hypothesis

AnalyzeOperations

Test

Specific

Hypothesis

Test

Effectiveness

of Modification

Satisfactory

None

Invalid

Unsatisfactory

Performance Improvement Procedure


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Questions

Why is saturation occurring?

In which parts of the system (CPU, disks,

memory, queues) will a transaction or job be

spending most of its execution time at the

saturation points?

Which are the best cost-effective alternatives

for avoiding (or, at least, delaying) saturation?


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Common Mistakes in

Capacity Planning1. No Goals

2. Biased Goals

3. Unsystematic Approach

4. Analysis Without Understanding the Problem

5. Incorrect Performance Metrics

6. Unrepresentative Workload

7. Wrong Evaluation Technique

8. Overlook Important Parameters

9. Ignore Significant Factors

10. Inappropriate Experimental Design

11. Inappropriate Level of Detail

12. No Analysis

13. Erroneous Analysis

14. No Sensitivity Analysis

15. Ignoring Errors in Input

16. Improper Treatment of Outliers

17. Assuming No Change in the Future

18. Ignoring Variability

19. Too Complex Analysis

20. Improper Presentation of Results

21. Ignoring Social Aspects

22. Omitting Assumptions and Limitations


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Capacity Planning of Steps

1. Instrument the system

2. Monitor system usage

3. Characterize workload

4. Predict Performance under different

alternatives

5. Select the lowest cost, highest

performance alternative

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