Evaluating Transaction System Performance
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Evaluating Transaction System Performance Using Real Workloads. Ashutosh Tiwary Co-Founder and CTO www.performant.com. Performance is a real problem. IT projects fail due to multiple reasons Performance is an important component Application complexity is growing dramatically

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Ashutosh tiwary co founder and cto performant

Evaluating Transaction System Performance

Using Real Workloads

Ashutosh Tiwary

Co-Founder and CTO

www.performant.com

Confidential & Proprietary to Performant, Inc.


Performance is a real problem

Performance is a real problem

  • IT projects fail due to multiple reasons

    • Performance is an important component

  • Application complexity is growing dramatically

    • Many layers of opaque 3rd party components

    • More and more IT developers know about less and less

  • Deploying scalable J2EE applications is hard

    • 12 SUN CPUs, 12 GB J2EE App server performance?

  • Packaged apps have their own challenges

    • $10M - $1B spent on deployments


Performance problem examples

Performance problem examples

  • Inability to recreate real world problems

    • “Our frustration is that we cannot recreate the production problems in our test environment”(Director of Performance Testing)

  • Inability to anticipate problems with current tools

    • “Why did we not find this problem with our load testing before we deployed the application?”(VP Engineering)

  • Inability to predict future performance

    • “Will our current system be able to handle the anticipated load for next 24 months?”(VP Information Systems)


Real workload approach

Transaction from User

Manipulation

HTTP Requests

REPOSITORY

WEB SERVER

Capture

JSP Requests

Performance Data

Correlation

P

P

Playback

APPLICATION

EJB Requests

P

P

P

Performance Data

APPLICATION SERVER

JDBC Requests

P

Performance Data

P

P

P

P

DATABASE SERVER

Real Workload Approach

A new approach

Real workload instead of synthetic

Diagnose and fix performance problems in production systems

A view inside the application while under load – detailed analysis

Automated application instrumentation


Current implementation optibench

Current implementation: OptiBench

  • HTTP Instrumentation using plug-ins

    • Support major web servers with minimal overhead (1-5%)

  • Automated byte code instrumentation of Java interfaces for J2EE applications

    • JSP and JDBC on major application servers

    • Insert byte-code into Jar files, minimal execution overheads (1-7%)

    • General purpose automated instrumentation technique that can instrument J2EE and potentially MS .NET interfaces

  • Multi-user and distributed capture, analysis and playback of workloads

    • Test management, data analysis

    • Correlation of system and application metrics with workloads


Sample usage scenarios

Sample Usage Scenarios

  • Solving production performance problems

  • Load testing with a view inside the application

  • Scaling and capacity planning

  • Benchmarking


Production problem solving

Production Problem-Solving

EXISTING

SYSTEM

DEVELOPMENT

SYSTEM

TEST

SYSTEM

PERFORMANCE

SERVER

Workload &

Performance

WORKLOAD

CODE FIXES

PERFORMANCE

Triggers

  • Process:

  • Instrument application and deploy to production

  • Set workload capture thresholds using monitoring systems. Capture workload and state when problem occurs.

  • Playback the workload to recreate the problem in the test environment to diagnose and fix it.

  • Replay the workload with the code fixes to validate that the problem is solved

  • Deploy the fixed code to production

Monitoring

System

OptiBench

Console

Monitoring

Console


Conclusions

Conclusions

  • Innovative technology and shipping product

    • Recording, playback, and correlation of real production workload with low overheads

  • Addresses real performance problems for customers

    • Product currently being deployed at major customer sites


Ashutosh tiwary co founder and cto performant

Confidential & Proprietary to Performant, Inc.


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