Automated capacity planning and support for enterprise applications
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Automated Capacity Planning and Support for Enterprise Applications. Dharmesh Thakkar School of Computing, Queen’s University, Canada. Performance Activities in The Waterfall SDLC.

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Automated capacity planning and support for enterprise applications

Automated Capacity Planning and Support for Enterprise Applications

Dharmesh Thakkar

School of Computing, Queen’s University, Canada


Performance activities in the waterfall sdlc

Performance Activitiesin The Waterfall SDLC

Verification: Performance test need to be conducted to verify that the required performance objectives are met


Performance activities in sdlc

Performance Activitiesin SDLC

Maintenance: Continuous monitoring, capacity planning and tuning need to be done to ensure that the system continues to meet the performance objectives


Overview of thesis

Overview of Thesis

Challenge: The goal of performance testing is not to find bugs, but to establish benchmarks

Build a capacity calculator based on the performance model

Challenge: Load test and stress test workloads need to be compared against the customer workloads

Modify the workload or the deployment scenario to put excessive stress on one or more system resources

The capacity calculator helps customer determine required hardware resources to support the anticipated workload

Run the application for long periods under high workloads

  • Customers engage the vendor’s support analyst to resolve the issues with system

  • Challenge: The support analyst needs to troubleshoot the customer deployment

  • Performance issues arise in customers’ production environment, which need troubleshooting


Overview of thesis our contributions

Overview of Thesis:Our Contributions

A framework for building performance model based capacity calculator

Presented at the Workshop on Software and Performance (WoSP 2008) Princeton, NJ.

Acceptance rate: 38%

A technique for helping troubleshoot performance issues by retrieving relevant report from a customer engagement repository

Presented at the International Conference on Software Maintenance (ICSM 2008) Beijing, China.

Acceptance rate: 26%


Verification phase an example of a capacity calculator

Verification Phase:An Example of A Capacity Calculator


Building a measurement based capacity calculator

Building a Measurement based Capacity Calculator


Performance modeling challenges

Performance Modeling Challenges

  • Large number of tests to be executed

  • Limited time for performance modeling

  • Manual process of setup, execution and analysis

  • Risk of error and repeating the full modeling process


Addressing the challenges of performance modeling

Addressing the Challenges of Performance Modeling

  • We created the framework to:

    • Automate the process

    • Speed up the process

    • Focus research on specific areas


Framework for building model based capacity calculator

Framework for Building Model based Capacity Calculator

  • Case Studies:

    • Dell DVD Store

    • A large enterprise application


Customization cost

Customization Cost


Maintenance phase customer support

Maintenance Phase:Customer Support


Retrieving relevant reports

Retrieving Relevant Reports

  • State of Practice:

    • No systematic techniques to retrieve and use information for future engagements

    • Keyword searching is limited:

      • depends on the search skills and experience of the analyst and peculiarity of the problem


Customer support problem statement

Customer SupportProblem Statement

  • We want to find customers with similar operational and problem profiles

  • We can reuse prior solutions and knowledge

Other Customers

  • Heavy Email, Light Web, Light calendar

  • Light Email, Light Web, Light calendar

  • Light Email, Heavy Web, Light calendar

  • Heavy Email, Heavy Web, No calendar

  • Light Email, Light Web, Heavy calendar

New Customer Engagement

Compare


Using logs for customer support

Using Logs forCustomer Support

  • Execution logs are readily available and contain

    • Operational Profile: usage patterns (heavy users of email from device, or to device, or light users of calendar, etc.)

    • Signature Profile: specific error line patterns (connection timeout, database limits, messages queued up, etc.)

  • Find the most similar profile


Execution logs

Execution Logs

  • Contain time-stamped sequence ofevents at runtime

  • Readily available representatives of both feature executions and problems

<time> Queuing new mail msgid=ABC threadid=XYZ<time> Instant message. Sending packet to client msgid=ABC threadid=XYZ<time> New meeting request msgid=ABC threadid=XYZ<time> Client established IMAP session emailid=ABC threadid=XYZ<time> Client disconnected. Cannot deliver msgid=ABC threadid=XYZ<time> New contact in address book emailid=ABC threadid=XYZ<time> User initiated appointment deletion emailid=ABC threadid=XYZ


Example

Example

Other Customers

Compare


Technique to retrieve relevant engagement reports

Technique to Retrieve Relevant Engagement Reports


Case studies

Case Studies

  • Case Study I

    • Dell DVD Store open source application

    • Code instrumentation done for event logging

    • Built the execution log repository by applying synthetic workloads, changing the workload parameters each time

  • Case Study II

    • Globally deployed commercial application

    • More than 500 unique execution events


Case study results

Case Study Results

  • Dell DVD Store

    • 100% precision and recall on both operational profile based and signature profile based retrieval

  • Commercial Application

    • 100% precision and recall for signature profile based retrieval

    • Results for operational profile based retrieval:


Sources of errors

Sources of Errors

  • Events that do not correspond directly to a particular operational feature, such as idle time events, server health check events, startup and shutdown events

  • Imbalance in the event logging


Summary our contributions

Summary:Our Contributions

A framework for building performance model based capacity calculator

Presented at the Workshop on Software and Performance (WoSP 2008) Princeton, NJ.

A technique for helping troubleshoot performance issues by retrieving relevant report from a customer engagement repository

Presented at the International Conference on Software Maintenance (ICSM 2008) Beijing, China.


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