DB2 Optimization Service - Boost application performance while cutting costs
AppBuilder Solutions is providing a service to optimize DB2-based Mainframe z/OS applications
and improve their performance.
Doing more with less !!!
> Cutting costs by reducing the amount of MIPs consumption.
> Improved batch performance – shrinking batch window is achieved.
> Improved on-line transactions – faster on-line application providing better service to your application’s end- users
> Improved maintenance - Minimize the amount of database dead locks
> Reduced back-up time and Mainframe resources
> Improve efficiency of DBA and system teams
About our service offering
We are using a state of the art tool that automatically analyzes huge amounts of database tables, data structures, SQL statements
and code. Using such automatic tool enable us to perform analysis that is impossible to achieve manually.
Our service is performed by a seasoned team, comprised of highly experienced IT professionals with proven record in performance
optimization initiatives and in-depth database-related knowledge.
Our methodology is comprised of the following steps :
The service is based on a combined and comprehensive analysis of various application components. Our performance analysis
covers the main aspects of a DB2-based application where mainframe resources can be saved which are:
1. Application code
2. SQL commands
3. DB2 data structures
Our analysis highlights performance sinks through the identification of suboptimal DB2 model-structures, code patterns and
Generation of recommendations
As a result of this analysis, a list of recommendations for remediation steps is generated, providing schema AND specific code changes recommendations.
The analysis, that scans large data volumes and diverse code structures, provides a list of recommendations that covers all
the DB2-dependent aspects of the application.
Each identified problem is accompanied with specific information revealing the exact root cause of the problem.
The specific table/filed/index/sql statement/code lines are provided together with the appropriate change that should to be
implemented in order to fix the problem.
Prioritization of recommendations
Once the analysis is done hundreds of issues for performance improvement might be discovered. In order to be able to
manage all those issues we prioritize them according to their CPU saving and simplicity of the implied fix.
The severity of each issue is being prioritized, while the worst offenders get the highest priority for change.
The implementation of the fixes is done according to the specific priority of each recommendation.
Thus, fixes that are simple to implement and yield significant performance improvement will be implemented first,
allowing starting benefiting the performance improvement as soon as possible.