Dugi2014

Dugi2014

Milan, 8th April 2014Rome, 9th April 2014

System Z Performance & Capacity Management using TDSz and DB2 Analytics Accelerator:

UnipolSai Customer Experience

Marina Balboni & Roberta BarnabéSystem Z Transactions and Data Area, UnipolSai

Francesco BorrelloTechnical Sales and Solutions – IBM Sales & Distribution, Software Sales

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Agenda

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6

Customer Environment

Customer needs – Pain points

IBM Proposal: Capacity Management Analytics

UnipolSai implementation

Final results

Next steps

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Agenda

1

2 3 4 5 6

Customer Environment

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Who is UnipolSai

• Second Insurance Group in Italy, first in Non-Life business

• Total premiums of €15.4 billions

• About 15000 employees

• Company with the biggest number of branches in Italy

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UnipolSai Hardware Technical Environment

2 IBM 2827-H20 (707 + 704)

707Production & Development (ex Unipol) :

o 7 GP + 3 zIIP + 6 zAAP + 1 ICFo 512 GB Memoryo 1092 MSU – 8954 MIPS

704Production (ex Fonsai):

o 4 GP + 1 zIIP + 1 zAAP + 1 ICF o 512 GB Memoryo 664 MSU – 5409 MIPS

14363MIPS

1756MSU

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UnipolSai Hardware Technical Environment

Appliance:o IBM DB2 Analytics Accelerator for z/OS: N1001-05

Storage MGM Configurationo DS8870 DS8800 MM (Sync – second site) o DS8800 DS8700 GM (Async – third site)o 2 X (TS7720, TS7680) Virtual Tape + TS3500 Real Tape

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UnipolSai Hardware Technical Environment

Disaster Recovery Site

IBM 2817- M15o 7 GP processorso 1 zIIP SEo 5 zAAP SEs o 1 ICF  o 165 GB Memory

Three sites configuration

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UnipolSai Mainframe Technical Environment

z/OS version 1.12

DB2 version 10 NFM (Data Sharing Implementation on going)9 Subsystems

IBM DB2 Analytics Accelerator V3.1 (Migration to V4 on going)

CICS TS 4.250 Subsystems9 million transactions/daily

WAS 8.5.5 + WAS 8.5.5 on z/OS 11 Application Servers (2 clustered)

6.5 million threads/daily

WebSphere MQ 7.0.1

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UnipolSai Application Environment

• Cobol Cics/Batch – Static and Dynamic• Assembler• JAVA (SQLJ/JDBC)• DELPHI (ODBC) on Workstation• Visual Basic - .NET on Workstation

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Agenda

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2

3 4 5 6

Customer needs – Pain points

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Customer Needs – Pain Points

• SMF is preferred source of statistics information helping System Z capacity management, but:

Lack of a unique tool for collecting SMF data Several monitors with overlapping functionalities Poor quality Redundancy High complexity in correlating data

Lack of system resources for collecting detailed information DB2 for zOS V10 gives some relief allowing SMF data compression

Need of saving huge amount of historical SMF data Storage issue Performance and trend analysis

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Customer Needs – Pain Points

• Solution should follow cost reduction directive, so the consumption of MIPS and use of storage should be reduced and kept as small as possible Complex analysis show elapsed time and cpu consumption issues

• Improvement in the existing user interface should be provided, allowing to: Intuitive navigation and easy-to-use tools Scheduling and ease of distribution Different report output formats

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Agenda

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3

4 5 6

IBM Proposal: Capacity Management Analytics

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Capacity Management Analytics – Core Architecture

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IBM Cognos BI

Cognos Business Intelligence provides the range of analysis capabilities necessary for optimizing zEnterprise use by confidently and simply compiling the information necessary to understand and manage system activity while significantly improving the ability to identify potential issues and pinpoint their cause.    

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IBM SPSS Modeler

SPSS Modeler

can help you use predictive analytics to forecast future requirements for zEnterprise and ensure the capacity required is available when the business needs it

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IBM Capacity Management Analytics Solution Kit

• Pre-built interactive reports and models Several COGNOS reports (CPU, WLM, Memory) SPSS predictive analytics model that forecast LPAR CPU usage

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IBM DB2 Analytics Accelerator: Faster Analysis

• What does it do?– Base forecasts off larger samples of historical

SMF data to improve accuracy of predictive models

– Dramatically accelerate the analysis of your zEnterprise usage & performance data

– Significantly speed up complex queries of the large volumes of data that are being created by zEnterprise.

– Lower the cost of long-term storage of large volumes of historical SMF data with a high-performance storage saver feature

IBM DB2 Analytics Accelerator What is it?

• A high performance appliance that speeds analysis, enabling you to base your projections on a larger sample of historical data

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IBM DB2 Analytics Accelerator: HPSSReducing the cost of high speed storage

• Time-partitioned tables where:– only the recent partitions are used in a transactional context

(frequent data changes, short running queries) – the entire table is used for analytics (data intensive, complex

queries). • DB2 partitions are deleted after the High Performance Storage Saver are

created on the accelerator

DB2#1

Accelerator #1

Query from Application

Or

Accelerator #2

Accelerator #3

Accelerator #4

Accelerator #5

Accelerator #6

Accelerator #7

No longer present on DB2 Storage

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Agenda

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4

5 6

UnipolSai implementation

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Overview of UnipolSai Solution Architecture

DB2

TDSz

SMF logs

Cognos

Most recent data (7-30 days) <= 1TB

NNN weeksstored in HPSS

Reports

Most recent data(7-30 days)

+

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The Plan to Implement the Designed Solution

• Phase 1: Setup & Configuration Setup of TDSz and Cognos environments

• Phase 2: Test TDSz and Accelerator Synergy Evaluate IBM DB2 Analytics Accelerator V3.1 functionalities Evaluate performance and consumption benefits

• Phase 3: Speed up and Archive Tables partitioning and archiving Batch alignment of data on the Accelerator Force queries to execute on the Accelerator

• Phase 4: Implement a complete automated process

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Phase 1: Setup & Configuration

• SMF record types collected via TDSz z/OS, DB2, CICS, WAS, MQ Configured both tables with detailed data (timestamp or hour) and tables

with aggregated measures

• COGNOS: setup and connection to TDSz DB2 for zOS database Migration of existing reports and definition of new ones

Installation of TDSz provided reports Migration of existing reports to COGNOS format with graphs and/or columnar

data Development of new local reports to satisfy new requirements

Reports scheduling and automatic distribution inside UnipolSai Schedule of predefined reports with output in different formats, mainly PDF Automatic distribution of reports to defined users Automatic publication of reports in Intranet Website

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Phase 2: Test TDSz and Accelarator Synergy

• Evaluate IBM DB2 Analytics Accelerator V3.1 basic functionalities in a Test Environment Add and load some tables on the Accelerator Test sample queries execution on the Accelerator

• Evaluate TDSz and IBM DB2 Analytics Accelerator synergy Identification of a Test Environment with a few TDSz data Identification of some TDSz critical reports and queries Add tables, load data on the Accelerator and execute test cases

• Evaluate performance and consumption benefits in Production Environment Identification of the most critical queries in terms of elapsed time and

MIPS consumption to be used for benchmarking Forcing execution on IBM DB2 Analytics Accelerator

SET CURRENT QUERY ACCELERATION ELIGIBLE;

Analyze results From almost 4 hours to 1 second

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Phase 3: Speed up and Archive

• Identification of TDSz tables for partitioning Efficient loading and archiving purposes Choice of partitioning criteria (time criteria)

Partitioning by month for tables with detailed data Partitioning by year for tables with aggregated data

• Partition TDSz tables Drop and re-create Archive tables (on going)

• Development of REXX program for batch data alignment on the Accelerator Only modified partitions or tables

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Phase 3: Speed up and Archive

• Configure Cognos for forcing both reports development and reports execution on the Accelerator

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Phase 4: What about a complete automated process?

• Implementing a complete automated process which consists of the following steps orchestrated by Tivoli Workload Scheduler (TWS):

Disable TDSz accelerated tables Mandatory only if QUERY_ACCELERATION zPARM is different from NONE

Start TDSz tasks for collecting SMF data and saving extracted information on DB2 for zOS

Invoke REXX batch program for loading only modified TDSz partitions or tables after collecting operations

Enable TDSz tables on the Accelerator Trigger Cognos reports execution and distribution

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Agenda

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5

6

Final results

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Cognos Reports: Measured Elapsed Time

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Cognos Reports: Measured CPU Time

• CPU consumption comparison between the two following scenarios: Scenario 1: all reports queries execute against DB2 Scenario 2: all reports queries execute against IBM DB2 Analytics

Accelerator

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Some Numbers about Space Usage

PDT_OBJECT_150 is not included in the graph, as it's too big and it's out of scale

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Load Operations: Measured Elapsed and CPU Time

• 3 Jobs Output: End of month elapsed and cpu time

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Ease of Sharing within UnipolSai

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Ease of Sharing within UnipolSai: Report Visualization

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… Just Another Example of Cognos Report Output

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Agenda

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6 Next steps

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Next Steps: Ideas for the future we're working on

• Use only TDSz tables containing detailed data Avoid to update TDSz tables containing aggregated measures All the aggregated measures will be calculated on the fly by DB2 Analytics

Accelerator

• Use of SPSS to forecast resource requests SPSS can forecast future capacity to ensure the capacity is available to

satisfy business needs

• Use of IBM DB2 Analytics Accelerator V4 (Migration on going) Performance improvements Archive operations improvements (automation of previous archive

operations) Static SQL

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Acknowledgements

Fabio Riva, zChampion, zStack Advocate, zClient Architect, IBM Italy

Fabio is a Senior IT Architect in SWG IBM Italy. Joining IBM in 1985, he covered different positions inside the company, from MVS SysProg to Systems Engineer, up to Senior IT Architect. During the last years his main activities were related to business development on System z. Fabio followed the development of cross-platform (hybrid) solutions, having the main focus on mainframe platform. He's also supporting some Tivoli products in the areas of SW asset, licence, and cost management on System z. Fabio published several publications inside IBM, but also articles on external newspapers. He acted also as a speaker at several international conferences and technical user groups.

Francesco La SalaSenior Consultant - 5EMME INFORMATICA S.p.A

Francesco is a Senior Consultant in “5EMME INFORMATICA S.p.A.” and he’s providing a great contribution to CMA project with UNIPOLSAI customer. His areas of specialization are in Tivoli (now CS&I) software brand, in particular regarding the product TDSz (Tivoli Decision Support for z/OS). He has deeper knowledge also in DB2 area, in particular on IBM DB2 Analytics Accelerator appliance.

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Thank you for your attention!