smarter z/os infrastructure management

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Smarter z/OS Infrastructure Management with IntelliMagic Vision v8.8

Brent Phillips – Managing Director, AmericasTodd Havekost – Sr. IntelliMagic Consultant

August 24, 2016

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Topics

Modernizing how we process and

understand RMF/SMF IntelliMagic

Vision v8.8 new feature highlights How to identify

unrealized MLC reduction

opportunities

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Commonly Held Assumptions

1. After 30+ years, the RMF/SMF reporting process is matureReality – the greatest potential value in the data is still unutilized

2. SMF is for forensics and trending, no value for real-time Reality – it can provide “sooner than real-time” visibility

3. CPU’s should be run at 100% to maximize cost efficiencyReality – you can optimize cost without compromising on quality

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At IntelliMagic wecreate new intelligence out of your performance and configuration data.

“Any sufficiently advanced technology is indistinguishable from magic”

Arthur C. Clarke, 1962

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Keep the z/OS infrastructure running the application workloadswithout service disruptions and as efficiently as possible:• Prevent: See issues before they can disrupt service and availability

• Resolve: Quickly identify and solve underlying problems

• Optimize: Save cost without risk to performance or availability

• Elevate: Amplify the strengths of the IT team

Your goals?

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• Realize these goals with intelligence from the SMF data, but only if interpreted using embedded expert knowledge:‒ Derive new, meaningful metrics out of the raw SMF data

‒ Throughput limits for internal components

‒ Best practices for configuration and performance management

‒ Balance and redundancy identification

‒ Relationship and interaction of logical and physical resources

Modernizing with Embedded Expert Knowledge

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• Far more powerful than statistical tools that look at anomalies:‒ The lack of interpretation means it can not do predictions

‒ Can suffer from a lot of false positives

‒ Does not help in creating a higher efficiency

• Far more efficient than a human looking through all the data:‒ Human intelligence is powerful, but there simply isn’t enough time

‒ Very ‘boring’ to review every metric/result to find the needle

The Difference

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Performance Today: Either Good or Bad

Unconcerned

Strategic Focus

Panic - Hard to focus

What’s wrong with this picture??

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Performance using Better Intelligence

Unconcerned

Strategic Focus

Panic - Hard to focus

10© IntelliMagic 2014

Time

Response Time

Your existing monitors look at symptoms here,

only after users experience problems

SLA

Perf

orm

ance

Real-time Performance Monitoring

Easy metric to get, but is an effect,

not a cause

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Availability Intelligence identifies risk here, before

response time suffers

© IntelliMagic 2014

Time

Response Time

Sub-component SaturationSL

A Pe

rfor

man

ce

Monitoring with Availability Intelligence

Requires evaluating every data point

with expert domain knowledge about every component

12© IntelliMagic 2014

Time

Response Time Sub-component Saturation

SLA

Perf

orm

ance

Most infrastructure “fires” can be prevented by

intervening here

Avoiding Disruptions

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I/O Performance Example

Storage Array Response

Times

Within Array

Between Arrays

Imbalance?

Application Workloads

Config or Failure

Changes?Disk Device

Loads

FW Bypass, etc.

Back-end,Cache

AdapterUtilization

Fibre Switch Errors

Front-endLag

Measure:

Lead Measures:Lead Measures:

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Automation & the Power of Knowing

• Automatically identify risk in every interval, every device, every data center

• Like a “thousand pairs of eyes”, automated interpretation of what the data means is the only way to continuously achieve ITIL v3 definition of capacity management:

– ensuring…the IT Infrastructure is able to deliver agreed Service Level Targets in a cost effective and timely manner…considers all Resources required to deliver the IT Service...

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IntelliMagic Vision for z/OS Systems

PreventResolveOptimizeElevate

z/OS System•Processor•CECs, LPARs•Specialty Engines (zIIP, zAAP)•Etc

z/OS System•Processor Cache•Relative Nest Intensity•SMF 113 Records•Etc

z/OS System•Paging Reports•Virtual Storage•zEDC /PCI Express •Etc

z/OS System•Workload Manager•Several MIPS/MSU reports•Trending/Comparison•Etc

Coupling Facility/XCF•CF / XCF Health•CF / XCF Analysis•Trending•Etc

Jobs and Datasets•Data Sets•Address Spaces•Trending•Etc

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IntelliMagic for z/OS Disk & Replication


Disk Storage•Front End•Back End•Channels & zHPF•Etc

Disk Replication•Replication Status•Rating Over Time•Verify Balance•Etc

FICON Directors•Director Health•Service Statistics•Channel Health•Etc

Jobs and Datasets•Data Sets•Address Spaces•Trending•Etc

Intelligent Trending•Selected Statistics •Summarized Hourly•Summarized Daily•Etc

Comparison•All Reports•Compare Daily•Compare Weekly, Monthly•Etc

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IntelliMagic Vision for z/OS Virtual Tape


Tape System• Cache• Throttling• Balance• etc

Tape Replication• Send/Receive• Grid Transfers/queues• Balance• etc

Intelligent Trending• Selected Statistics • Summarized Hourly• Summarized Daily• etc

Host Activity• Systems/Jobs/Programs• Volume Groups• Device Groups• etc

Front End• Throughput• Virtual Devices/Mounts• Balance• etc

Back End • Pools• Migration/Recall/Reclaim• Balance• etc

Detailed webinar

overview on Virtual Tape Analytics:

Tuesday August 30:

bit.ly/zvtape

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• Good problem to solve with Software as a Service• Easy Access to intelligence relevant to different roles• Access to IntelliMagic experts for knowledge transfer, analysis• Solution infrastructure is managed for you, creating more focus

IntelliMagic Vision as a Service

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IntelliMagic Vision Homepage

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Embedded Expertise: Infrastructure KRI’s

Focus area: Disk Subsystem, LPAR, CPU, WLM,Virtual Tape, etc.

Performance Metrics

Key Risk Indicators

Automatically identify and rate performance risks and efficiency opportunities with 1000’s of automated health checks

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Embedded Expertise: Quantify good vs bad

Automatically rate existing and new metrics using embedded expert knowledge about z/OS and your infrastructure

to derive intelligence about performance threats and efficiency opportunities

No Border, Opinion N/A

Green Border, Good

Yellow Border, Early Warning

Red Border, Exceptions

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Embedded Expertise: Rate Exception Severity

A three level rating system based on hardware capabilities

A three level, dynamic rating based on both workload

characteristics and hardware

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IntelliMagic Vision v8.8 Highlights

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8.8 z/OS Reporting Enhancements

• Application Groups

• Real and Virtual Storage

• Processor Reporting

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Application Groups

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Application Groups

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Application Groups – Data Sources

• Data sets

• Coupling Facility structures

• Disk volumes

• XCF members

• XCF transmission groups

• Jobs

• Service Classes

• Report Classes

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Real and Virtual Storage Reporting• Virtual storage

• Real storage

• LFAREA / 1MB Pages

• High Virtual Common (HVCOMMON) and High Virtual Shared (HVSHARE) areas

• Storage Class Memory / Flash Storage

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Processor Reporting – Guiding Principles

• Separate reporting of CPU on general purpose CPs from zIIPsand zAAPs

• Use MIPS to refer to the processor capacity rating metric (not in its classic sense of millions of instructions per second)

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Processor Reporting – New Report Sets• Tables and CP Usage

• 4 Hr Rolling Avg and Capping

• LPAR Mgmt and Capture Ratio

• Priority Raised

• Mobile

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Tables and CP Usage• Overview tables and multicharts from "All Processors“ report

set

• WLM Parms table from “WLM Constants” report set

• 2 sets of reports for CPU on general purpose CPs‒ Sequenced by CEC, LPAR, Workload, Service Class‒ First set in units of MIPS‒ Second set in units of Processors

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4 Hr Rolling Avg and Capping (1 of 5)

• New CECs table with data and drilldowns focused on Vertical CP configurations (“polarization”) and LPAR Topology (99.14)

• New LPAR Config table with key metrics for Vertical CP configuration and MLC analysis‒ Physical & Logical CPs, Vertical CP configuration,

LPAR % Weight, Capacity Group, Soft Cap‒ Polarity drilldown shows MIPS by Polarity (VH, VM, VL)‒ Changes drilldown lists changes in Vertical CP config

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• Rolling 4 Hour Average charts - by CEC and LPAR‒ Drilldown compares 4HRA vs. interval RMF CPU usage‒ Further drilldowns by Workload, Service Class, Address Space

• % WLM Capping – critical aspect of MLC Reduction‒ Capping Limited Processor Resources (%)‒ Capping Processor Resources Considered by WLM (%)

• This indicates the time interval when the LPAR's access to CPU was limited and the vertical CP configuration was disrupted

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• % Logical CP Utilization‒ Low utilizations can indicate surplus logical CPs‒ Online Processor drilldown helpful to confirm LPARs where logical CPs

may be over-specified

• CP Weight – CP Usage vs. LPAR Weight (rated)‒ Low values can help identify LPARs that could “donate” weight to

increase Vertical Highs for high-use LPARs

• Logical CP tuning can help optimize Vertical CP configuration and minimize PR/SM overhead‒ 2:1 Logical/Physical is general Rule of Thumb

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• RNI by LPAR‒ Also appears here (in addition to Processor Hardware focal

point) because it is a critical metric for tuning‒ Processor drilldown very helpful to show RNI impact of work

executing on VMs & VLs (after filtering out zIIPs and parked VLs)

• % CPs Vert High – % Physical CPs Defined as Vertical Highs for CEC‒ Workloads executing on Vertical Highs experience improved

processor cache efficiency

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• Polarity CEC - % CP Time Dispatched on Vertical Highs‒ Work executing on Vertical Highs typically has a lower RNI and

thus executes more efficiently‒ Drilldowns by System and MIPS by Polarity

• Dispatch Pol. – Dispatched CP MIPS by LPAR by Polarity‒ Shows MIPS executing on VHs, VMs and VLs for all LPARs‒ Extremely helpful to identify opportunities for RNI tuning‒ By Time and Changes drilldowns also very useful

• WLM Nodes – LPAR Topology from 99.14 records

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LPAR Mgmt and Capture Ratio (1 of 2)

• Improves reporting on PR/SM LPAR overhead

• Phys CP % - Unattributed LPAR Overhead for Physical Partition‒ RMF collects overhead that cannot be attributed to a specific

LPAR and reports in *PHYSICAL* LPAR‒ Expressed as % of entire CEC

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LPAR Mgmt and Capture Ratio (2 of 2)

• CP LPAR Mgmt % - Overhead assigned to an LPAR‒ Expressed as % of that LPAR's total utilization (e.g., attributed LPAR

overhead of 0.5% of CEC for LPAR that consumed 10% of CEC would be 5% on this report)

‒ Capture Ratio drilldown compares LPAR Mgmt % vs. RMF capture ratio (typically an inverse relationship, lower LPAR Mgmt % correlates to higher RMF capture ratio)

• CP Capt % - CP Capture Ratio‒ General purpose CPU time captured in RMF 72.3 (and assigned to

service classes) as % of total general purpose CPU consumption per RMF 70, by system

‒ Drilldown to compare against LPAR Mgmt %

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Processor Reporting – New Report Sets• Tables and CP Usage

• 4 Hr Rolling Avg and Capping

• LPAR Mgmt and Capture Ratio

• Priority Raised – WLM raising priority of tasks holding resources other tasks are waiting for

• Mobile – New WLM capability to classify activity originating from mobile devices

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8.8 z/OS Reporting Enhancements

• Application Groups

• Real and Virtual Storage

• Processor Reporting

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How to Identify Unrealized MLC Opportunities

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• FTP RMF/SMF data to IntelliMagic• IntelliMagic will analyze and identify opportunities• You get access to logon and explore your data

MLC Assessment Service