Capacity planning2 v02 - STOR2RRD · Microsoft PowerPoint - Capacity_planning2_v02.ppt Created...

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Transcript of Capacity planning2 v02 - STOR2RRD · Microsoft PowerPoint - Capacity_planning2_v02.ppt Created...

Page 1: Capacity planning2 v02 - STOR2RRD · Microsoft PowerPoint - Capacity_planning2_v02.ppt Created Date: 9/26/2012 5:19:18 PM ...
Page 2: Capacity planning2 v02 - STOR2RRD · Microsoft PowerPoint - Capacity_planning2_v02.ppt Created Date: 9/26/2012 5:19:18 PM ...

Agenda

Capacity Planning – practical view

CPU Capacity Planning

LPAR2RRD Premium features

Future

Discussion

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What is that?

Does that save money?

If so then how?

Have you already have an IT capacity manager position and a tool at your company?

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Why do we need capacity planning? To predict future bottlenecks

How to start? Need to have data.

Where to get data? Need to have monitoring in place

What to monitor? Networking (LAN / SAN / WAN)

Memory

Storage

CPU

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Bottleneck on the LAN / SAN is very rare From my experience only backups are able regularly highly utilize

LAN/SAN

When a problem appears then it is usually caused by bad infrastructure design

Fix is usually fast and relatively cheep

new IO cards, network component, trunk …

From capacity planning view it is not major area

Network should never cause a bottleneck! Why?

HW/SW on the network layer is much cheaper than CPU, memory or storage so it should be sized enough

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Usually it is not virtualized like CPU There are exceptions like

▪ IBM PowerVM Active Memory Sharing

▪ VMware Consumption is not so dynamic as CPU

i.e. database memory consumption is fixed by cfg Mem size has usually no effect on SW licensing Easy extending

Nowadays physical limits of memory on servers are usually high enough

Extend can be planned in days after a problem appears

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From capacity planning point of view Storage capacity (size)

Storage throughput (IOPs, Bytes/sec)

Storage capacity Can be relatively simple retrieved and approximated to the future

When no special requirement for throughput then new capacity is relatively cheep

Disk upgrade is usually quick operation

Storage throughput Storage throughput is often reason of bottlenecks

Storage IO bottleneck is usually though to prove or predict

▪ Due to storage caching for example

▪ Solution does not have to be easy (data migration …)

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Can be highly virtualized ( IBM PowerVM, VMware …) Virtualized means shared between virtual partitions

Lack of CPU power or bad virtualization design often cause bottlenecks

CPUs are quite expensive A lot of SW products has licensing based on CPU

Companies should care about number of CPU to do not have to buy unnecessary SW licenses

Accurate capacity planning can directly save money spent for HW and SW

Often happens that servers are fully CPU equipped and cannot be extended Server upgrade and or lpar migration can be long process

All above reasons indicate that CPU is most important from capacity planning point of view

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Next part of presentation will be focused on CPU capacity planning on IBM Power platform

However the product we will talk about can be extended even to Intel world == VMware, Linux Redhat KVM …

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The problem:

How to manage the CPU pools and sub pools on IBM Power Systems▪ Document actual setup

▪ Knowledge of free resources

Determine CPU usage trends

Identify abnormal CPU usage

Manage Capacity

Compare CPU load on different server models for migration purposes

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http://www.lpar2rrd.com/

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Business model

Product is free

Support is for fee

Support levels

Basic

Standard

Premium

Some features are available only for customers under support

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• Light weight solution• Real time and historical data• Easy to implement and manage• Cost effective (free)

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it creates historical, future trends and nearly "real-time" CPU utilization graphs of LPAR's and shared CPU usage of IBM Power servers.

It collects complete physical and logical configuration of all servers & LPAR's.

It is agent less (it gets everything from the HMC/SDMC or IVM).

It supports all kinds of logical partitions:

AIX / AS400 / Linux / VIOS

It is free!!!

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Last 24 hours Last week

Last month Last year

Trend

Main view

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60 second interval reports on CPU usage

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Aggregated graphs

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Memory

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More examples on: http://lpar2rrd.com/aix_iseries_trends.htm

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4 levels of detail

Global view

▪ all HMCs/SDMCs/IVMs, servers, lpars

Summary per each HMC (servers, lpars)

▪ http://lpar2rrd.com/userfiles/file/summary.htm

Detail view per each HMC (servers, lpars)

▪ http://lpar2rrd.com/userfiles/file/detail.htm

Verbose HW details per each server

▪ http://lpar2rrd.com/userfiles/file/server0/config.html

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Shows 10 most CPU utilized lpars per:

All environment

Particular server

Day / week / month / year

Example:

http://lpar2rrd.com/topten.htm

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Live Partition Mobility

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It makes CPU estimation based on historical data

Useful for migration / consolidation

Estimation based on rPerf/CPW benchmark

Live example on

http://lpar2rrd.com/live_demo.html

Doc http://lpar2rrd.com/cpu_workload_estimator_ann.html

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Favourites

It allows you choice typically most important or most often viewed CPU pools or lpars and place them into separated menu for quick access.

You can assign them aliases which then appear under “Favourites" menu

http://lpar2rrd.com/favourites.html

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Custom groups

It allows you group selected lpars or pools from different servers into one aggregated graph

Limitations of free LPAR2RRD version is Max 4 lpars/pools per a group

You can use regular expressions

http://lpar2rrd.com/custom_groups.html

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Alerting

You can define alarms for any CPU pool (or complete server) lpar

Useful especially for pools

Alerting Email Direct Nagios support External script Intergration with others monitoring on a request

http://lpar2rrd.com/alerting.html

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All can be setup within 1 hour!

LPAR2RRD can run on any Unix OS

Disk space requirements are about 4MB per monitored LPAR

Required SW

Any web server

SSH

RRDTools

Perl

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Automated capacity planning and performance analysis

Provides the information needed to help: productively and cost effectively manage their growth and

performance

Ensure uninterrupted availability of system The customer be prepared for IT challenges /

opportunities Maximize return on current and future hardware

investments Easily understand and plan for future requirements

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LPAR2RRD home page http://www.lpar2rrd.com

Monitoring shared processor pools with LPAR2RRD http://www.ibm.com/developerworks/aix/library/au-

lpar2rrd/index.html

Nigel Griffith's LPAR2RRD view https://www.ibm.com/developerworks/mydeveloperworks/blogs/aix

pert/entry/whole_power_server_virtual_server_monitoring_part_2_via_lpar2rrd68?lang=en

Redbook: SAP Applications on a Virtualized IBM Power Systems Environment http://www.redbooks.ibm.com/abstracts/sg247564.html

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Integration with SAP

Use of business data from SAP

Data source for SAP CCMS

Monitor storages (IOps, Bytes/sec …)

IBM DS3/4/5k already under beta

IBM DS8k November 2012

IBM Storewize and others will follow (EMC?)

Batch daily job for identification of lpars which reach max of their configured CPU

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Storage monitoring

Monitoring basic storage parameters

IO rate per controller/port

Data rate per controler/port

Cache hit

Same easy frontend like for CPU

On a click you will find storage utilization

IBM DS4k/5k already in testing phase

IBM DS8k will be ready in November 2012

Other storages will follow on per a request …

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Storage monitoring -Storage I/O rate

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Storage monitoring -Data rate kB/sec

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Questions

Memory monitoring Data retention…