Agenda. Capacity Planning practical view CPU Capacity Planning LPAR2RRD LPAR2RRD. Discussion. Premium features Future

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2 Agenda Capacity Planning practical view CPU Capacity Planning LPAR2RRD LPAR2RRD Premium features Future Discussion

3 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?

4 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

5 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

6 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

7 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 )

8 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

9 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

10 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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12 Business model Product is free Support is for fee Support levels Basic Standard Premium Some features are available only for customers under support

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

14 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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16 Main view Last 24 hours Last week Last month Last year Trend

17 60 second interval reports on CPU usage

18 Aggregated graphs

19 Memory

20 More examples on:

21 4 levels of detail Global view all HMCs/SDMCs/IVMs, servers, lpars Summary per each HMC (servers, lpars) Detail view per each HMC (servers, lpars) Verbose HW details per each server

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23 Shows 10 most CPU utilized lpars per: All environment Particular server Day / week / month / year Example:

24 Live Partition Mobility

25 It makes CPU estimation based on historical data Useful for migration / consolidation Estimation based on rperf benchmark Live example on:

26 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

27 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

28 LPAR2RRD home page Monitoring shared processor pools with LPAR2RRD Nigel Griffith's LPAR2RRD view xpert/entry/whole_power_server_virtual_server_monitoring_part_ 2_via_lpar2rrd68?lang=en Redbook: SAP Applications on a Virtualized IBM Power Systems Environment

29 Integration with SAP Use of business data from SAP Data source for SAP CCMS VMware porting Only for capacity monitoring purposes Cross platform CPU estimations IBM Power / Intel Alerting and notifications (Q3 2012) Non linear data approximation into the future Monitor storages (IOps, Bytes/sec)

30 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 Q Other storages per request

31 Storage monitoring - Storage I/O rate

32 Storage monitoring - Data rate kb/sec