© 2009 IBM Corporation
Capacity Management, Demand Management, and Performance Engineering Integration
Ann Dowling
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The Capacity Management Process is comprised of six key Activities.
Establish Capacity Management Framework: Based on the business and IT strategy and the architectural models, guidelines and a framework for capacity management will be developed.
Model and Size Capacity Requirements: – Modeling involves performance and capacity prediction through estimation, trend analysis,
analytical modeling, simulation modeling and benchmarking. Application sizing is a technique that predicts the capacity solution required to meet service level requirements for response times, throughput, and batch elapsed times.
Monitor, Analyze, and Report Capacity Usage: – Monitors should be established on all the components and for each of the services. The data
should be analyzed using, wherever possible, expert systems to compare usage levels against thresholds. The results of the analysis should be included in reports, and recommendations made as appropriate.
Supervise Tuning and Capacity Delivery: – Outputs from monitoring, analyzing, and reporting activities are examined and actions to tune
individual resources or to re-balance the available capacity are planned and initiated through Change and Release Management.
Produce and Maintain Capacity Plan: – The objective of this activity is to develop, maintain, test and revise alternative approaches in
satisfying various enterprise-shared resource requirements. It delivers the capacity plan that addresses the customer's resource requirements.
Evaluate Capacity Management Process Performance: Measurements include the definition, collection of measurements, analysis, review and reporting for Capacity Management.
Managing
the
Process
Managing
the
Process
Executing the
Process
Executing the
Process
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There are three sub-processes that comprise the ITIL® Capacity Management process. Each uses the primary activities of the process decomposition in differing ways, to differing stakeholders, to differing end results.
Business Capacity Management (BCM) translates business needs and plans into requirements for service and
IT infrastructure, ensuring that the future business requirements for IT services are quantified, designed, planned and implemented in a timely fashion
Service Capacity Management (SCM) management, control and prediction of the end-to-end performance and
capacity of the live, operational IT services usage and workloads
Component Capacity Management (CCM) management, control and prediction of the performance, utilization and
capacity of individual IT technology components
"ITIL ® is a Registered Trade Mark, and a Registered Community Trade Mark of the Office of Government Commerce, and is Registered in the U.S. Patent and Trademark Office"
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Elements of Demand Management are the main source of business demand that Capacity Management uses to develop capacity forecasts and solutions.
Excerpted from “Service economics” chapter of itSMF publication for ITIL® V3 core documents, 2008-12-15.
Conceptual View
Note: IBM provides additional process guidance supporting Demand Management and other ITIL processes.• IBM Tivoli Unified Process (ITUP)
Business processes are the primary source of demand for services.
Patterns of business activity (PBA) influence the demand patterns seen by the service providers (Figure5.23)
It is very important to study the customer’s business to identify, analyse and codify such patterns to provide sufficient basis for Capacity Management.
Visualize the customer’s business activity and plans in terms of the demand for supporting services
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And…add ITIL V3 Service Strategy Demand Management for ‘sense and respond’ alignment with client Business Transformation
ITIL® Demand Management Key Activities:
Establish Demand Management framework
Value and classify business demands
Consolidate business demand patterns and forecasts
Forecast service demand
Identify and plan demand management initiatives
Assess and report demand management outcomes
Evaluate demand management performance
Capacity Management translates demand through to the component level.
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Several tasks in the Demand Management process need to be driven by the Capacity Management team in order to initiate progress toward improved capacity requirements and forecasts.
Demand Mgmt. Key Activity
Demand Mgmt. Task
Relationship with Capacity Management
Note: This is a minimal subset to provide input to Capacity Management for Demand Management
Value and Classify Business Demands
Identify and Analyze Business Demand Streams and Demand
Work with business areas to gather business demand information, analyze types of demand in business terms and obtain trend of the demand - For customers of IT, internal and external
Forecast Service Demand
Create Business Demand Forecasts
Work with business areas to create forecasts of business demand for major business areas
Assess & Report Demand Mgt.
Identify Service Demand Baselines
Determine existing baselines for service demand. for given business areas
Forecast Service Demand
Translate Service Demand to Service Consumption Units
Convert service demand into service consumption units for the business areas
Forecast Service Demand
Translate Business Demands to Service Demands
Take business demand data and results and identify demand for specific IT services
Forecast Service Demand
Create Service Demand Forecasts
Take the Service Demands and create forecast for the required IT services (input to “Model and Size Capacity Requirements” and “Produce and Maintain Capacity Plan”
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IBM leverages its Performance Engineering and Management Method (PEMM) for its engagements.
PEMM was first outlined in 1998 in an IBM internal white paper, as a comprehensive approach to addressing performance throughout the lifecycle of a custom application development (CAD) project.
It was developed into a comprehensive method with full elaboration of the eight major Themes, supporting Work Products, exploration of the Role of the Performance Architect and the mult-disciplinary Performance Engineering Team
In addition to the traditional disciplines of performance testing and performance/capacity planning and management, PEMM stresses the need for proactive performance engineering tasks which should be taking place during earlier project phases (i.e. requirements, architecture, design & development) and managing the scalability, capacity and performance in the production environment.
PEMM is the basis of an internal IBM course on “Architecting for Performance” that is included in the education roadmap for the IBM Architect Profession.
PEMM has been customized by IBM on multiple engagements across several industries, including several large Insurance industry clients.
The three dimensions of Performance Engineering:• The project Phases and deliverables dimension defined in your project development
standards• The People dimension in which you build and maintain your relationships with other key
members of the project and within the Performance Engineering team itself.• The Themes dimension in which you maintain and drive forward the longer conceptual
threads of activity needed to help you achieve your objectives.
THEMES
PHASES
PE
OP
LE
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The PEMM themes apply across the life cycle and produce a set of outputs also shared and refined throughout the life cycle. PEMM directly maps to YOUR life cycle and beyond into Introduction and Deployment.
Software Development Life Cycle
Startup DeploymentSolution
CloseSolution OutlineMacro Design
Micro Design
BuildSolution Requirements
Volumetrics
Performance Estimation and Modeling
Performance Testing and Validation
Live Monitoring and Capacity Management
Technology Research
Ou
tpu
ts
Requirements and Early Design
Design, Development, and Tracking
Risk and Performance Management
performance engineering activities completed in the earliest part of the project to ensure performance and capacity requirements are well-defined and assessed at the outset
analyzing the quantitative (volumes) factors, both business and technical, that will effect system performance
activities associated with predicting future performance behavior or capacity requirements of a system
PE Strategy Non-Functional
Requirements Business Volumetrics PE Risk Assessment
and Containment Plan
investigation required to make estimation and modeling more accurate and fact-based
PE activities conducted during the development life cycle include supporting design and code reviews and establishing performance time or resource utilization budgets
test and assess the performance of the live solution, usually by an independent performance test team
manage performance and capacity of the deployed solution in production, using monitoring tools and processes and service level agreements
ensure risks related to performance and capacity are properly identified, assessed and addressed
PE Plan Performance Critical
Use Cases Technical Volumetrics Performance Budgets Performance Model
Application Profiles Capacity Sizing Monitoring Plan Performance Test
Cases
►Performance Engineering and Management Method
Measurement Specifications
Performance Analysis Results
Tuning Recommendations
Performance Service Levels Monitoring Thresholds/Alerts Implemented Tuning Capacity Plan Capacity Plan vs. Actual reports
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Business
Service
Component
Integration points foster mutual awareness and collaboration between the Capacity Management process and Performance Engineering themes which mutually strengthens the overall effectiveness.
Capacity Management view as embodied in ITIL and IBM’s ITUP
(Service Management perspective)
Performance Engineering view as embodied in PEMM
(Solution Design and Delivery perspective)
Capacity Planning for a future system deployment
Capacity Management for a deployed system
Performance Engineering of a solution being developed and/or assembled
Performance Management of a solution being deployed
Model and size capacity
requirements
Monitor, Analyze and Report
Capacity Usage
Supervise Tuning and Capacity
Delivery Produce and maintain capacity
plan
Requirements and Early Design
Volumetrics
Estimation and
ModelingTechnolog
y Research
Design, Developmen
t and Tracking
Test Planning
and Execution
Live Production
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The convergence of Capacity Management, Demand Management, and Performance Engineering (PEMM) provides a powerful and truly full life cycle methodology.
Demand Management
Patterns of Business Activity and Demand
Policies
Performance Engineering Risk Assessment Non-Functional Requirements
Performance Model
Capacity Management Information System &
Capacity Plan
Performance Engineering & Management Method(PEMM based)
Capacity Management Process(ITIL® based)
Feasibility Design Development Test Deploy Production Optimize
• IBM’s Performance Engineering & Management Method (PEMM)
• IT Infrastructure Library (ITIL®)
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Model and Size Capacity Requirements
Model and size capacity
requirements
Monitor, Analyze and Report
Capacity Usage
Supervise Tuning and Capacity
DeliveryProduce and
maintain capacity plan
Requirements and Early Design
Volumetrics
Estimation and
Modeling
Technology Research
Design, Development and Tracking
Test Planning and
Execution
Live Production
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Model and Size Capacity Requirements
Modeling involves performance and capacity prediction through estimation, trend analysis, analytical modeling, simulation modeling and benchmarking. Modeling can be performed for all or any layer of the IT solution including the business, application and technology infrastructure.
Application sizing is a technique that predicts the service level requirements for response times, throughput, and batch elapsed times.
It also:• predicts resource consumption and cost implications for new or
changed applications
• predicts the effect on other interfacing applications.
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Modeling involves one or more techniques must be selected when modeling workload behavior and associated resource requirements.
Modeling Objectives:
– Predict the behavior of IT Services under a given volume and variety of work using:• Pilot studies• Prototypes• Full scale benchmarks• Trend analysis• Analytical modeling• Simulation modeling• Baseline models
Like modeling and forecasting during a solution development project:
– No single technique can apply to all situations
– One or more techniques must be selected when modeling workload behavior and associated resource requirements
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Application Sizing Objectives– Estimate resource requirements for new or changed application– To ensure it meets required service levels– Has to be an integral part of the applications lifecycle
Application sizing has a finite life-span– Initiated at Project Initiation stage for a new application– Major Change to an existing Application– It is performed at the beginning of the solution lifecycle and continues
through the development, testing and implementation phases. Service Levels defined
– During initial systems analysis and design– Enables use of pertinent technologies & products– Easier and less expensive to consider early in application lifecycle
Modelling can be used within Application Sizing Applies to Application Packages (COTS):
– Research similar customers & do benchmarks
Application Sizing has a strong correlation with Performance Engineering.
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Forecast Accuracy
Co
st &
Tim
e
FullProduction
Test
AnalyticModel
SimulationModel
Testing +Simulation
ModelTesting +AnalyticModel
ScalabilityTesting
LinearExtrapolation
The Testing / Modeling Continuum is a guide to determining which forecasting technique should be used in a particular situation.
+/- 10~15% +/- 5~10%
Benchmark
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Capacity modeling can be utilized to project the infrastructure requirements for any production or test based application.
Basic Capacity Planning (Scalability) Methodology Identify key workloads / transactions and develop a performance metric
collection strategy Collect performance and configuration data required to construct the models Create and calibrate the model to base system metrics Utilize the calibrated baseline model to project future business scenarios Analyze modeling results and identify application and infrastructure
requirements Create and deliver final report and softcopy performance models
Model Projections
0
20
40
60
80
100
100 150 200 250 300 350 400 450
Total Users
CPU
Util
izat
ion
(%)
0
5
10
15
20
Res
pons
e Ti
me
(sec
) Server1
Server2
Server3
Tran1
Tran2
Time in Seconds Application NetworkApp Transaction RespT ProcT NetT App Turns AppMsgs AppData NetPkts NetData
CTC 1a (Total) 0.27 0.08 0.19 11 13 18,835 44 25,598CTC 4b (Total) 2.49 2.47 0.01 91 92 274,854 522 348,122CTC 7a (Total) 3.04 3.02 0.03 23 25 284,361 493 333,321CTC 8a (Total) 4.70 4.67 0.02 23 25 284,945 495 336,933CTC 11b (Total) 1.41 1.36 0.01 132 136 183,193 440 245,781Dealer KPI 15a (Total) 0.06 0.06 0.00 11 16 11,825 26 13,259Dealer KPI 21a (Total) 3.16 3.14 0.02 775 863 242,527 1,034 298,943Dealer KPI 22a (Total) 0.19 0.17 0.02 75 198 264,036 447 288,924Dealer KPI 29a (Total) 1.87 1.84 0.03 3,905 3,924 184,708 3,933 397,158SAS Enterprise Guide 34b (Total) 38.97 38.53 0.44 1,312 2,621 878,389 4,010 1,104,002SAS Enterprise Guide 39a (Total) 276.00 275.16 0.84 2,032 4,019 827,170 5,605 1,145,303SAS Enterprise Guide 45a (Total) 1.61 1.45 0.16 438 878 250,614 1,297 324,043SAS Enterprise Guide 51a (Total) 238.07 237.72 0.34 530 1,045 272,794 1,526 360,396VPIPE 54a (Total) 0.19 0.19 0.00 29 31 6,220 36 8,208VPIPE 57a (Total) 4.06 4.06 0.00 5 8 4,909 13 5,641VPIPE 59a (Total) 30.32 30.32 0.01 109 121 58,588 161 67,522VPIPE 61a (Total) 106.41 105.73 0.67 16,928 16,959 7,528,632 20,739 8,671,263DRBA 67a (Total) 0.14 0.14 0.00 3 4 3,875 7 4,265DRBA 71a (Total) 139.43 139.23 0.19 3 4 3,579 9 4,089DRBA 75a (Total) 7.49 7.49 0.00 3 4 544 7 940DRBA 79a (Total) 0.95 0.95 0.00 3 6 4,909 13 5,641
Time in Seconds Application NetworkApp Transaction RespT ProcT NetT App Turns AppMsgs AppData NetPkts NetData
CTC 1a (Total) 0.27 0.08 0.19 11 13 18,835 44 25,598CTC 4b (Total) 2.49 2.47 0.01 91 92 274,854 522 348,122CTC 7a (Total) 3.04 3.02 0.03 23 25 284,361 493 333,321CTC 8a (Total) 4.70 4.67 0.02 23 25 284,945 495 336,933CTC 11b (Total) 1.41 1.36 0.01 132 136 183,193 440 245,781Dealer KPI 15a (Total) 0.06 0.06 0.00 11 16 11,825 26 13,259Dealer KPI 21a (Total) 3.16 3.14 0.02 775 863 242,527 1,034 298,943Dealer KPI 22a (Total) 0.19 0.17 0.02 75 198 264,036 447 288,924Dealer KPI 29a (Total) 1.87 1.84 0.03 3,905 3,924 184,708 3,933 397,158SAS Enterprise Guide 34b (Total) 38.97 38.53 0.44 1,312 2,621 878,389 4,010 1,104,002SAS Enterprise Guide 39a (Total) 276.00 275.16 0.84 2,032 4,019 827,170 5,605 1,145,303SAS Enterprise Guide 45a (Total) 1.61 1.45 0.16 438 878 250,614 1,297 324,043SAS Enterprise Guide 51a (Total) 238.07 237.72 0.34 530 1,045 272,794 1,526 360,396VPIPE 54a (Total) 0.19 0.19 0.00 29 31 6,220 36 8,208VPIPE 57a (Total) 4.06 4.06 0.00 5 8 4,909 13 5,641VPIPE 59a (Total) 30.32 30.32 0.01 109 121 58,588 161 67,522VPIPE 61a (Total) 106.41 105.73 0.67 16,928 16,959 7,528,632 20,739 8,671,263DRBA 67a (Total) 0.14 0.14 0.00 3 4 3,875 7 4,265DRBA 71a (Total) 139.43 139.23 0.19 3 4 3,579 9 4,089DRBA 75a (Total) 7.49 7.49 0.00 3 4 544 7 940DRBA 79a (Total) 0.95 0.95 0.00 3 6 4,909 13 5,641
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Monitor, Analyze, and Report Capacity Usage
Model and size capacity
requirements
Monitor, Analyze and Report
Capacity Usage
Supervise Tuning and Capacity
DeliveryProduce and
maintain capacity plan
Requirements and Early Design
Volumetrics
Estimation and
Modeling
Technology Research
Design, Development and Tracking
Test Planning and
Execution
Live Production
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Monitor, Analyze, and Report Capacity Usage
Monitors should be established on all the components and for each of the services.
The data should be analyzed using, wherever possible, expert systems to compare usage levels against thresholds.
The results of the analysis should be included in reports, and recommendations made as appropriate.
There is a fundamental level of data collection and reporting necessary in any environment before capacity and performance services can be established.
Monitors and Data Collection and Reporting suites might be required at many levels, including but not limited to, the operating system, the database, the transaction processor, middleware, network, Web Services, and end-to-end (user) experience.
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Objectives of Monitoring and Analysis
Monitoring objectives:Measure the utilization of each resource and service on an on-going basis to ensure:
– the optimum use of the hardware and software resources– that all agreed service levels can be achieved– that business volumes are as expected
Analysis objectives:Identify trends from which the normal utilization and service level, or baseline, can be establishes
Identify exception conditions in the utilization of individual components or service thresholds by regular monitoring and comparison with the baseline thresholds
Identify and report breaches or near misses in the SLAs Predict future resource usage, or monitor predicted growth against actual business growth (plan vs. actual)
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Several categories of monitoring are within the scope of the Capacity Management process.
Utilization MonitoringProcessor utilizationMemory utilizationPer cent processor per transaction
type IO rates (physical and buffer) and
device utilizationQueue lengthsDisk utilizationTransaction ratesResponse timesBatch durationDatabase usage Index usageHit ratesConcurrent user numbersNetwork traffic rates.
Response Monitoring Incorporating specific code within client and server
applications software (application instrumentation)Using ‘robotic scripted systems’ with terminal
emulation softwareUsing distributed agent monitoring softUsing specific passive monitoring systems
Durations for MonitoringReal-time (events)Historical
– Problem determination and root cause analysis
– Trend analysis
– Planning
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Insesu
re Zon
e
Secu
re Zon
e
DM
Z
Ga
teway
We
bS
ervers
Voice
Service
sW
ebS
ervers
PartnerServices
VP
N
Customers
Émployees
Portal
Process Server
Service Registry
Application Servers
Integrated Service Management
InfrastructureServices
SecurityServices
Adapters
Connectors Adapters
Connectors
Existing Applications
Intranet
Rel. DB
Internet
Enterprise Service Bus
Agent
Composite ApplicationMonitoring & Management
Agent
Agent
Agent
Composite application monitoring and management offers end-to-end visibility within applications and infrastructure components.
Agent
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Source: ITIL Service Design
© Crown Copyright 2007
According to ITIL, a CDB or CMIS is a cornerstone of a successful Capacity Management process.
The ITIL Capacity Management sub-processes are carried out across several key activities.
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Data Collection begins with establishing a methodology for ensuring that data and measurement requirements are well understood and can be achieved.
Data collected must account for resource usage, accommodate forecasts, and provide for monitoring and tuning the system.
–Which tool(s) to use for data collection and reporting• Metric data – data repository• Non-metric data – document repository
–Frequency of collection and summarization• Detail, hourly, daily, weekly, monthly, quarterly• Peak vs. average
–View of data / information• Business, Application, or Project view• Service view• IT Component view • Location view
–Levels of detail• Shared vs. dedicated resources• Workload level (i.e., process id) vs. transaction level
The CMIS (Capacity Management Information System) repository will be the primary source of the system data needed for
forecasting.
Carefully designed categorization of data allows for flexibility in reporting and analysis from various views.
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A diverse set of data and information can be compiled into a set of application profiles valuable as both inputs and outputs throughout the Capacity Management process.
Business data– Business transactions– Schedule of business events– Business drivers
Service data– Response Time service objectives / levels– Elapsed time, End time, Turnaround Time, Throughput– Maintenance windows
Technical data– CPU type, model, serial– available capacity (MIPS), memory (Central and
Expanded), channels, number of cps, speed of cps, weight
– Operating System, Subsystems
Financial data– Financial plans – IT budgets, including specific budgets for hw and sw
expenditure – external suppliers, for cost of new hw and sw upgrades
Utilization data– IT resource measurements by workload groupings
• CPU resource usage (utilization)• Storage usage (utilization)
Workload 123
Application abcNon-
metric and
metric data
Application or Workload Profiles provide the workload characterization:
Application behavior over time patterns, peaks
Aggregation or groupings Growth requirements, growth scenarios
A composite of all this information can be organized into a set of application or workload profiles.
Application xyz
Various analysis and reporting are also derived from use of the CDB or CMIS.
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A common, standard set of resource usage data can be shared by performance, capacity, and usage-based show-back to forecast and manage IT demand.
Event Monitoring and Management • Alerts, Alarms• Thresholds
Short Term: performance bottleneck analysis(IT resource, application, process, or thread level)
• Problem determination• Root cause analysis
Long Term: Capacity Planning• Trending, plan vs. actual analysis • Forecasting• Sizing• Modeling, statistical regression
IT Accounting: usage-based chargeback • Pricing• Billing• Forecasting • Variance analysis
It is very important to determine which metrics to collect on an ongoing basis, with varying levels of detail applicable
to specific situations.
Raw Data from Agents
Time Range
It is crucial to map resource usage metrics to the
corresponding applications and business units
consuming the resource.
Metrics collected from various platforms, databases, sub-components and
applications address the entire range of scope – from immediate alerts and problem
determination to long term capacity planning and usage-based billing.
Consistent, standardized data collection is crucial to ensure that the metrics needed for performance monitoring, capacity planning (forecasting), and chargeback are readily available.
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Supervise Tuning and Capacity Delivery
Model and size capacity
requirements
Monitor, Analyze and Report
Capacity Usage
Supervise Tuning and Capacity
DeliveryProduce and
maintain capacity plan
Requirements and Early Design
Volumetrics
Estimation and
Modeling
Technology Research
Design, Development and Tracking
Test Planning and
Execution
Live Production
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Supervise Tuning and Capacity Delivery
Outputs from monitoring, analyzing, and reporting activities are examined and actions to tune individual resources or to re-balance the available capacity are planned and initiated through Change and Release Management or through the Service Desk in the case of simple requests to other support groups or self-help for users.
Some recommendations might involve changes in the way that the users use the IT systems: – moving discretionary workloads to off-peak periods
– performing a business function using a more efficient IT service path
– balancing services
– changing concurrency levels
– adding or removing resources
The cycle then begins again, monitoring any changes made to ensure they have had a beneficial effect and collecting the data for the next day, week, or month.
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Supervise Tuning and Capacity Delivery
Service and component tuning:– enables effective utilization of IT resources by identifying inefficient
performance, excess or insufficient capacity, and making recommendations for optimization. It can
– balances the need to maintain service while reducing capacity capability to reduce the cost of service.
Understanding the combined performance impact of various components within a complex infrastructure is needed to accurately differentiate symptoms from actual problems. This level of understanding provides the most accurate baseline for future planning.
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Various techniques can be used for tuning.
Tuning objectives: Identify areas of the configuration that could be tuned to better utilize the
system resource or improve the performance of the particular service
Implementation objectives: Introduce to the live operation services any changes that have been identified
by the monitoring, analysis and tuning activities
Tuning techniques that are of assistance include: Balancing workloads and traffic – transactions may arrive at the host or server at a
particular gateway, depending on where the transaction was initiated; balancing the ratio of initiation points to gateways can provide tuning benefits
Balancing disk traffic – storing data on disk efficiently and strategically, e.g. striping data across many spindles may reduce data contention
Database locking strategy - definition of an accepted locking strategy that specifies when locks are necessary and the appropriate level, e.g. database, page, file, record and row – delaying the lock until an update is necessary may provide benefits
Efficient use of memory – may include looking to utilize more or less memory, depending on the circumstances
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Produce and Maintain Capacity Plan
Model and size capacity
requirements
Monitor, Analyze and Report
Capacity Usage
Supervise Tuning and Capacity
DeliveryProduce and
maintain capacity plan
Requirements and Early Design
Volumetrics
Estimation and
Modeling
Technology Research
Design, Development and Tracking
Test Planning and
Execution
Live Production
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Produce and Maintain Capacity PlanThe objective of this activity is to develop, maintain, test/model and revise alternative approaches in satisfying various enterprise-shared resource requirements.
• Inputs:–forecast assumptions–forecast projections–subject matter expert recommendations
•Controls:–financial constraints–hardware constraints–performance policies–resource standards and definitions–strategy and direction.
•Deliverables:–agreed capacity plan–alternative solutions–optimized resource solution
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Forecasted resource requirements (demand) can provide quantified IT resource ‘volumetric’ input (load) to testing or modeling studies that analyze the impact of the projected IT resource load and exercise various solution alternatives to satisfy the demand.
Establish Baseline:Define Content and Scope Select representative time Period Determine Metrics to characterize Determine time Durations
Develop forecast requirements (demand):
Define objectives of forecastDetermine forecasting horizonSelect appropriate set of forecasting techniques Define growth scenarios• Conservative, Most-likely, Aggressive Quantify forecasted requirements (demand) into IT
resource requirements (load) over time
Conduct Testing / Modeling Studies:
Calibrate the baselineApply forecasted requirements (demand) against
baseline Analyze impact of forecasted IT resource
volumetrics (load) over time Exercise various solution alternativesDocument assumptions and risksRecommend conservation actions
Capacity Plan:Consolidate growth plans for all workloads• existing workloads • new applications, enhancements to applications • changes to the IT environment / infrastructure Recommend solutionsDocument associated approaches, assumptions, risks Track through plan vs. actual analysis
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Capacity planning is needed to help evaluate existing and new applications, as well as changes in your business environment.
Capacity planning missionThe goal of the capacity planning process is to help ensure that sufficient cost-
effective capacity is available to meet existing service level commitments, as well as business and application growth requirements.
Each of the three major sources of growth must consider the impact of business growth expectations and planned business events.
ENVIRONMENTAL CHANGES
NEW APPLICATIONS
GROWTH IN EXISTING APPLICATIONS
BASELINE USAGE
Time
IT r
eso
urc
e u
sag
e
t t0 1
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Composite views of IT resource estimates are developed based on the aggregation of the individual resource requirements.
All of the requirements are summarized, or subtotaled, to develop an aggregate or composite view of the overall, enterprise-wide resource requirements or demand
IT resource composite views can include:– Servers
– Storage
– Data Network
– Voice Network
– Middleware
– Database A composite view of IT resource requirements can be
analyzed at various levels of breakout and detail: – Locations
– Key applications/workloads
– Business functions
– Physical processors
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Individual requirements are developed at a more detailed level that is typically based on a reasonable set of key applications/workloads.
Workload grouping assists in determining what level of detail provides an effective aggregation for a composite view that is reasonable and appropriate for the Capacity Plan.
Workload grouping: Defining key applications/workloads
– Top resource load Group or Aggregate like application/workloads
– Similar resource usage characteristics• By IT resource component: an application / workload could surface as ‘key’ in some
component areas and not in others– Similar growth characteristics: one or more of these factors can justify
aggregation:• Similar seasonal trends• Similar growth rates (monthly, annually)• Similar historical trends• Similar business drivers (estimation or correlation)• Similar impact from business events
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Validation of forecasts must be done on a regular basis. One common approach is plan vs. actual analysis. If the actuals deviate significantly or consistently from the plan then investigation into the cause and possible adjustment to the forecast is necessary.
EXAMPLE ONLY2084-305 CECA Average Monthly MIPS Used and Forecasted by LPAR
Shift xxx: startday - endday (starttime - endtime timezone)
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Month
MIP
S
MVSP MVSW DOFPDOFD WSS1 HRAPMVSZ MVSB PHYSICALMVSI DOFZ 80% - planning threshold (1586.4 MIPS)Total installed (1983 MIPS) ACTUALS
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Once the source of the deviation from plan has been determined then the cause of the deviation must be investigated.
What forecasting technique was used ?– If business-driven, has the business driver
forecast changed ?
– If historical trend, has some change been introduced that was not known ?
– Is there an unplanned business event or project that has occurred and is potential impacting the workload ?
Is it possible to drill down further within the workload to further isolate the source of the deviation ?
– perhaps at the application level Are there any related problems that have been
reported, such as response time degradation, etc. ?
What measurements were used to quantify the baseline and the forecasts ?
What were the assumptions ?
What is the degree of risk/impact from this deviation ?
– Is a forecast adjustment necessary ? How do I adjust the forecast ?
– One time event only ?
– Seasonal adjustment ?
– Long term adjustment ? Why do I adjust the forecast ?
– What assumptions need to be modified ?
– Is a different forecasting technique more appropriate ?
What measurements do I have to quantify the necessary adjustments ?
Was the baseline valid or does it have some inherent problems or exceptions that need to be resolved ?
Without sufficient levels of data grouping, it can be very difficult to drill down to the probable source of the deviation and therefore difficult to determine the cause of the
deviation of actual to plan.
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The convergence of Capacity Management, Demand Management, and Performance Engineering (PEMM) provides a powerful and truly full life cycle methodology.
Demand Management
Patterns of Business Activity and Demand
Policies
Performance Engineering Risk Assessment Non-Functional Requirements
Performance Model
Capacity Management Information System &
Capacity Plan
Performance Engineering & Management Method(PEMM based)
Capacity Management Process(ITIL® based)
Feasibility Design Development Test Deploy Production Optimize
• IBM’s Performance Engineering & Management Method (PEMM)
• IT Infrastructure Library (ITIL®)
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Method / Process(Themes / Activities)
Long term elements of system design, development, and delivery that interact
with Performance Engineering
Organization People in the project that you need to work with to achieve your objectives
Phases & Work Products
(Data and Tools)
What the team needs to do or to produce in each phase
of the project.
Integrating work products into the existing phases or gates of the SDLC, project management, and other key business and service management processes helps to operationalize or institutionalize PE.
THEMES & ACTIVITIES
PHASES
PE
OP
LE
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The role of the Performance Engineer or Performance Architect requires multi-faceted skills and responsibilities.
A person who carries out performance engineering duties and leads a Performance Engineering project or team is referred to as a Performance Engineer or Performance Architect.
Performance Engineering is most successful when it is carried out by a multi-disciplinary team representing the major business and technical stakeholders in a project or solution:– Requirements Analysts – Architects– Developers – Infrastructure and Application Engineers– Testers– Capacity Planners– Performance Analysts
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