Price: $3,999.00

Course Number: 9050
Length: 4 Days
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Capacity Planning Training

The purpose of capacity planning is to ensure the requirement for goods and services are met with equal effective capacity as well as to avoid overages in capacity that contribute to wasted resources.

In Information Technology (IT), capacity planning is often referred to as capacity management. Capacity management generally relates to the literal interpretation of the word “capacity,” which relates directly to the hard disk storage, computing power, software, and network resources required to facilitate the expected number of interactions over a given time period.

These interactions may be customers on their e-commerce website making purchases, or thousands of employees sending emails, receipts, telephone recordings, and documents across a company network. The common thread between these operations is the servers and databases that house the information.

Without capacity planning, an IT service provider can either spend excess costs for the realistic business requirements or fall short on delivering ITIL service level targets.

The general consensus is that in IT capacity planning there is a balancing act between costs and capacity. There needs to be a focus on ensuring that the processing capacities satisfy the business requirements at justifiable costs as well as be used efficiently.

Another key element during capacity planning is supply and demand. The available range of processing services should be aligned with the current and future requirements of the business. As in costs and capacity, the demand for a service must be supplied by the IT service provider. Good capacity planning means that the IT service provider will be able to deliver on the demand from the customers.

There are several steps involved in efficient capacity planning. The first step involves determining service level requirement. This is where a business breaks down work into categories as well as quantifies users’ expectations for how that work is accomplished.

This first step often encompasses three additional stages: establishing workloads, determining the unit of work and setting service levels.

The second step is about analyzing current capacity. This is where an organization takes an in-depth look at its current production schedule to evaluate capacity and analyze each workload and system as a whole.

The third step is a call for planning. Basing a plan on forecast processing requirements helps prevent overwhelming the system. In order to accomplish this task, organizations must know the amount of incoming work expected over the coming quarters. Then an optimal system should be configured for satisfying service levels over this period.

Capacity Planning Training Course by Tonex

Capacity Planning Training Boot Camp by Tonex is an intensive learning experience that covers the essential elements of your chosen subject. Boot camps are ideal for busy professionals who want to stay current in their fields but have limited time to be away from the office.

Capacity Planning Training

Capacity Planning Training Course Boot Camp provides the details of capacity planning as a repeatable process for IT infrastructure, cloud computing, virtualized environment, data centers, 5G wireless (NFV) and telecom. It’s about understanding service levels and resource usage and aligning capacity requirements with business demands with trending and forecasting.

Capacity Planning training course covers tactics for doing performance analysis, system sizing, performance measurements, trend analysis in today¹s challenging business and IT environment.

Performance analysis and planning are often forgotten due to the project completion on time.This hands-on course will define the characteristics of a good BMI and give techniques for identifying the best BMI choice from the many possibilities. We will discuss analytical tools, formulas and techniques used, and describe both theoretical ideals and real world cases. We will also show examples on how to use increasingly fuzzy BMIs to make great capacity plans. We have updated the course material with a special section on Green Capacity Planning and some case studies on Green Data Centers.

All boot camps includes:

  • Experienced instructors including senior technology leaders, project managers, technical authors, engineers, educators, consultants, course developers, and CTOs.
  • Real life examples and practices.
  • Small class size.
  • Personalized instructor mentoring.
  • Pre-training discussions.
  • Ongoing post-training support via e-mail, phone and WebEx.

Objectives

After completing this boot camp, attendees will be able to:

  • Review designing, implementing and managing world-class infrastructure and applications
  • Review enterprise management and IT system management processes
  • Explain the basics of capacity planning and performance management
  • Understand the engineering tools and procedures required for capacity planning
  • Explain the Capacity Planning problem
  • Review of Capacity Planning applications
  • Define a Capacity Planning methodology
  • Understand performance and availability of new infrastructure and applications
  • Identify capacity and performance management best practices
  • Understand inventory and asset management processes
  • Explore Service Level Management (SLM)
  • Describe how to define, structure, manage and maintain inventory and manufacturing capacity
  • Define metrics, models and methods
  • Understand workload forecasting
  • Define measuring the performance
  • Identify the relationship between Business Metrics of Interest (BMIs) and available system performance metrics
  • Explore project management process of capacity planning
  • Review successful capacity planning deployments
  • Discuss successful and unsuccessful capacity planning projects
  • Step through a practical process for managing a capacity planning project
  • Explore benchmarking, load testing, workload forecasting, and performance modeling of Web services
  • Develop a capacity utilization and forecast plan to achieve costs, quality, and customer satisfaction objectives
  • Explore the current and future market trends
  • Explore Green Capacity Planning
  • Perform trend analysis and forecasting
  • Review examples and case studies
  • Review Virtualization Capacity Planning techniques
  • Discuss Cloud Computing Capacity Planning techniques and methods
  • Discuss Cloud and DevOps capacity planning support

Outline

Introduction to Capacity Planning

  • What is capacity planning?
  • Concepts and terminology
  • Applications and related domains
  • Capacity planning and performance measurements
  • Predict IT resource requirements
  • SLA and service management
  • Capacity management
  • Network capacity planning
  • Required components
  • Administrative considerations
  • System performance tuning
  • Domain model review
  • Process for network capacity planning
  • Performance tuning & capacity planning
  • Practical methods of measurement, simulation, and analytical modeling

ITIL Capacity Management

  • Performance monitoring
  • Workload monitoring
  • Application sizing
  • Resource forecasting
  • Demand forecasting
  • Modeling

Understand the IT resources needed to deliver acceptable service

  • Accurate models and forecasts
  • Defining workloads
  • Manage workloads
  • Measure and manage performance and resource usage with business-oriented analysis
  • Eliminate guesswork
  • Isolate root cause of performance and response time bottlenecks rapidly
  • Concentrate scarce resources
  • Manage by exceptions from normal performance across complex environments via statistical analysis
  • Identifying the relationship between Business Metrics of Interest (BMIs) and available system performance metrics
  • BMIs represent the real world transactions that drive our business workload’s resource consumption

The Capacity Planning Problem

  • A Capacity Planning Methodology
  • Performance Models
  • Performance of Client-Server Systems
  • Obtaining Input Parameters
  • Model Calibration and Validation
  • Performance of New Applications
  • Supply Chain Optimization - 1:1-Type
  • Supply Chain Optimization - N-Tier-Type
  • Supply Chain Optimization - 1-Tier-Type
  • Demand Capacity Planning
  • Cloud and DevOps Support
  • Data Center Capacity Planning

Capacity Planning Processes

  • Why is capacity planning important?
  • Foundation of performance
  • Queuing, parallelism and multiprocessor systems
  • IT management process maturity
  • Find wasted capacity
  • Model a single system or multi-tiered applications
  • Overview of current procedures and processes
  • Discussion of issues related to coordination of processes
  • Performance analysis of an application
  • Workload characterization Sizing using resource utilization profiles
  • Application architecture-specific modeling
  • Memory (buffers)
  • Internal application scheduling and prioritization
  • 3-tier architecture
  • Users (client workstations, typically PCs, web users, etc.)
  • Application Server
  • Database Server
  • The process to address the problem
  • Understand where the data is located
  • Collate and correlate data
  • Build a model

Modeling Applications

  • Modeling a pure 3-tier environment
  • Measurements available for Database Server
  • Separating relevant RDBMS instances
  • Using additional information from
  • Application and Web Servers
  • Examples
  • Sample resource breakdown

Capacity and Performance Management

  • CPU
  • Back plane or I/O
  • Memory
  • Interface and Pipe Sizes
  • Queuing, Latency, and Jitter
  • Application Characteristics
  • Capacity and Performance Management Best Practices
  • Service Level Management
  • Minimizing the cost of meeting SLAs
  • Reducing data center complexity
  • Maximizing the utilization of resources
  • Server consolidation
  • Service level management
  • Prediction of resource requirements
  • A proactive extension of performance management
  • Planning of hardware and software purchases
  • Planning of upgrades and consolidate servers
  • Capacity shortages or wasteful under utilization
  • Analytical queuing modeling
  • Capacity trending
  • Historical patterns
  • Linear trend line
  • Linear growth path
  • Predicts capacity requirements
  • Infrastructure capacity planning
  • Predict performance
  • Determine the optimal configuration
  • Components of response time
  • Identify performance problems
  • Manage performance with alarms
  • Built-in performance guidelines
  • Optimize IT infrastructure for peak performance
  • Locate bottlenecks and pinpoint the cause
  • Analyze real-time and historical performance

Modeling of Related Systems

  • System structure
  • The operational strategy
  • Computer systems
  • Planning of the capacity of computer systems
  • Predict performance under different configurations
  • Design new applications that meet performance requirements
  • Use of analytic queuing network models of computer systems.
  • Communication networks
  • The Telephone network
  • Data networks
  • LANs, WANs and MANs
  • Mobile communication systems
  • Cellular systems
  • 4G and 5G Mobile Systems
  • IMS and VolTE Systems

Probability Theory and Statistics

  • Theory of Queuing
  • Familiar queuing problems
  • Characterizing a queue
  • Basic metrics
  • Throughput, busy time, utilization, response time, load, service time
  • Response time relationships for some simple queues
  • Distribution functions
  • Combination of random variables
  • Time Interval Distributions
  • Exponential distribution
  • Steep distributions
  • Flat distributions
  • Cox distributions
  • Other time distributions
  • Observations of life{time distribution

Performance Management Processes

  • Performance modeling of communication networks and computer architectures
  • Performance of centralized, distributed, parallel, client/server systems, Web server and e-commerce site performance.
  • Performance measuring tools for operating systems such as Unix and Windows NT
  • Performance characteristics and considerations
  • Performance Quality Assurance
  • QOS performance goal setting
  • Network/Resource performance goal setting
  • Subscriber service quality criteria
  • QOS performance assessment
  • Network/Resource performance assessment
  • Resource performance assessment
  • Data integrity check
  • System and Network Management using SNMP and RMON

Performance Monitoring

  • Performance monitoring policy
  • Network performance monitoring event correlation and filtering
  • Data aggregation and trending
  • Data collection
  • Traffic status
  • Traffic performance monitoring
  • Threshold crossing alert processing
  • NE(s)/Resource trend analysis
  • Performance monitoring data accumulation
  • Detection, counting, storage and reporting

Performance Management Control

  • Network traffic management policy
  • Traffic control
  • Traffic administration
  • Performance administration
  • Execution of traffic control
  • Audit report
  • Performance Analysis

Recommendations for Performance Improvement

  • Exception threshold policy
  • Traffic forecasting
  • Customer service performance summary (excludes traffic)
  • Customer traffic performance summary
  • Traffic exception analysis
  • Traffic capacity analysis
  • Network performance characterization
  • NE(s) performance characterization
  • NE(s) traffic exception analysis
  • NE(s) traffic capacity analysis

Performance Measurement Techniques

  • Measurement
  • Simulation
  • Analytical modeling
  • Performance Metrics
  • Measurement Tools and Techniques
  • Statistical Interpretations of Data

Analyzing Network Traffic

  • Analysis process
  • Network monitor
  • Examining network packets
  • Comparing network protocols
  • Characterizing services
  • Classifying network traffic
  • Performance analysis techniques - a Review
  • Performance data collection services
  • Creation of predict models representing workloads
  • Evaluation of the Predict model
  • Verification and calibration of the predict model
  • Predictive analysis of the effects of workload growth and system upgrades
  • Graphs and reports to demonstrate modeling results
  • Set response time and resource utilization guidelines and thresholds
  • Review the impact of workload growth on the current resource utilization
  • Evaluate the effects of various upgrades

Traffic Measurements

  • Measuring principles and methods
  • Continuous measurements
  • Discrete measurements
  • Theory of sampling
  • Continuous measurements in an unlimited period
  • Scanning method in an unlimited time period
  • Numerical example

Optimizing Networks

  • Network planning
  • Network performance
  • Optimization tools and techniques
  • Optimizing client-to-server traffic
  • Optimizing server-to-server traffic
  • Predicting network traffic
  • General guidelines
  • Traffic prediction scenarios

Capacity Planning Applied

  • Performance management vs. systems management
  • Performance monitoring
  • Performance analysis
  • Performance prediction
  • Server performance
  • Application performance
  • Application performance-benchmarks
  • Performance management standards
  • Industry performance management standards

Capacity Planning and Web Services

  • When Web Performance is a Problem
  • Protocols and Interaction Models for Web Services
  • Basic Performance Concepts
  • Performance Issues of Web Services
  • Planning the Capacity of Web Services
  • Understanding and Characterizing the Workload
  • Benchmarks and Performance Tests
  • System-Level Performance Models
  • Component-Level Performance Models
  • Web Performance Modeling
  • Availability of Web Services
  • Workload Forecasting
  • Measuring Performance

Capacity Planning Trend analysis, Forecasting and Improvements

  • Systematic method of consistently measuring servers
  • Measuring application performance
  • Lessons Learned
  • Tools and Trend
  • Green IT Capacity Planning: from theory to the practice
  • Tools for server, mainframes and application performance management
  • Capacity Planning Modeling and Analysis
  • Why forecast?
  • An overview of forecasting technique
  • Forecasting Approaches
  • Date-based trending
  • Business driver trending
  • Types of Growth
  • Business Driver Based Forecasting Steps
  • Actual vs. Projected analysis

Trending with Forecasting Methods

  • Forecasting Horizons
  • Data Collection Approaches
  • Qualitative Approaches to Forecasting
  • Quantitative Approaches to Forecasting
  • Subjective Models
  • Delphi Methods
  • Causal Models
  • Regression Models
  • Time Series Models
  • Moving Averages
  • Exponential Smoothing
  • Seasonality
  • Associative Forecasting
  • Autoregressive moving average (ARMA)
  • Autoregressive integrated moving average (ARIMA)

Modeling for Forecasting

  • Effective Modeling for Good Decision-Making
  • Regression models Components of an Observation
  • Time-Critical Decision Modeling and Analysis
  • Accuracy and Validation Assessments
  • Autocorrelation
  • Standard Error for a Stationary Time-Series
  • Performance Measures for Forecasting
  • Estimation Period, Validation Period, and the Forecasts
  • Stationary Time Series
  • Statistics for Correlated Data
  • A Summary of Forecasting Methods
  • Neural Network for time series forecasting, the prediction model
  • Predictions by Regression
  • Applications of forecasting
  • The Components of a Time Series
  • Elements of a Good Forecast Smoothing Techniques
  • Measuring Forecast Accuracy
  • Forecasting Error Analysis

Forecasting Performance

  • How good is the forecast?
  • Measures of Forecast Error
  • Standard Squared Error (MSE)
  • Mean Absolute Deviation (MAD)
  • Mean absolute percentage error (MAPE)
  • Mean Forecast Error (MFE or Bias)
  • Tracking signal
  • Dimensions of Forecast Accuracy
  • Quantity Accuracy
  • Time Accuracy
  • Correlation Analysis

Introduction to Virtualization, NFV and Cloud Computing Capacity Planning

  • Capacity planning applied to virtualized infrastructure and environments
  • Virtualization capacity planning concepts and terminology
  • Creating a cloud computing capacity planning process
  • Creating a capacity planning process for virtualized infrastructure
  • Capacity Planning applied to Network Function Virtualization (NFV)
  • Key measurable factors
  • Business requirements
  • Performance & Capacity Management
  • Capacity Planning and Performance Monitoring applied to Cloud and Virtualization
  • Service level agreements
  • Availability, Storage, Backup and Recovery
  • Utilization Patterns and Trends
  • Managing Workloads
  • Workload scenarios for new products or services
  • Managing seasonal fluctuations
  • Software support
  • Availability, agility, scalability
  • Integration with other systems
  • Security, compliance, and regulatory requirements
  • Data management policies
  • Data creation, access, retention, archiving and deletion
  • Configuration considerations
  • Disaster recovery

Labs, Exercises and Hands-on Activities 

  • Working with Tonex Capacity Planning Models and Processes
    • Create a System Capacity Planning Framework for your organization
    • System Capacity Planning
    • Main Steps for Capacity Planning
    • Determine Service Level Requirements
    • Analyze Current Capacity
    • Planning for the future
    • Service Description
    • SLA Parameters
    • Workload Characterization
    • Define Workload Profiles
    • Capacity Planning Forecasting
  • Simulate projected traffic growth to identify necessary network upgrades and associated costs.
  • Perform exhaustive failure analysis to determine risk areas, and plan redundant routes.
  • Define service-level agreements (SLAs) for any metric, such as application response time.
  • Design a cost-effective, optimized network that incorporates new technologies.
  • Optimize application deployments by right-sizing network resources, fine-tuning protocols, and configuring servers in advance.
  • Forecasting and Trend Analysis Labs
    • Trend
    • Multiple Regression
    • Seasonal Analysis
    • Exponential Smoothing
    • Lags
    • Time Series

Capacity Planning Training

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