Capacity planning is a strategic function used to predict IT resource requirements. It is a proactive extension of performance management, bringing order to chaos and predictability to IT management. Capacity planning and performance management together are sometimes referred to as capacity management.
This course provides an introduction to capacity planning as a repeatable process. It's about understanding service levels and resource usage and aligning capacity requirements with business demands. Capacity Planning training boot camp covers tactics for doing performance analysis, system sizing, performance measurements and capacity planning in today¹s challenging business and IT environment. Performance analysis and planning are often forgotten due to the project completion on time.
One of the major goals of capacity planning is to ensure that the business service level objectives are met. Identifying the relationship between Business Metrics of Interest (BMIs) and available system performance metrics is critical to accurate models and forecasts. BMIs represent the real world transactions that drive our business workload’s resource consumption. 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.
Objectives
After completing this boot camp, attendees will be able to:
Review of 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
Define a process
Define a strategy
Define capacity areas
Define the capacity variables
Define performance models
Model calibration and validation
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
Review examples and case studies
Course Outline
Introduction to capacity planning
What is capacity planning?
Concepts and terminology
Capacity planning and performance measurements
Predict IT resource requirements
A proactive extension of performance 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
Emphasis is on 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.
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
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
Separating the 2-tier work
Separating UNIX 2-tier users
Using additional information from
Application Servers
Modeling a 2-tier environment
Modeling UNIX 2-tier work
Modeling PC 2-tier work
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 underutilization
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
Local Area Networks (LAN)
WANs and MANs
Mobile communication systems
Cellular 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 Improvements
Systematic method of consistently measuring servers
Measuring application performance
Lessons Learned
Tools and Trend
Tools for server and application performance management
Case Studies
Labs and Hands-on Exercises
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.
Experienced instructors including senior executives, managers, authors, educators, consultants, course developers, and CTOs.
Real life examples and practices
Small class size
Personalized instructor mentoring
Ongoing post-training support via e-mail and phone
On-Site Classes
On-site classes can also be tailored to meet your needs. You might shorten a 20-day class into a 5-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff's and site's requirements. We require a minimum of five employees and above.
Customize your Boot Camp TONEX Boot camps can be tailored to meet your specific needs. At TONEX, we gain an in-depth understanding of your organization and your training requirements. We can then customize the Boot Camp to match your project and the attendees' experience and requirements.
Courses can be delivered to your office, providing content and focus integrated with the immediate needs of your organization.
TONEX extracts the key elements of the course topics and packages them into an efficient and cost effective Boot Camp by eliminating the overlap and introductory redundancy.
A customized Boot Camp gives provides immersion into a subject in a comparatively short period of time. For those requiring more detailed views, we offer Advanced courses.
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