Description
Capacity Planning training class - What is a TONEX Boot Camp?
TONEX Capacity Planning Training Boot Camp is intensive learning experiences that cover the essential elements of your chose 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.
All boot camp 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.
What will you learn at the TONEX Capacity Planning Training Course Boot Camp?
Capacity planning training course bootcamp provides the details of capacity planning as a repeatable process for IT infrastructure, cloud computing, and data centers. 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 setion on Green Capacity Planning and some case studies on Green Data Centers.
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
- Explor Green Capacity Planning
- Perform trend analysis and forecasting
- 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
- 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.
- 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 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
Labs and Hands-on Exercises
Additional Information
Don't Delay -- Space is Limited!
Take advantage of group discounts! Organize a group enrollment -- you save your company money and enhance the skills of everyone who attends. Individuals and small groups please contact us in regards to available seats and dates. Call Today: 888-TO-TONEX / International +1-972-735-8686.
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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.
On-Site Classes
TONEX Training boot camps can be held on-site and tailored to meet your organizational needs. You may shorten or extend the length or a course 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 for on-site training.
Call today: 888-TO-TONEX/ International +1-972-735-8686.