Corporate Cloud Capacity Planning Training Course

1. Fundamentals of cloud technology concepts
   • Fundamental cloud computing
   • Fundamentals of capacity planning and performance management
2. Cloud capacity planning and management process
3. Business and technology frameworks
   • Agile
   • ITSM
   • Lean
   • Performance, safety, and reliability cultures
4. Fundamentals of cloud capacity
5. Fundamentals of DevOps
   • Advanced cloud capacity with DevOps
   • Key practices for a mature DevOps organization dealing with cloud capacity
   • Real-time monitoring and observability, and key metrics to track

1. Types of cloud models
   • Public and private clouds
   • Hybrid cloud
2. Cloud service models
   • Software as a Service (SaaS) cloud
   • Platform as a Service (PaaS) cloud
   • Infrastructure as a Service (IaaS) cloud
   • Network as a Service (NaaS) cloud
3. Service level agreements and quality of service
   • Calculating and rating cloud SLA
4. Cloud quality of service characteristics
   • Scalability
   • Cost-effectiveness
   • Immediate availability
   • Performance
   • Security

1. Cloud capacity planning and performance measurements
   • Predict cloud resource requirements
2. Cloud SLA and service management
   • Capacity management drivers
   • Cloud performance management & performance data collection
3. Cloud workload analysis
4. Cloud-based workload models and management
5. Capacity planning vs. demand management
6. Business vs IT capacity
7. Service capacity vs. resource capacity
8. Efficient operational environment
9. Capacity calculations for cloud computing
   • Service capacity calculation
   • Resource capacity calculation
   • Virtualization capacity calculation
10. Business capacity assessment for cloud providers and cloud consumers
11. Dynamic cloud-based capacity planning and management
12. System health & capacity reporting
13. Cloud Service Level Agreement (SLA) elements
14. Process for cloud capacity planning
15. Cloud performance tuning & capacity planning methods

1. Cloud performance monitoring
2. Cloud workload monitoring
3. Cloud application sizing
4. Cloud resource forecasting
5. Cloud demand forecasting
6. Modeling tips for demand capacity planning
7. Cloud and DevOps support
8. Data center capacity planning

1. Component performance and management
   • CPU
   • Back plane or I/O
   • Memory
   • Interface and pipe sizes
   • Queuing, Latency, and Jitter
2. Application characteristics
3. Capacity and performance management best practices
   • Service level management
   • Minimizing the cost of meeting SLAs
4. Analytical queuing modeling
5. Capacity trending methods
6. Infrastructure capacity planning techniques
7. Components of response time
8. Performance problem management
9. Built-in performance guidelines
10. Optimize IT infrastructure for peak performance

1. Cloud performance monitoring policy
2. Network performance monitoring
   • Event correlation and filtering
   • Data aggregation and trending
3. Data collection techniques
4. Traffic status and monitoring
5. Threshold crossing alert processing
6. Performance management control

1. Forecasting horizons and data collection
2. Approaches to forecasting
   • Qualitative
   • Quantitative
   • Subjective models
   • Delphi methods
   • Causal models
   • Regression models
   • Time series models
3. Forecast error measures
   • Standard Squared Error (MSE)
   • Mean Absolute Deviation (MAD)
   • Mean absolute percentage error (MAPE)
   • Mean Forecast Error (MFE or Bias)
4. Forecast accuracy dimensions
   • Quantity accuracy
   • Time accuracy
   • Correlation analysis

1. Capacity planning the DevOps way
2. Role of people and teams in capacity planning
3. Enterprise architecture and middleware
4. Process and process automation
5. Technology and architectures
6. Performance vs. limitation
7. Capacity modeling approach
8. Steps to successful capacity planning and management

1. Core DevOps principles
2. Key DevOps practices applied to cloud capacity planning
3. Culture, behaviors & operating models
4. Continuous delivery
5. Site reliability & resilience engineering
6. Organizational maturity models
7. Target operating models
8. Automation & architecting DevOps toolchains
9. Measurement, metrics, and reporting

1. Working with Tonex Cloud Capacity Planning Models and DevOps Processes

2. Forecasting and Trend

Hands-on experience with forecasting and trend analysis in the context of cloud capacity planning will be provided by our experts. The professionals will work on real-world case studies and projects to apply the concepts and techniques covered in earlier modules. The labs will cover time series, trend, and regression analyses.