Cloud Capacity Planning Training

Cloud Capacity Planning Training

Cloud Capacity Planning Training is a 2-day course where participants learn about the engineering tools and procedures required for effective cloud capacity planning.

In the rapidly evolving cloud landscape, effective performance analysis and capacity planning are crucial for optimizing resources and ensuring seamless application delivery.

An essential tactic for enhancing cloud performance is taking a hard look at performance measurement. Start by establishing clear performance metrics. Focus on key performance indicators (KPIs) such as response time, uptime, throughput, and resource utilization.

Utilize monitoring tools like AWS CloudWatch, Azure Monitor, or Google Cloud Monitoring to gather real-time data. This data helps identify performance bottlenecks and ensures that your applications meet user expectations.

It is also a good idea to conduct regular trend analysis to identify patterns in resource usage over time. By analyzing historical data, you can predict future demand and adjust your cloud resources accordingly. Look for spikes in usage during peak times and assess whether your current capacity can handle future growth. Tools such as Grafana and Kibana can help visualize these trends effectively.

Experts in this area contend that proper system sizing is essential for optimizing costs and performance. Start with a thorough understanding of your application architecture and workloads. Use load testing tools like Apache JMeter or LoadRunner to simulate different traffic conditions and identify the optimal configuration for your resources. Sizing should be iterative; continually refine your estimates based on actual usage data.

Then there’s integrating DevOps practices.

Adopt DevOps practices to enhance collaboration between development and operations teams. Implement continuous integration and continuous deployment (CI/CD) pipelines to automate resource provisioning and scaling. This allows you to respond quickly to changing demands and optimize your cloud environment dynamically. Tools like Terraform and Kubernetes can facilitate infrastructure as code, enabling efficient resource management.

It’s also beneficial to leverage automated tools for cloud capacity planning. Solutions like CloudHealth or CloudCheckr can analyze usage patterns and recommend adjustments. Establish a proactive approach by regularly reviewing capacity and performance data to prevent potential issues before they impact your users.

Cloud Capacity Planning Training Course by Tonex

Cloud Capacity Planning Training is a 2-day training course covering all the aspects of Capacity Planning for the Cloud and DevOps methods.

Capacity Planning Training Boot Camp by Tonex is an intensive learning experience that covers the essential elements of cloud computing and DevOps capacity planning. The course is ideal for busy professionals who want to stay current in their fields but have limited time to be away from the office.

Cloud and DevOps Capacity Planning Training course  provides the details of capacity planning as a repeatable process for IT Cloud infrastructure, virtualized functions, data centers, 5G wireless (NFV/SDN/Network Slices) and modern networking and telecom systems. 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 cloud performance analysis, system sizing, performance measurements, trend analysis and using DevOps methods and processes.

Cloud capacity planning and management process works closely with service level management to ensure that the business’ requirements for cloud capacity and performance can be met. Cloud and capacity management also serves as a focal point for any capacity issues in IT Service Management dealing with Cloud.

Additionally, as organizations progress through their DevOps journey, this training course covers the best practices that successful cloud capacity planning teams use including a set of core DevOps practices that are critical for cloud capacity planning success. Discover what separates successful DevOps teams from those that fail, and learn the next steps to take on your DevOps journey.

Successful cloud capacity management requires a thorough understanding of how business demand influences demand for cloud services, and how service demand influences demand on components.

Who Should Attend?

The target audience for the Cloud Capacity Planning course includes Analysts, IT Capacity Planning Engineers, Managers, Operations, Developers, QA and Testing professionals such as:

• Application Developers
• Automation Architects
• Business Analysts
• Business Managers
• Business Stakeholders
• Change Agents
• Consultants
• DevOps Consultants
• DevOps Engineers
• Individuals involved in IT development
• Infrastructure Architect
• Integration Specialists
• IT Directors
• IT Managers
• IT Operations
• IT operations or IT service management
• IT professionals working with Agile Service Design Environment
• IT Team Leaders
• Lean Coaches
• Network Administrators
• Operations Managers
• Project Managers
• Release Engineers
• Software Developers
• Software Tester/QA
• System Administrators
• System Integrator
• Systems Engineers
• Tool Providers

Learning Objectives

After completing the Cloud Capacity Planning training, participants will be able to:

• Review of design, implementation and management world-class cloud infrastructure and applications
• Review enterprise architecture, management and modern IT system management processes
• Explain the basics of capacity planning and performance management applied to Cloud Computing and DevOps
• Understand the engineering tools and procedures required for cloud capacity planning
• Step through a practical process for managing a cloud capacity planning project
• Explore benchmarking, load testing, workload forecasting, and performance modeling of cloud computing
• Develop a cloud capacity utilization and forecast plan to achieve costs, quality, and customer satisfaction objectives
• Review Virtualization Capacity Planning techniques
• Discuss Cloud Computing Capacity Planning techniques and methods
• Discuss Cloud and DevOps capacity planning support

Course Modules

Introduction to Capacity Management and Capacity Planning

• Fundamentals of Cloud Technology Concepts
• Fundamental Cloud Computing
• Fundamentals of Capacity Planning and Performance Management
• Cloud Capacity Planning and Management Process
• Business and Technology Frameworks
• Agile
• ITSM
• Lean
• Performance, Safety and Reliability Cultures
• Fundamentals of Cloud Capacity
• 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

Fundamental Cloud Computing

• Fundamental Cloud Computing Terminology and Concepts
• Public and Private Clouds
• Hybrid Cloud
• Software as a Service (SaaS) Cloud
• Platform as a Service (PaaS) Cloud
• Infrastructure as a Service (IaaS) Cloud
• Network as a Service (NaaS) Cloud
• Calculating and Rating Cloud SLA
• Cloud Quality of Service Characteristics
• Scalability
• Cost-effectiveness
• Immediate availability
• Performance
• Security

Introduction to Cloud Capacity Planning

• Cloud Capacity planning and performance measurements
• Predict cloud resource requirements
• Cloud SLA and service management
• Capacity Management Drivers
• Cloud Performance Management & Performance Data Collection
• Cloud Workload Analysis
• Cloud-based Workload Models and Management
• Capacity Planning vs. Demand Management
• Business vs IT Capacity
• Service Capacity vs. Resource Capacity
• Efficient Operational Environment
• Capacity Calculations for Cloud Computing
• Service Capacity Calculation
• Resource Capacity Calculation
• Virtualization Capacity Calculation
• Business Capacity Assessment for Cloud Providers and Cloud Consumers
• Dynamic Cloud-based Capacity Planning and Management
• System Health & Capacity Reporting
• Case Study 1
• Cloud Service Level Agreement (SLA)
• Service Commitment
• Service Credits
• Availability
• Monthly Uptime Percentage
• Cloud Service Credit Percentage
• Process for Cloud capacity planning
• Cloud Performance tuning & capacity planning
• Practical methods of measurement, simulation, and analytical modeling

ITIL Capacity Management Applied to Cloud

• Cloud Performance monitoring
• Cloud Workload monitoring
• Cloud Application sizing
• Cloud Resource forecasting
• Cloud Demand forecasting
• Modeling Tips for Demand Capacity Planning
• Cloud and DevOps Support
• Data Center Capacity Planning

Cloud 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
• 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

Cloud Performance Monitoring

• Cloud 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
• Performance monitoring data accumulation
• Detection, counting, storage and reporting
• Performance Management Control

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
• 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

DevOps and Capacity Planning

• Capacity Planning the DevOps Way
• Capacity planning in DevOps
• Role of People and Teams
• App Team
• Platform Team
• Capacity Planning
• Enterprise Architecture
• Middleware and App Development
• Data Architecture
• Process and Process Automation
• Technology and Architectures
• Performance vs. Limitation
• Capacity Modeling Approach
• Steps to Successful Capacity Planning and Management

DevOps Practices applied to Cloud Capacity

• Core DevOps Principles
• Key DevOps Practices Applied to Cloud Capacity Planning
• Culture, Behaviors & Operating Models
• Continuous Delivery
• Site Reliability & Resilience Engineering
• Organizational maturity models
• Target Operating Models
• Automation & Architecting DevOps Toolchains
• DevOps Toolchain
• Measurement, Metrics, and Reporting
• The Importance of Capacity Metrics
• Technical and Business Metrics
• Measuring & Reporting Metrics

Labs, Exercises and Hands-on Activities 

• Working with Tonex Cloud Capacity Planning Models and DevOps Processes
• Forecasting and Trend Analysis Labs

Cloud Capacity Planning Training