Capacity Planning Training – Performance Engineering, Cloud, Infrastructure & Real-Time Case Studies

Capacity Planning Training – Performance Engineering, Cloud, Infrastructure & Real-Time Case Studies – Live Training

(Master Workload Modeling, Forecasting, Application, Database, Cloud & Infrastructure Capacity Planning with Hands-On Scenarios)

 

This Capacity Planning Training Course is designed to help you understand how to predict, design, and optimize system capacity for modern applications. You will learn how to handle real-world traffic, prevent outages, and ensure systems scale efficiently under load.

The course covers end-to-end capacity planning, including workload analysis, demand forecasting, application sizing, database planning, infrastructure capacity, and cloud scaling strategies. You will also explore real outage case studies from industries like banking, eCommerce, and fintech to understand where systems fail and how to prevent it.

With hands-on learning, you will gain expertise in performance engineering concepts, Little’s Law, throughput modeling, auto-scaling, Kubernetes capacity planning, and observability-driven optimization.

By the end of this course, you will be able to design scalable, high-availability systems and confidently work in roles like Performance Engineer, SRE, DevOps Engineer, and Capacity Planner.

Why Choose This Capacity Planning Course?

• Industry-focused training with real-time outage case studies
• Covers complete capacity planning lifecycle: demand → modeling → validation → optimization
• Learn workload modeling and forecasting techniques
• Hands-on experience with Excel-based demand forecasting
• Covers application, database, infrastructure, and cloud capacity planning
• Includes modern architectures like microservices and Kubernetes
• Learn real-world scaling strategies and failure scenarios
• Focus on performance engineering and system reliability
• Understand cost vs performance trade-offs in cloud environments
• Beginner-friendly with advanced real-time concepts

About the Instructor:

Sushant is a seasoned performance engineering and capacity planning professional with over 12 years of industry experience working on enterprise-scale applications. His expertise includes capacity forecasting, workload modeling, infrastructure sizing, and performance risk analysis across large production systems. He has supported business-critical platforms by aligning technical capacity strategies with growth and cost-optimization goals. His real-world exposure enables him to approach capacity planning as both a technical and business-driven discipline. With 4+ years of teaching experience, Sushant has successfully trained over 300 professionals through classroom and corporate training programs. Teaching is his passion, and he is known for his structured explanations, real-time industry examples, and learner-centric approach. He focuses on building strong fundamentals while enabling participants to apply concepts confidently in real projects. At OOR Institute, he is committed to developing industry-ready capacity planning professionals.

 

Sample Videos:

End-to-End Capacity Planning for Modern Applications (Cloud, Microservices & DevOps)-Demo

 

End-to-End Capacity Planning for Modern Applications (Cloud, Microservices & DevOps)-Day 1

 

Live Sessions Price:

For LIVE sessions – Offer price after discount is 229 USD 179 USD 119 USD Or  1900 INR 15000 INR 9900 Rupees.

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✨ Recently, we have completed the demo sessions for our current batch. The next batch will be scheduled soon.

📌 To know more details and get complete information about the course, please register using the “Enroll for Free Demo” button, or you can directly reach out to us using the WhatsApp button above.

🙏 Thank you for your interest! Once the new batch date and time are finalized, we will get in touch with you.

 

What student’s have to say about Sushant:

This course is fantastic for beginners! I had no prior experience with Python or Pandas, but now I feel confident in my ability to clean, transform, and analyze data. – Kanthi I highly recommend this course to anyone looking to upskill in data analysis. The content is well-structured, and the pacing is just right. I particularly enjoyed the sections on exploratory data analysis and data visualization with Pandas. – Shyam This course exceeded my expectations! The instructors are knowledgeable and engaging, and the course material is presented in a clear and concise manner. I appreciated the emphasis on hands-on learning, which allowed me to immediately apply what I learned to real-world datasets. – Mounika

 

Who can enroll for this course?

• Performance Testers who want to move into capacity planning and performance engineering
• DevOps Engineers and Site Reliability Engineers (SREs) working on scalable systems
• Backend Developers interested in system design and application scalability
• System Architects involved in high-availability and capacity decisions
• Database Administrators (DBAs) working on database performance and scaling
• Cloud Engineers working with AWS, Azure, or Kubernetes environments
• IT Professionals handling infrastructure, monitoring, and optimization
• Freshers looking to build a career in performance engineering and cloud technologies
• Anyone interested in learning capacity planning, workload modeling, and system optimization

 

What will I Learn by end of this course?

• Understand capacity planning concepts and complete capacity planning lifecycle
• Learn key metrics like throughput, latency, concurrency, and utilization
• Apply Little’s Law in real-world scenarios
• Perform workload modeling and user behavior analysis
• Build demand forecasting models using real-time data
• Plan capacity for applications, APIs, and microservices
• Identify performance bottlenecks in CPU, memory, and threads
• Design database capacity planning including storage and indexing
• Plan infrastructure capacity for CPU, memory, disk, and network
• Implement cloud capacity planning using AWS, Azure, and Kubernetes
• Understand auto-scaling strategies and performance trade-offs
• Design high availability (HA) and failover strategies
• Validate systems using performance testing for capacity planning
• Use observability and monitoring for continuous improvement
• Optimize applications, databases, and infrastructure systems

Salient Features:

• 30 Hours of Live Training
• Every session gets recorded and lifetime access to these videos will be given.
• Course Completion Certificate

 

Course syllabus:

MODULE 1: Foundations of Capacity Planning (Sessions 1–5)

Session 1: Capacity Planning – Why It Makes or Breaks Systems

• What capacity planning really means (beyond infra sizing)
• Real outage case studies (Banking, eCommerce, Payments)
• Capacity planning vs performance testing
• Where most organizations fail

Session 2: Capacity Planning Lifecycle

• Demand → Modeling → Validation → Monitoring → Optimization
• Short-term vs long-term planning
• Reactive vs proactive planning

Session 3: Core Terminologies & Metrics

• Throughput, latency, concurrency
• Peak vs average load
• Headroom, saturation, utilization
• Little’s Law (practical explanation)

Session 4: Types of Capacity Planning

• Business capacity planning
• Service capacity planning
• Resource capacity planning
• Component-level planning

Session 5: Capacity Planning in SDLC

• Agile, DevOps & CI/CD alignment
• Shift-left capacity planning
• Role of PE, SRE, Architects

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MODULE 2: Workload & Demand Analysis (Sessions 6–9)

Session 6: Understanding Business Demand

• Business events driving load
• Seasonal vs event-based traffic
• BFSI & FinTech traffic patterns

Session 7: User Behavior & Workload Modeling

• Think time, arrival rates
• User mix modeling
• Transaction criticality mapping

Session 8: Forecasting Techniques

• Linear growth
• Seasonal growth
• Event-based surge modeling
• Historical data analysis

Session 9: Creating Demand Forecast Models (Hands-on)

• Excel-based forecasting
• CAGR & growth assumptions
• Risk buffers

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MODULE 3: Application-Level Capacity Planning (Sessions 10–14)

Session 10: Application Architecture Deep Dive

• Monolith vs Microservices
• Synchronous vs asynchronous systems
• Stateless vs stateful services

Session 11: App Server Capacity Planning

• JVM sizing fundamentals
• Thread pools, connection pools
• Memory & GC impact

Session 12: API & Microservices Capacity Planning

• Per-service throughput modeling
• Downstream dependency impact
• Fan-out & cascading failures

Session 13: Caching & Performance Patterns

• Cache hit ratio impact
• CDN, Redis, in-memory caches
• Capacity savings through caching

Session 14: App-Level Bottleneck Identification

• CPU vs Memory vs Threads
• Vertical vs horizontal scaling decisions

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MODULE 4: Database Capacity Planning (Sessions 15–19)

Session 15: Database Workload Characteristics

• Read vs write intensive systems
• OLTP vs OLAP
• Transaction complexity

Session 16: DB Sizing & Growth Planning

• Storage growth forecasting
• Index growth
• Archival strategies

Session 17: DB Performance Metrics

• TPS, QPS
• Locking & contention
• Connection limits

Session 18: HA, DR & Replication Impact

• Active-active vs active-passive
• Replication lag
• Read replicas planning

Session 19: DB Bottleneck Simulation

• What breaks first and why
• Capacity buffers for peak events

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MODULE 5: Infrastructure & Network Capacity Planning (Sessions 20–23)

Session 20: CPU, Memory & Disk Planning

• Utilization thresholds
• IO wait & disk latency
• Overcommitment risks

Session 21: Network Capacity Planning

• Bandwidth estimation
• Latency & packet loss
• East-west vs north-south traffic

Session 22: Load Balancers & Gateways

• L7 vs L4 capacity
• SSL termination impact
• Failover scenarios

Session 23: Capacity Planning for HA Systems

• N+1, N+2 models
• Failure scenarios
• Degraded mode planning

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MODULE 6: Cloud Capacity Planning (Sessions 24–28)

Session 24: Cloud Capacity Planning Fundamentals

• Cloud is not infinite
• Quotas, limits, throttling

Session 25: Auto-scaling Strategies

• Horizontal vs vertical scaling
• Scaling policies
• Cold start impact

Session 26: Cost vs Performance Trade-offs

• Right sizing
• Over-provisioning vs under-provisioning
• Reserved vs on-demand

Session 27: Container & Kubernetes Capacity Planning

• Pod resource requests & limits
• Node sizing
• Cluster autoscaler logic

Session 28: Cloud Failure Case Studies

• When auto-scaling fails
• Misconfigured limits
• Cost explosions

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MODULE 7: Validation, Monitoring & Optimization (Sessions 29–32)

Session 29: Capacity Validation via Performance Testing

• How to design capacity-focused tests
• Breaking points vs safe limits

Session 30: Observability for Capacity Planning

• Golden signals
• Trend analysis
• Leading vs lagging indicators

Session 31: Continuous Capacity Planning

• Feedback loops
• Monitoring-driven forecasting
• Capacity debt concept

Session 32: Optimization Techniques

• App tuning
• DB tuning
• Infra & cloud optimization

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FAQs – Capacity Planning Training Course

1. What is capacity planning in simple terms?

Capacity planning is the process of determining how much system resources (CPU, memory, database, network) are needed to handle expected traffic without failures.

2. Is capacity planning different from performance testing?

Yes, performance testing checks system behavior under load, while capacity planning predicts future needs and ensures scalability.

3. Do I need coding knowledge for this course?

Basic technical understanding is helpful, but coding is not mandatory.

4. Will I learn real-time scenarios?

Yes, the course includes real outage case studies and practical use cases.

5. Does this course cover cloud platforms?

Yes, it includes AWS, Azure, Kubernetes, and auto-scaling strategies.

6. What tools are used in this course?

You will use Excel for forecasting and learn concepts applicable to tools used in performance engineering and monitoring.

7. What job roles can I apply for after this course?

You can apply for roles like Performance Engineer, SRE, DevOps Engineer, and Capacity Planner.

8. Why is capacity planning important?

It helps prevent system failures, reduces downtime, and ensures optimal performance during peak traffic.

How can I enroll for this course?

Enroll For Free Demo

OR

For any other details, Call me or Whatsapp me on +91-9133190573

 

Live Sessions Price:

For LIVE sessions – Offer price after discount is 229 USD 179 USD 119 USD Or  1900 INR 15000 INR 9900 Rupees.

 

Sample Course Completion Certificate:

Your course completion certificate looks like this……

 

 

Note:

To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.

To reiterate, moving from one course to another or shifting from one trainer to another (even if it is the same course) is not possible. Changing batches or trainers in any form is strictly not permitted.

We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.