Online Business Builder

From Beginner To Full Stack Hero

Tag: Advanced

  • System Design: Systems that Scale & Evolve

    System Design: Systems that Scale & Evolve

    🧠 System Design Bootcamp: Architect Scalable and Reliable Systems

    🧾 Course Description

    System Design is a critical skill for backend engineers, full stack developers, and tech leads. In “System Design Bootcamp”, you’ll learn how to architect scalable, fault-tolerant, and high-performance systems that power real-world applications like YouTube, Uber, WhatsApp, or Netflix.

    This course is structured around core design principles, component patterns, trade-offs, and interview-ready architectures. You’ll design end-to-end systems using tools like load balancers, databases, caching, queues, CDN, CAP theorem, and consistency models.

    Perfect for engineers preparing for interviews or architects designing real production systems.

    ✅ Key Benefits

    • 🧩 Design with Clarity — Break down complex problems into scalable components
    • 🌐 Real-World Readiness — Learn architectures behind well-known platforms
    • ⚖️ Balance Trade-offs — Understand consistency, availability, and performance
    • 🏗️ Deployable Patterns — Use queues, caching, replication, and sharding effectively
    • 🧪 Interview-Ready — Practice whiteboard sessions and system walkthroughs

    🎯 Pre-requisites

    • Strong knowledge of data structures & algorithms
    • Working experience with web apps or backend systems
    • Familiarity with network basics, databases, and APIs
    • No prior experience with distributed systems required

    📚 Curriculum Breakdown

    📘 Module 1: Foundations of System Design

    • What is system design?
    • Types of systems: OLTP vs OLAP, synchronous vs async
    • Requirements gathering (functional & non-functional)

    🔧 Module 2: Core Building Blocks

    • Load balancers, reverse proxies
    • Databases (SQL vs NoSQL), sharding
    • Caching strategies (Redis, Memcached)
    • CDNs, rate limiting, API gateway

    📶 Module 3: Scaling Techniques

    • Vertical vs horizontal scaling
    • Database replication & partitioning
    • Consistent hashing and data distribution
    • Auto-scaling and stateless architecture

    🔁 Module 4: Communication and Coordination

    • REST vs gRPC vs message queues
    • Message brokers: Kafka, RabbitMQ
    • Event-driven architecture and pub-sub models

    🔐 Module 5: Reliability, Fault Tolerance, and Security

    • CAP theorem, eventual consistency
    • Failover, retries, circuit breakers
    • Authentication and authorization design
    • Data security and rate limiting

    🛠️ Module 6: Monitoring and Maintenance

    • Observability: metrics, logs, tracing
    • Health checks and alerting
    • Blue-green and canary deployments

    🧪 Module 7: System Design Patterns

    • Microservices vs monolith vs SOA
    • CQRS, Saga pattern, database-per-service
    • API versioning and backward compatibility

    🚦 Module 8: Case Studies & Final Projects

    • Design real-world systems like:
      • URL shortener (Bitly)
      • Ride-sharing service (Uber backend)
      • Chat system (WhatsApp)
      • Video streaming platform (YouTube/Netflix)
    • Present architecture + justify decisions

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationIdeal For
    2 hours/day18–20 days (~3 weeks)Deep understanding with practice
    4 hours/day9–10 days (~1.5 weeks)Balanced case studies and theory
    6 hours/day5–6 days (bootcamp)Fast-track, intensive learners

    🎓 Outcome

    By the end of System Design Bootcamp, you will:

    • Design scalable and maintainable systems using real-world techniques
    • Explain your architectural decisions in interviews and discussions
    • Balance performance, consistency, and cost
    • Be ready for system design interviews, tech lead roles, or architect-level work
  • Full Stack Architecture: The Blueprint behind the App

    Full Stack Architecture: The Blueprint behind the App

    🏗️ Full Stack Architecture: Design Scalable, Maintainable Applications from Frontend to Backend

    🧾 Course Description

    Full Stack Architecture is about more than just coding both frontend and backend — it’s about designing software systems that are scalable, modular, secure, and maintainable. In “Full Stack Architecture”, you’ll learn how to plan, build, and document full-stack systems using modern web technologies (like React, Node.js, Spring Boot, MongoDB, and PostgreSQL) with clean separation of concerns, API design, data flow, deployment pipelines, and cloud integration.

    This course bridges the gap between developer and architect by teaching you how to think holistically — managing components like authentication, caching, state, APIs, databases, deployment, and observability.

    Perfect for senior developers, tech leads, and aspiring architects, this course turns your development experience into architecture expertise.

    ✅ Key Benefits

    • 🧱 End-to-End System Design — Learn how components interact from UI to DB
    • 📦 Modular Thinking — Design scalable, testable, and maintainable layers
    • 🔐 Secure & Performant — Handle auth, rate limiting, logging, and monitoring
    • 🚀 CI/CD & Cloud Ready — Plan pipelines and deployments from day one
    • 📚 Team-Ready Docs — Use diagrams, documentation, and handoff strategies

    🎯 Pre-requisites

    • Solid knowledge of frontend (React/Angular/Vue) and backend (Node.js, Java, Python) frameworks
    • Experience with REST APIs, databases, and basic DevOps practices
    • Optional: Exposure to Git, Docker, CI/CD tools, or cloud platforms (AWS/GCP/Azure)

    📚 Curriculum Breakdown

    📘 Module 1: Introduction to Full Stack Architecture

    • What is full stack architecture?
    • Layers of a modern full-stack app
    • Monolith vs microservices vs hybrid architectures

    🧠 Module 2: Frontend Architecture

    • Component structure and state management
    • API integration strategies
    • Optimizing for performance, accessibility, and SEO
    • CI for frontend builds

    🔗 Module 3: Backend Architecture

    • Layered design (Controller → Service → DAO)
    • REST vs GraphQL
    • Statelessness, error handling, validation
    • Microservice readiness

    🛢️ Module 4: Data Layer & Persistence

    • Choosing between SQL vs NoSQL
    • ORM usage, schema design, migrations
    • Connection pooling, query optimization
    • Caching with Redis/Memcached

    🔐 Module 5: Security & Auth Architecture

    • JWT, OAuth2, sessions vs tokens
    • Securing APIs and frontend routes
    • Data sanitization and encryption
    • Rate limiting and CORS

    ⚙️ Module 6: CI/CD & Deployment Architecture

    • Branching models and GitOps
    • Dockerizing apps and managing environments
    • CI pipelines for build → test → deploy
    • Deploying to cloud (Render, Railway, AWS, Vercel, Netlify)

    📈 Module 7: Monitoring & Observability

    • Logging (Winston, ELK), tracing, health checks
    • Uptime monitoring, error alerts
    • Integration with tools like Sentry, Prometheus

    🧪 Module 8: Final Architecture Project

    • Design & Document a Full Stack System:
      • Frontend (React/Vue)
      • Backend API (Node.js/Java)
      • DB layer (PostgreSQL/MongoDB)
      • Auth + API Gateway + CI/CD
      • Deployment to cloud

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationIdeal For
    2 hours/day16–18 days (~3 weeks)Great for part-time tech professionals
    4 hours/day8–9 days (~1.5 weeks)Balanced learning with project focus
    6 hours/day5–6 days (bootcamp)Intensive system design & labs

    🎓 Outcome

    By the end of Full Stack Architecture, you will:

    • Design scalable, production-ready full-stack applications
    • Choose the right components and patterns for each layer
    • Handle CI/CD pipelines, security, monitoring, and deployments
    • Confidently take on roles like Technical Architect, Full Stack Lead, or Solution Engineer
  • Cloud Deployment Strategies

    Cloud Deployment Strategies

    ☁️ Cloud Deployment Strategies: Ship Smarter, Scale Better

    🧾 Course Description

    Cloud deployment is no longer just about uploading code — it’s about deploying securely, reliably, and at scale. In “Cloud Deployment Strategies”, you’ll master the principles and techniques for delivering applications to public, private, and hybrid cloud platforms using modern DevOps approaches.

    This course explores multiple deployment strategies like blue-green, canary, rolling, and recreate, and shows how to implement them using tools like Docker, Kubernetes, GitHub Actions, and cloud platforms like AWS, Azure, or GCP.

    By the end, you’ll be confident designing and executing deployment pipelines that reduce downtime, mitigate risk, and deliver fast.

    ✅ Key Benefits

    • 🚀 Minimize Downtime — Learn zero-downtime deployments using modern strategies
    • 🔁 Progressive Delivery — Canary and rolling releases ensure stability and fast feedback
    • 🛡️ Risk-Controlled Shipping — Use automated rollbacks, traffic shifting, and versioning
    • 🌍 Cloud-Native Focus — Apply concepts on AWS, Azure, GCP, and Kubernetes
    • ⚙️ Tool-Integrated — Combine CI/CD tools, Docker, and infrastructure automation seamlessly

    🎯 Pre-requisites

    • Basic understanding of DevOps workflow and CI/CD pipelines
    • Familiarity with Docker, Git, and basic shell scripting
    • Optional: exposure to Kubernetes, cloud providers (AWS, GCP, Azure), or Terraform

    📚 Curriculum Breakdown

    🌐 Module 1: Introduction to Deployment

    • Evolution of software deployment
    • Deployment goals: speed, reliability, security
    • Overview of cloud environments: public, private, hybrid

    🔄 Module 2: Deployment Strategies Overview

    • Recreate (Basic)
    • Rolling
    • Blue-Green
    • Canary
    • A/B Testing and Shadow Deployment (intro)

    ⚙️ Module 3: Implementing Deployment Strategies

    • Docker-based deployment basics
    • Running rolling and recreate deployments using shell scripts & services
    • Blue-green and canary rollout using load balancers (Nginx/ALB)

    ☸️ Module 4: Kubernetes-Based Deployments

    • Deployments with kubectl and kubectl rollout
    • Rolling updates in Kubernetes
    • Canary deployments using labels, selectors, and services
    • Argo Rollouts (intro)

    📦 Module 5: Deployment Automation with CI/CD

    • GitHub Actions / GitLab CI pipeline integration
    • Deploy on commit, approve to production
    • Rollback on failure using conditions and health checks

    🔒 Module 6: Deployment Patterns & Monitoring

    • Health checks and readiness probes
    • Traffic splitting and feature flag integration
    • Logging, monitoring, and rollback automation

    🧪 Module 7: Final Project

    • End-to-End Deployment Project:
      • Containerized web app
      • CI/CD pipeline with GitHub Actions
      • Blue-Green deployment to staging/production
      • Auto-monitoring + rollback strategy

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationLearning Style
    2 hours/day14–16 days (~2–2.5 weeks)Ideal for learners with day jobs
    4 hours/day7–8 days (~1 week)Deep focus with real-world practice
    6 hours/day4–5 days (bootcamp)Fast-paced, project-driven track

    🎓 Outcome

    By the end of Cloud Deployment Strategies, you’ll:

    • Understand and compare multiple deployment strategies
    • Design zero-downtime pipelines using tools like Docker, Kubernetes, and GitHub Actions
    • Automate rollouts and rollbacks based on metrics and health
    • Be ready to implement real-world cloud deployments in startup or enterprise environments
  • Infrastructure as a Code (IaaC): Terraforming the Cloud

    Infrastructure as a Code (IaaC): Terraforming the Cloud

    🏗️ Infrastructure as Code Essentials: Automate Your Cloud the DevOps Way

    🧾 Course Description

    Infrastructure as Code (IaC) is a foundational DevOps practice that enables you to provision and manage cloud infrastructure using version-controlled code — making your infrastructure reliable, repeatable, and scalable.

    In “Infrastructure as Code Essentials”, you’ll learn the core concepts of IaC, hands-on usage of tools like Terraform, and real-world scenarios involving cloud provisioning, modularization, and automation. This course equips developers, DevOps engineers, and cloud architects to treat infrastructure the same way as application code — with testing, reusability, and CI/CD integration.

    ✅ Key Benefits

    • ⚙️ Automate Infrastructure Creation — No more manual provisioning or drift
    • 🔁 Version-Controlled & Reproducible — Rollback changes just like source code
    • ☁️ Multi-Cloud Compatible — Use Terraform to provision AWS, Azure, GCP, and more
    • 📦 Modular & Scalable — Build reusable and parameterized infrastructure modules
    • 🔐 Secure by Default — Manage secrets, policies, and configurations consistently

    🎯 Pre-requisites

    • Basic understanding of cloud computing (e.g., AWS EC2, S3, IAM concepts)
    • Familiarity with command-line interface (CLI)
    • Optional but helpful: Git, YAML/JSON syntax, or CI/CD basics
    • No prior experience with Terraform or IaC tools required

    📚 Curriculum Breakdown

    📘 Module 1: Introduction to Infrastructure as Code

    • What is IaC? Benefits & challenges
    • Declarative vs imperative IaC
    • Popular IaC tools: Terraform, CloudFormation, Pulumi (overview)

    ⚙️ Module 2: Terraform Basics

    • Installing Terraform
    • HCL syntax, provider blocks, and resources
    • Creating and destroying infrastructure (init, plan, apply, destroy)

    🧱 Module 3: Variables, Outputs & State

    • Defining variables and input parameters
    • Output values and references between resources
    • Terraform state files and state locking

    📦 Module 4: Modular Infrastructure Design

    • Breaking configs into modules
    • Passing variables to modules
    • Using remote modules from the Terraform Registry

    ☁️ Module 5: Real-World Cloud Provisioning

    • Provision AWS infrastructure (EC2, VPC, IAM, S3)
    • Reusable VPC + subnet modules
    • Intro to Azure and GCP equivalents

    🔐 Module 6: Managing Secrets & Backends

    • Using environment variables and .tfvars
    • Storing state in S3 and securing with DynamoDB locking
    • Terraform Cloud & remote workspaces (intro)

    🧪 Module 7: Project – Infrastructure Pipeline

    • Deploy a complete AWS environment using Terraform
      • VPC + EC2 + RDS + S3
      • Parameterized variables
      • Modular structure
      • Remote backend
      • Provision via CI/CD (GitHub Actions or Jenkins)

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationLearning Style
    2 hours/day12–14 days (~2 weeks)Ideal for professionals and learners
    4 hours/day6–7 days (1 week)Balanced theory + hands-on practice
    6 hours/day3–4 days (bootcamp)Fast-track with real-world project

    🎓 Outcome

    By the end of Infrastructure as Code Essentials, you’ll:

    • Write reusable infrastructure scripts using Terraform
    • Provision and manage cloud infrastructure with automation
    • Implement infrastructure pipelines integrated with CI/CD
    • Be ready for DevOps, Cloud Engineer, or Platform Architect roles
  • Microservices Mindset

    Microservices Mindset

    🧩 Microservices Decoded: Design Scalable Systems with Confidence

    🧾 Course Description

    Microservices architecture is the backbone of modern enterprise and cloud-native systems. In “Microservices Decoded”, you’ll learn how to design, build, and deploy distributed applications that are scalable, resilient, and independently deployable.

    This course covers everything from breaking a monolith into services, communication strategies, service discovery, and inter-service security — all explained with real-world scenarios, design patterns, and optional implementation using Spring Boot, Docker, and API Gateway.

    Whether you’re a developer, architect, or DevOps professional, this course will give you the conceptual clarity and system-level thinking needed to excel in a microservices environment.

    ✅ Key Benefits

    • 🧠 Think in Systems, Not Scripts — Learn to design modular, scalable architectures
    • 🔗 Build for Independence — Avoid bottlenecks by decoupling services
    • 📦 Polyglot Flexibility — Use the best tech stack for each service
    • 🚀 Deploy Faster & Smarter — Improve delivery with independent pipelines
    • 💥 Resilience by Design — Handle failures, retries, and distributed state like a pro

    🎯 Pre-requisites

    • Solid understanding of REST APIs, HTTP, and basic backend development
    • Familiarity with Java (Spring Boot) or any web framework (Node.js, Python, etc.)
    • Basic knowledge of Docker, Git, and CI/CD concepts recommended
    • Optional: exposure to monolithic app structure

    📚 Curriculum Breakdown

    🔧 Module 1: Introduction to Microservices

    • What are Microservices?
    • Monolith vs Microservices
    • Benefits & trade-offs of distributed architecture

    🧱 Module 2: Service Decomposition

    • Identifying service boundaries
    • Domain-Driven Design (DDD) basics
    • Bounded contexts and database-per-service pattern

    🌐 Module 3: Communication Between Services

    • RESTful HTTP, messaging queues (RabbitMQ, Kafka)
    • Synchronous vs asynchronous
    • Circuit breakers, retries, fallbacks

    🔁 Module 4: Service Discovery and API Gateway

    • Centralized routing with API Gateway
    • Load balancing and dynamic service discovery
    • Netflix Eureka, Consul (conceptual)

    🔒 Module 5: Security and Config Management

    • Inter-service authentication (JWT, OAuth2)
    • Centralized config with Spring Cloud Config or Vault
    • Environment-specific configurations

    ⚙️ Module 6: Observability & Monitoring

    • Centralized logging with ELK
    • Distributed tracing (Zipkin, Jaeger)
    • Metrics collection (Prometheus, Grafana)

    🧪 Module 7: Practical Microservice Project (Spring Boot-based)

    • Build 3 microservices (e.g., User, Order, Inventory)
    • Use REST communication
    • Add service registry + config server + gateway
    • Include fault tolerance (Hystrix/resilience4j)
    • Deploy using Docker + Docker Compose

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationNotes
    2 hours/day15–18 days (~3 weeks)Ideal for professionals & part-timers
    4 hours/day8–9 days (~1.5 weeks)Balanced theory + practice
    6 hours/day5–6 days (bootcamp)Project-heavy accelerated learning

    🎓 Outcome

    By the end of Microservices Decoded, you will:

    • Understand microservice design principles, trade-offs, and best practices
    • Decompose monoliths into maintainable, scalable services
    • Handle inter-service communication, observability, and service failure
    • Be ready to work on enterprise-grade microservice systems using Spring Boot, Docker, and cloud platforms
  • Kubernetes: The Cloud Orchestrator

    Kubernetes: The Cloud Orchestrator

    ☸️ Kubernetes Unlocked: Orchestrate Containers Like a Pro

    🧾 Course Description

    Kubernetes (K8s) is the industry-standard container orchestration platform used to deploy, scale, and manage modern applications across clusters of machines. In “Kubernetes Unlocked”, you’ll gain hands-on experience with deploying containerized apps, managing clusters, rolling updates, autoscaling, and service discovery.

    This course bridges theory and practice with real-world examples, YAML configs, and CLI workflows. Whether you’re a DevOps engineer, backend developer, or system architect, Kubernetes is essential to operate at scale — and this course gets you there fast.

    ✅ Key Benefits

    • ☸️ Master K8s Core Concepts — Pods, deployments, services, volumes, and namespaces
    • 🔁 Automate Scaling & Rollouts — Keep apps reliable under load and during updates
    • 🌐 Build Real Clusters — Use Minikube, Kind, or cloud (EKS/GKE) for real deployments
    • 🔄 Integrate with CI/CD — Learn how K8s fits into DevOps pipelines
    • 📦 Foundation for Helm & Cloud-Native Apps — Prepares you for advanced orchestration

    🎯 Pre-requisites

    • Basic Docker knowledge (containers, images, Dockerfile, docker run)
    • Familiarity with Linux CLI
    • Recommended: understanding of YAML, Git, and basic networking

    📚 Curriculum Breakdown

    🔧 Module 1: Kubernetes Overview

    • Why Kubernetes? History and use cases
    • Architecture: Master, Node, API Server, Scheduler, etcd

    🛠️ Module 2: Setting Up Your Cluster

    • Install Minikube / Kind / Play with K8s (cloud playgrounds)
    • CLI tools: kubectl, kubeadm
    • Cluster configuration and context switching

    🧱 Module 3: Deploying Your First App

    • Pods and ReplicaSets
    • Deployments and rollout strategies
    • Labels, selectors, and annotations

    🌐 Module 4: Services & Networking

    • ClusterIP, NodePort, LoadBalancer
    • DNS in Kubernetes
    • Ingress controllers and ingress rules (basic)

    📦 Module 5: Volumes and ConfigMaps

    • PersistentVolumes and PersistentVolumeClaims (PVC)
    • ConfigMaps and Secrets for environment management

    📈 Module 6: Scaling, Health Checks & Auto-restarts

    • Horizontal Pod Autoscaler
    • Readiness and liveness probes
    • Rolling updates and rollbacks

    🧪 Module 7: Project — Deploy a Full App

    • Deploy a multi-container web app (frontend + backend + DB)
    • Expose via LoadBalancer or Ingress
    • Use ConfigMaps, volumes, and scaling

    ☁️ Module 8: (Optional Bonus) — Cloud Integration

    • Intro to Kubernetes in AWS/GCP (EKS, GKE)
    • YAML vs Helm basics

    ⏱️ Estimated Duration

    Daily Study TimeEstimated DurationNotes
    2 hours/day14–16 days (~2 weeks)Detailed with hands-on labs
    4 hours/day7–8 days (1 week)Practical & project-focused
    6 hours/day4–5 days (intensive)Ideal for bootcamp learners

    🎓 Outcome

    By the end of Kubernetes Unlocked, you’ll:

    • Deploy and manage production-ready apps in Kubernetes
    • Understand Pods, Services, Volumes, Ingress, and Scaling
    • Be ready to work with cloud-native tools (Helm, Prometheus, ArgoCD)
    • Confidently pursue DevOps, SRE, or Platform Engineering roles