System Design Training

RexGalaxy Academy's System Design Training is a practical and interview-focused program designed for learners who want to understand how real-world software systems are planned, scaled, secured and maintained. The course is useful for developers, backend learners, full stack learners, cloud learners, DevOps learners and anyone preparing for technical interviews where architecture thinking is required.

This training starts from basic architecture concepts and gradually moves into APIs, databases, caching, load balancing, queues, microservices, distributed systems, cloud deployment, reliability, observability and security. Students learn how to convert a requirement into a clear design by identifying users, traffic, data flow, services, databases, scaling needs and failure points.

The course is not limited to memorizing diagrams. Learners practice step-by-step design thinking: clarify requirements, estimate scale, choose components, design APIs, model data, explain trade-offs, handle bottlenecks and present a final architecture professionally. Real examples such as URL shortener, chat system, file storage, video platform, ecommerce system, notification service and ride booking system are used to build practical understanding.

Students should be able to:

• Understand how scalable software systems are designed from requirements to deployment.

• Design APIs, databases, caches, queues, load balancers and backend services for real applications.

• Explain trade-offs between SQL and NoSQL, monolith and microservices, consistency and availability, latency and cost.

• Build architecture diagrams for web apps, mobile apps, distributed systems and cloud-ready platforms.

• Understand reliability, fault tolerance, observability, security and performance optimization basics.

• Prepare confidently for system design interviews with structured answers and real-world case studies.

Start with the core mindset needed to design reliable and scalable software systems.

• Understand what system design means and why it is important for developers, architects and engineering teams.

• Learn the difference between low-level design, high-level design, architecture design and infrastructure planning.

• Understand common system components such as clients, servers, databases, APIs, caches, queues, load balancers and storage systems.

• Learn how software systems evolve from simple applications to scalable distributed platforms.

• Understand functional requirements, non-functional requirements, constraints, trade-offs and assumptions.

• Practice thinking in terms of users, requests, data, services, storage, latency, availability and failure points.

• Learn how to draw architecture diagrams with clear components, arrows, flows and responsibilities.

• Understand important design qualities such as scalability, reliability, maintainability, security and performance.

• Practice converting a simple app requirement into a high-level system diagram.

• Outcome: build architecture thinking and understand how to approach system design problems from scratch.

Understand how systems communicate using clients, servers, protocols, APIs and network basics.

• Learn client-server architecture and how browsers, mobile apps and backend services communicate.

• Understand HTTP, HTTPS, request-response flow, headers, status codes, methods and payloads.

• Learn REST API basics including endpoints, resources, request methods, response formats and versioning.

• Understand API gateway awareness, authentication flow and service-to-service communication.

• Learn synchronous versus asynchronous communication and when each approach is suitable.

• Understand WebSockets, polling and real-time communication awareness for chat or notification systems.

• Practice designing API endpoints for common systems such as user login, product listing, order creation and search.

• Learn API documentation basics, request validation, error handling and rate limiting awareness.

• Understand network latency, timeouts, retries and how communication failures affect system design.

• Outcome: design clear API and communication flows for modern software systems.

Learn how to clarify requirements, estimate scale and plan system capacity before choosing technology.

• Understand why requirement clarification is the first step in any system design interview or project.

• Separate functional requirements from non-functional requirements such as performance, uptime, security and scalability.

• Learn how to ask useful questions about users, features, traffic, data size, read-write ratio and business priorities.

• Estimate daily active users, requests per second, storage growth, bandwidth, database writes and cache needs.

• Understand read-heavy, write-heavy, real-time and batch-processing system patterns.

• Learn simple back-of-the-envelope estimation techniques without overcomplicating calculations.

• Understand capacity planning for compute, storage, network, database and cache layers.

• Practice requirement and estimation exercises for URL shortener, chat app, ecommerce app and file storage system.

• Learn how to state assumptions clearly when exact numbers are unknown.

• Outcome: plan scalable systems using requirement clarity and practical estimation.

Design data storage layers using SQL, NoSQL, indexing, schema planning and data access patterns.

• Understand relational databases, tables, rows, columns, primary keys, foreign keys and normalization awareness.

• Learn NoSQL database types including key-value, document, column-family and graph database awareness.

• Compare SQL and NoSQL based on consistency, relationships, query needs, scale and flexibility.

• Design database schemas for users, products, orders, posts, messages, payments and activity logs.

• Understand indexes, query performance, search patterns and why database design affects speed.

• Learn partitioning, sharding, replication and read replica awareness at a conceptual level.

• Understand transactions, ACID properties, eventual consistency and data integrity basics.

• Practice data modelling for systems such as ecommerce, chat, URL shortener and social media feed.

• Learn common database mistakes such as over-normalization, missing indexes, hot partitions and unclear access patterns.

• Outcome: choose and design database layers based on real application requirements.

Improve system performance using caching, CDN, data locality and optimization strategies.

• Understand caching and why it reduces database load, latency and repeated computation.

• Learn cache layers including browser cache, CDN cache, application cache and database query cache awareness.

• Understand common caching tools and patterns such as Redis awareness, key-value cache and cache-aside strategy.

• Learn cache invalidation, TTL, stale data, cache warming and cache eviction concepts.

• Understand CDN usage for static files, images, videos, scripts and globally distributed content delivery.

• Learn how caching improves read-heavy systems such as product pages, news feeds, dashboards and media platforms.

• Understand performance metrics such as latency, throughput, response time and p95/p99 awareness.

• Practice adding caching and CDN layers to ecommerce, video streaming and file delivery system diagrams.

• Learn trade-offs between speed, freshness, complexity and storage cost.

• Outcome: design faster systems by applying caching and content delivery strategies correctly.

Manage incoming traffic using load balancers, reverse proxies, routing and high availability patterns.

• Understand what load balancing is and why it prevents a single server from becoming a bottleneck.

• Learn Layer 4 and Layer 7 load balancing awareness and common routing strategies.

• Understand reverse proxy concepts and how Nginx or cloud load balancers sit in front of application servers.

• Learn health checks, failover, sticky sessions and target group awareness.

• Understand horizontal scaling versus vertical scaling and when each approach is useful.

• Design multi-server architecture for web applications using load balancers and multiple app instances.

• Learn how load balancing supports high availability, traffic distribution and zero-downtime deployment awareness.

• Understand rate limiting, throttling and traffic protection against overload or abuse.

• Practice adding load balancers to chat, ecommerce, booking and API-based system designs.

• Outcome: design systems that handle more traffic and remain available during server failures.

Use queues and event-driven architecture to process tasks asynchronously and make systems more reliable.

• Understand why not every task should be processed immediately in the user request path.

• Learn message queue concepts including producers, consumers, topics, brokers, events and workers.

• Understand asynchronous processing for emails, notifications, payments, video processing and background jobs.

• Learn queue tools awareness such as Kafka, RabbitMQ, SQS or similar messaging platforms.

• Understand retry logic, dead-letter queues, idempotency, ordering, duplication and delivery guarantees.

• Design event-driven systems where services communicate through events instead of tight coupling.

• Learn how queues improve reliability, traffic smoothing and user experience in high-load systems.

• Practice designing notification service, order processing, logging pipeline and video processing architecture.

• Understand trade-offs between simplicity, delay, consistency and operational complexity.

• Outcome: use asynchronous design patterns to build scalable and resilient backend systems.

Understand monolithic and microservice architecture and learn how services are separated responsibly.

• Compare monolithic architecture, modular monolith, microservices and serverless service models.

• Understand when a monolith is useful and when microservices become necessary.

• Learn service boundaries, domain-driven thinking, ownership, APIs and independent deployment concepts.

• Understand service discovery, API gateway awareness, inter-service communication and shared database problems.

• Learn common microservice patterns such as database per service, circuit breaker awareness and service orchestration.

• Understand challenges such as distributed debugging, network failures, data consistency and operational overhead.

• Practice splitting an ecommerce system into user, product, cart, order, payment and notification services.

• Learn how containerization and cloud platforms support microservice deployment.

• Understand trade-offs between speed of development, scalability, complexity and team size.

• Outcome: design service-based architectures without blindly overusing microservices.

Learn distributed system principles used in large-scale platforms and high-availability systems.

• Understand distributed systems and why multiple machines create coordination, consistency and failure challenges.

• Learn replication, partitioning, sharding, leader-follower awareness and consensus concept awareness.

• Understand CAP theorem at a practical level: consistency, availability and partition tolerance.

• Learn strong consistency, eventual consistency and where each model appears in real systems.

• Understand fault tolerance, redundancy, failover, retries, timeouts and graceful degradation.

• Learn idempotency, distributed locks awareness and duplicate request handling.

• Understand data consistency issues in payments, orders, inventory, messaging and collaborative systems.

• Practice explaining trade-offs for systems where correctness, availability and latency compete.

• Study examples such as distributed database, chat delivery, payment processing and inventory management.

• Outcome: reason about reliability and consistency in systems that run across many servers.

Connect architecture ideas with cloud deployment, infrastructure components and production environments.

• Understand cloud architecture basics including compute, storage, databases, networking, DNS and monitoring.

• Learn how AWS or similar cloud platforms host applications using servers, load balancers, databases and storage services.

• Understand deployment environments such as development, staging and production.

• Learn container deployment awareness using Docker and Kubernetes at a high level.

• Understand infrastructure planning for public/private networks, security groups, subnets and access control awareness.

• Learn static content hosting, database hosting, API hosting and media storage architecture patterns.

• Understand CI/CD awareness and how code changes reach production systems safely.

• Learn backup, disaster recovery, multi-region awareness and high availability planning.

• Practice drawing cloud-ready architecture for a web application or mobile backend.

• Outcome: connect system design diagrams with real-world cloud infrastructure and deployment planning.

Design systems with observability, security, reliability and cost awareness from the beginning.

• Understand observability basics including logs, metrics, traces, dashboards and alerts.

• Learn how monitoring helps teams detect failures, performance problems and unusual system behavior.

• Understand reliability concepts such as SLA, SLO, uptime, error budgets and incident response awareness.

• Learn security basics including authentication, authorization, encryption, rate limiting and secure API design.

• Understand data privacy, access control, secrets management and safe storage of sensitive information.

• Learn backup, recovery, audit logs and compliance awareness for production systems.

• Understand cost-aware design including over-provisioning, storage cost, compute cost and data transfer cost.

• Practice adding monitoring, alerts, security layers and backup strategy to architecture diagrams.

• Learn common production mistakes such as no logs, no alerts, weak access control and unclear ownership.

• Outcome: design systems that are not only scalable, but also safe, observable, reliable and cost-conscious.

Practice complete system design case studies and prepare structured answers for interviews.

• Learn a repeatable interview framework: clarify requirements, estimate scale, define APIs, design data model, draw architecture and discuss trade-offs.

• Practice designing a URL shortener with API, database, cache, redirection and analytics awareness.

• Practice designing a chat application with real-time messaging, presence, storage, queues and delivery status.

• Practice designing file storage or Google Drive-like systems with upload, metadata, storage, sharing and permissions.

• Practice designing ecommerce systems with product catalog, cart, orders, payments, inventory and notifications.

• Practice designing video or media platforms with upload, processing, CDN, recommendations awareness and playback flow.

• Learn how to explain bottlenecks, scaling plans, failure handling, security and monitoring in every design.

• Prepare architecture diagrams, trade-off notes and interview-friendly explanations for portfolio and revision.

• Review common mistakes such as jumping to technology, ignoring requirements, weak database design and unclear trade-offs.

• Outcome: become confident in solving system design problems and explaining architecture professionally.