Date: 2024-06-22
I will stay laser-focused on my goal.
URL Shortening Service
Hint: Use hash functions for URL mapping, a key-value store like Redis for storage, handle collisions with re-hashing or suffix addition, and ensure the system scales horizontally.
Diagram: 👤 => 🌐 => 🔀 => 🗄️
Cache System for a Web Application
Hint: Use in-memory caches like Redis or Memcached, implement cache eviction policies (LRU, LFU), and ensure cache invalidation on data update.
Diagram: 👤 => 🌐 => 🗄️🔄(Redis/Memcached)
Scalable Web Crawling System
Hint: Use distributed worker nodes, task queues like RabbitMQ or Kafka, URL deduplication, politeness policies (rate limiting), and storage for crawled data.
Diagram: 🌐 => 🐇(RabbitMQ) => 🏗️(Workers) => 🗂️
Online Ticket Booking System
Hint: Implement ACID transactions for ticket purchases, use seat locking mechanisms, handle concurrency with optimistic/pessimistic locking, and use load balancers to distribute traffic.
Diagram: 👤 => 🌐 => 💳 => 🏷️🔒 => 🗄️
Social Media Feed System
Hint: Use a publish-subscribe model with Kafka, maintain denormalized tables for feeds, use ranking algorithms for content relevance, and cache results for fast retrieval.
Diagram: 👤 => 🌐 => 📨(Kafka) => 🗂️ => 🗃️
File Storage and Sharing Service
Hint: Utilize object storage like AWS S3, implement data redundancy and replication, handle file metadata in a relational database, and secure access with ACLs and encryption.
Diagram: 👤 => 🌐 => 🗄️(Metadata) + 🗂️(S3)
Search Autocomplete System
Hint: Use trie or prefix tree data structures, cache popular queries, implement type-ahead search with fuzzy matching, and optimize for low-latency responses.
Diagram: 👤 => 🌐 => 🌲 => 🗃️
Global Content Distribution Network (CDN)
Hint: Deploy edge servers close to users, use caching strategies (TTL, cache hierarchy), implement load balancing, and ensure content invalidation.
Diagram: 👤 => 🌐 => 🌎🌍🌏 (CDN)
Messaging System like WhatsApp
Hint: Use message brokers like Kafka for message queuing, end-to-end encryption for security, store messages in partitioned databases, and ensure high availability.
Diagram: 👤 => 🌐 => 🔐 => 📨(Kafka) => 🗂️
Online Payment System
Hint: Ensure security with PCI compliance, use transactional databases, idempotent API endpoints, and multi-layered authentication (2FA, tokens).
Diagram: 👤 => 🌐 => 🏦 => 🔒
Real-Time Collaborative Document Editing
Hint: Implement operational transformation (OT) or conflict-free replicated data types (CRDTs), use WebSockets for real-time updates, and version control for document states.
Diagram: 👤 => 🌐 => 🕸️ (WebSocket) => 📝
Scalable Notification Service
Hint: Use a message queue for asynchronous processing, push notification services (e.g., Firebase), store user preferences, and ensure delivery guarantees.
Diagram: 👤 => 🌐 => 📨(Queue) => 📲
Recommendation System for E-commerce
Hint: Implement collaborative filtering, content-based filtering, use real-time data processing with Spark or Flink, and personalize recommendations with user profiles.
Diagram: 👤 => 🌐 => 🧠 => 🗄️
Ride-Sharing Service
Hint: Use GPS tracking, implement real-time matching algorithms, use scalable databases for storing ride details, and ensure low-latency communication.
Diagram: 👤 => 📍 => 🌐 => 🧮
Real-Time Analytics System
Hint: Use stream processing frameworks like Apache Flink, data warehouses like Redshift, and real-time visualization tools like Grafana or Tableau.
Diagram: 👤 => 🌐 => 📊 (Flink) => 🗂️
Managing User Sessions Across Devices
Hint: Implement centralized session storage with Redis, use session tokens or JWTs, secure cookies, and ensure session expiration policies.
Diagram: 👤 => 🌐 => 🗄️ (Redis) => 🔑
Video Streaming Service
Hint: Use CDNs for content delivery, adaptive bitrate streaming for various network conditions, video encoding with formats like H.264, and scalable storage for video files.
Diagram: 👤 => 🌐 => 📹 => 🌎🌍🌏
Server Performance Monitoring System
Hint: Use metrics collection tools like Prometheus, alerting systems like Grafana, log aggregation with ELK stack, and visualize performance data on dashboards.
Diagram: 👤 => 🌐 => 📊 => 📉
API Rate Limiter
Hint: Implement token bucket algorithms, use distributed rate limiting with Redis, and provide throttling to prevent abuse, logging and monitoring for insights.
Diagram: 👤 => 🌐 => ⏳ => 🗄️ (Redis)
Distributed Database
Hint: Use data partitioning (sharding), implement replication (master-slave, multi-master), handle consistency with protocols like Paxos or Raft, and optimize for CAP theorem trade-offs.
Diagram: 👤 => 🌐 => 📊 => 🗄️
Log Collection and Analysis
Hint: Use log aggregation tools like ELK stack, store logs in a distributed file system, index logs for fast search, and analyze logs with Kibana or Grafana.
Diagram: 👤 => 🌐 => 📋 => 📊
Microservices Architecture for E-commerce
Hint: Implement service discovery (Consul, Eureka), API gateways (Kong, Nginx), container orchestration with Kubernetes, and inter-service communication with gRPC or REST.
Diagram: 👤 => 🌐 => 🗄️ (Services) => 🚢 (K8s)
Fault-Tolerant Distributed System
Hint: Implement redundancy with replication, use consensus algorithms like Raft, ensure automatic failover, and handle network partitions gracefully.
Diagram: 👤 => 🌐 => 🔄 => 🗄️
Scalable Chat Application
Hint: Use WebSockets for real-time communication, message queues for asynchronous processing, partition databases for horizontal scaling, and implement read replicas.
Diagram: 👤 => 🌐 => 🕸️ (WebSocket) => 📊
Processing Large-Scale Data Streams
Hint: Use stream processing frameworks like Kafka Streams, Apache Flink, or Spark Streaming, and scalable storage solutions like HDFS or S3.
Diagram: 👤 => 🌐 => 📊 => 🗄️
Geographically Distributed System
Hint: Implement data replication across regions, use load balancing to optimize latency, and handle eventual consistency with conflict resolution mechanisms.
Diagram: 👤 => 🌐 => 🌎🌍🌏 => 🔄
Load Balancer
Hint: Use reverse proxies like Nginx or HAProxy, implement consistent hashing for stateful services, and perform health checks to route traffic away from unhealthy nodes.
Diagram: 👤 => 🌐 => 🌀 (Balancer) => 🗄️
Web Analytics System
Hint: Use event tracking with tools like Google Analytics or custom solutions, data warehousing with BigQuery, and real-time processing with Spark Streaming.
Diagram: 👤 => 🌐 => 📊 => 🗄️
Search Engine for E-commerce Website
Hint: Implement inverted indexes, use Elasticsearch or Solr, relevance ranking algorithms, and cache search results for performance.
Diagram: 👤 => 🌐 => 🔍 => 🗄️
Real-Time Bidding System for Online Advertising
Hint: Use low-latency data processing with Apache Kafka, auction algorithms, bidder management systems, and ensure scalability.
Diagram: 👤 => 🌐 => 📨 => 🗄️
Content Recommendation Engine
Hint: Implement machine learning models for personalized recommendations, use collaborative and content-based filtering, and perform A/B testing for evaluation.
Diagram: 👤 => 🌐 => 🧠 => 🗄️
Multi-Tenant SaaS Application
Hint: Implement tenant isolation with separate databases or schemas, use shared infrastructure for efficiency, and manage tenant-specific configurations.
Diagram: 👤 => 🌐 => 🗄️ (Tenants) => 🔒
Fraud Detection in Transactions
Hint: Use anomaly detection algorithms, real-time data processing with Kafka or Flink, machine learning models, and implement alerts for suspicious activities.
Diagram: 👤 => 🌐 => 🧠 => 🚨
Distributed File System
Hint:
Use data replication for fault tolerance, implement erasure coding for storage efficiency, handle consistency models, and provide a unified namespace. - Diagram: 👤 => 🌐 => 🗄️ => 🌐
Scalable API Gateway
Hint: Use Kong or Nginx for API management, implement rate limiting, authentication, and service discovery, and provide logging and monitoring.
Diagram: 👤 => 🌐 => 🌀 (Gateway) => 🗄️
User Permissions and Roles Management
Hint: Implement Role-Based Access Control (RBAC), use ACLs for fine-grained permissions, and maintain audit logs for security compliance.
Diagram: 👤 => 🌐 => 🔐 => 🗄️
Notification System for Social Media Platform
Hint: Use message brokers for queueing notifications, store user preferences, implement delivery guarantees, and provide push notifications.
Diagram: 👤 => 🌐 => 📨 (Queue) => 📲
Metrics Collection and Aggregation System
Hint: Use time-series databases like InfluxDB, collect metrics with Prometheus, aggregate data for analysis, and visualize with Grafana.
Diagram: 👤 => 🌐 => 📊 => 🗄️
A/B Testing System
Hint: Implement experiment management, use user segmentation for targeting, collect and analyze data for statistical significance, and iterate based on results.
Diagram: 👤 => 🌐 => 🔀 (Test) => 📊
Database Sharding Strategy
Hint: Use horizontal partitioning, choose appropriate shard keys, handle rebalancing and resharding, and ensure consistency and availability.
Diagram: 👤 => 🌐 => 📊 => 🗄️
Handling High-Traffic Spikes
Hint: Implement autoscaling with cloud services, use load balancers to distribute traffic, and implement queueing mechanisms to handle bursts.
Diagram: 👤 => 🌐 => 🌀 (Balancer) => 🗄️
Service Discovery for Microservices
Hint: Use service registries like Consul or Eureka, implement health checks, provide dynamic configuration, and ensure high availability.
Diagram: 👤 => 🌐 => 🗄️ (Services) => 🔍
Scalable Leaderboard System
Hint: Use sorted sets in Redis for ranking, implement efficient query mechanisms, handle updates in real-time, and cache results for performance.
Diagram: 👤 => 🌐 => 🗄️ (Redis) => 🏆
Real-Time Event Processing System
Hint: Use event-driven architecture with Kafka or Kinesis, implement stream processing with Flink, and ensure scalability and fault tolerance.
Diagram: 👤 => 🌐 => 📨 (Kafka) => 📊
Backup and Disaster Recovery System
Hint: Implement regular data snapshots, automate backups, ensure data redundancy, and create failover plans for quick recovery.
Diagram: 👤 => 🌐 => 🗄️ => 🔄 (Backup)
High-Availability System for Critical Services
Hint: Use redundancy, implement failover mechanisms, ensure low-latency data replication, and meet SLAs for uptime.
Diagram: 👤 => 🌐 => 🔄 => 🗄️
Workflow Orchestration System
Hint: Use workflow engines like Apache Airflow, define task dependencies, implement retries and error handling, and provide monitoring.
Diagram: 👤 => 🌐 => 🧩 => 📊
Rate-Limiting System for APIs
Hint: Implement token bucket or leaky bucket algorithms, use distributed rate limiting with Redis, monitor usage patterns, and provide alerts.
Diagram: 👤 => 🌐 => ⏳ => 🗄️ (Redis)
Data Synchronization Across Multiple Regions
Hint: Implement eventual consistency, use conflict resolution strategies, replicate data with tools like Cassandra or DynamoDB, and optimize for low-latency access.
Diagram: 👤 => 🌐 => 🌎🌍🌏 => 🔄
High-Performance In-Memory Data Store
Hint: Use in-memory databases like Redis or Memcached, partition data for scalability, ensure replication for high availability, and optimize data structures for performance.
Diagram: 👤 => 🌐 => 🗄️ (Redis) => 💾