Scale from Zero to Millions of Users
Understanding how systems evolve from a single server to a highly available, distributed tier-based architecture.
Core Architecture Concepts
- DNS Routing & CDN caching for static content
- Load Balancers (Nginx/HAProxy) for horizontal scaling
- Database replication (Master/Replica) and read/write splitting
- Stateless web tier using external session storage (Redis)
Trade-offs & Challenges
Moving from vertical to horizontal scaling requires handling state-sharing, data consistency across replicas, and ensuring load balancer health checks are robust to avoid single points of failure (SPOF).
Implemented in my project:
3-Tier Cloud Migration App
Implemented horizontal stateless containers behind an Nginx load balancer reverse proxy, using PostgreSQL replication practices. Managed configurations via Docker Compose for easy deployment scaling.
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Design a Notification System
Building scalable and reliable messaging pipelines across notification channels (SMS, Email, Push, Webhooks, Telegram).
Core Architecture Concepts
- Asynchronous message queues (RabbitMQ/Kafka) to decouple notification triggers from delivery
- Rate limiting to prevent alert fatigue and network throttling
- Retry mechanisms with exponential backoff for failed sends
- Template engines for message personalization and separation of concerns
Trade-offs & Challenges
Guaranteeing "at-least-once" delivery versus preventing duplicate messages. Setting proper rate limits at the user level to protect channel reputation and enhance UX.
Implemented in my project:
Network & System Monitor
Built a custom notification gateway with Telegram bot integration, incorporating threshold-based rate limiting to prevent spamming notifications when a metric oscillates around limit thresholds.
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Metrics Monitoring & Alerting System
Designing infrastructure to collect, store, and query high-volume time-series data for system health tracking.
Core Architecture Concepts
- Pull vs. Push collection: Pull (Prometheus scrapes endpoints) reduces server-side collection logic complexity
- Time-Series Database (TSDB) storage optimization for write-heavy metric logging
- Metrics aggregation, downsampling, and custom query languages (PromQL)
- Alert routing, deduplication, and integration with incident response (PagerDuty, Slack)
Trade-offs & Challenges
Pull model requires service discovery but protects the server from push surges. TSDB requires efficient compression algorithms (like Gorilla) to handle billions of telemetry points daily.
Implemented in my project:
Cloud Monitoring Stack
Deployed a full observability stack using Docker Compose, integrating Prometheus pull-based scraping, Grafana dash representation, and Alertmanager routing alert webhooks to Telegram channels.
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Design S3-like Object Storage
Creating a scalable, highly durable, and cost-effective distributed file storage system for unstructured data.
Core Architecture Concepts
- Separation of Metadata (SQLite/PostgreSQL) and Blobs (Data node storage)
- REST API interface (GET, PUT, DELETE bucket/object operations)
- IAM Policy engine checking bucket/object access permissions
- Data durability via replication or erasure coding across failure domains
Trade-offs & Challenges
Strong consistency for metadata vs eventual consistency for object replication. Handling large files via multipart uploads to avoid memory overflow on API nodes.
Implemented in my project:
Cloud Storage & IAM Simulator
Simulated AWS S3 IAM structure locally using MinIO object storage. Wrote Python script validation using boto3 API to test access permissions for Admin, Developer, and ReadOnly roles.
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Design a Chat System
Supporting real-time, low-latency communication with message persistence and presence tracking.
Core Architecture Concepts
- WebSockets for bi-directional, persistent real-time communication
- Stateful connection managers to handle active user socket connections
- Message synchronization across devices using sequence numbers
- Read receipts and active presence heartbeat mechanisms
Trade-offs & Challenges
WebSockets are stateful, requiring sticky sessions or pub/sub message brokers (like Redis) to route messages to users connected to different chat servers. Scaling for group chats requires different fan-out patterns.
Implemented in my project:
AI IT Support Assistant
Integrated Telegram API for real-time ticket query submission and AI response retrieval. Managed session persistence locally in SQLite database and used RAG vector querying to resolve user prompts dynamically.
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