Deep-dive system design guides written for engineers who want to go beyond surface-level answers. Every guide is built from first principles — algorithms, trade-offs, failure modes, and production-ready patterns.
Design a standalone rate limiting service handling 500M requests/day across 50+ microservices. Token bucket, Redis Cluster, Lua atomicity, circuit breakers, and full observability.
Caching at 1M reads/sec. Cache-aside vs write-through, Redis vs Memcached, consistent hashing, stampede prevention (PER, mutex, stale-while-revalidate), and eviction policies.
Push, email, SMS, in-app at 100B/month. Kafka-backed priority pipeline, at-least-once delivery with dedup, user preferences, DND, frequency capping, retry with backoff, DLQ, and circuit breakers per provider.
Hashing strategies, redirect architecture, analytics pipeline, and how to handle 1B+ short URLs with low latency reads.
Kafka internals: partitions, consumer groups, offsets, and delivery semantics. When to use Kafka vs SQS vs RabbitMQ.
Build your own Redis/DynamoDB. LSM trees, SSTables, bloom filters, compaction strategies, and replication.
Preventing split-second overselling across 5,000 dark stores at 500k mutations/sec. Redis Lua atomics, Redlock for bundles, soft-hold reservation lifecycle, sub-millisecond cache invalidation, event sourcing, CRDT counters, and flash sale virtual queues.
End-to-end flash sale system: pre-registration, virtual queues, dynamic pricing, fraud prevention, and post-sale reconciliation.
Transformer architecture, multi-head attention, tokenization, pre-training pipeline, RLHF, LoRA fine-tuning, inference decoding strategies, KV cache, RAG, and serving at scale with vLLM.
HNSW and IVF-PQ deep dive, embedding pipelines, filtered search trade-offs, hybrid sparse+dense retrieval, production RAG architecture, and designing a 1B-vector system. Pinecone vs Qdrant vs pgvector comparison.
Online vs offline stores, point-in-time correctness, feature pipelines, and preventing training-serving skew.
NPCI architecture, VPA resolution, P2P / Collect / QR flows. Internals of Google Pay, PhonePe and Paytm. MPIN HSM security, deemed transactions, auto-reversal, and 10B+ txn/month scalability.
Design a Razorpay/Stripe-like gateway. Checkout flows, card tokenisation, 3D Secure, PCI DSS, webhooks, and reconciliation.
ML-based fraud scoring, feature engineering on transaction streams, Kafka real-time pipelines, and rule engines.
Every guide starts with the questions a senior engineer asks before touching a whiteboard. Scope before you solve.
No hand-waving. Every choice — algorithm, database, pattern — is justified with explicit pros, cons, and alternatives.
What breaks? How? What's the recovery strategy? Production systems live in the failure paths, not the happy path.
API contracts, SDK patterns, Prometheus metrics, alert rules. Not just architecture — the full operational picture.
I'm a seasoned software architect with 19 years of experience building systems that scale — currently at Tesco Technology, Bengaluru. Over nearly 15 years at Tesco, I've led multiple technology transformation journeys, balancing engineering principles with stakeholder realities and delivery timelines.
My work sits at the intersection of distributed systems, ML/AI, and product engineering. I hold a master's degree in Machine Learning & AI and actively apply those foundations to real-world backend architecture. I'm a published author on DZone — writing about LLMs, product management for AI, and software design patterns.
I run #MindMapMondaysByManas — a series of hand-crafted visual mind maps on software concepts, security, spring, system design, and more. This repo is the long-form companion to that series: deep-dive guides written the way I wish I'd found them when I was learning.