developer @fullstack88

Design patterns I expect senior backend devs to actually use in production: 1) Adapter: wrap vendor SDKs so you can swap Stripe/S3/Kafka without touching business code 2) Strategy: pick algorithms at runtime (rate limiting: token bucket vs fixed window) 3) State machine: model order/payment lifecycle, stop if/else soup, make retries safe 4) Circuit breaker + bulkhead: contain downstream failures, cap concurrency per dependency 5) Outbox + idempotency key: publish events without double sends, survive retries and deploys 6) Saga: multi-service workflows with compensations, not 2PC 7) CQRS (lightweight): separate write model from read projections when reads are messy 8) Decorator/middleware: auth, logging, tracing, metrics without copy-paste

Based on 50+ BigTech LLD interviews experience, sharing Leetcode problem sheet that prepares you for the low level design round involving classes, interfaces, and constraints. 1. LRU Cache LLD concepts: Cache interface, eviction policy, O(1) design 2. Design Parking System LLD concepts: Object modeling, enums, capacity handling 3. Design Browser History LLD concepts: State management, undo/redo 4. Design HashMap LLD concepts: Buckets, collisions, APIs 5. Design Circular Queue LLD concepts: Fixed capacity systems, buffer design 6. Design Hit Counter LLD concepts: Time-based aggregation, APIs 7. Design Underground System LLD concepts: Data modeling, aggregation, clear responsibilities 8. Design Authentication Manager LLD concepts: Token lifecycle, expiry, encapsulation 9. Logger Rate Limiter LLD concepts: Throttling logic, extensible design 10. Design File System LLD concepts: Tree structures, recursion, API design 11. Design Leaderboard LLD concepts: Encapsulation, efficient updates 12. Design Tic-Tac-Toe LLD concepts: Game state, validation, extensibility Some of these are premium problems that you can search on internet.

pulkit mittal @pulkit_mittal_

2 days ago

This is all I had to learn to clear every design round i applied to including FAANGs. If you can spend 3-4 focussed hours with each system i've mentioned, you can win the world! Here’s a beginner-friendly list to start with: HLD: - URL Shortener - Pastebin - Rate Limiter - Key

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How short URLs are generated • Redirect flow • Redis caching • Database design • Load balancing • Scalability considerations

Suhani @tiwarisuhani_11

4 days ago

Today's System Design Concept Authentication, Authorization, Authentication Types & Proxies Authentication vs Authorization Basic Authentication Token Based Authentication (JWT) OAuth (Login with Google/GitHub) Forward Proxy Reverse Proxy

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so you have big goals but you’re lazymaxxing and procrastinating af? i follow a simple framework that keeps me moving even when there are no visible results yet. here’s how it works: i break every goal down into very small tasks that can be finished in 45-60 minutes max. then I work in two modes: planner mode: this is where i think. i question things, analyze trade-offs, and decide what’s worth doing. execution mode: once i start executing, there is no more debating. no overthinking. no renegotiating with myself. even if a task feels pointless in that moment, i have to do it. for example, if i create a task that i’ll go to the gym at 6am tomorrow, the decision is already made. morning-me doesn’t get a vote. there are a few other parts to this system as well. i’m planing to build an app around it to automate the whole process for myself. would this be useful for others too?

90% of Kubernetes interviews in 2026 come down to these 7 points: 1. Pods vs Deployments: what gets restarted, what gets rolled out, and why ReplicaSets exist 2. Services and DNS: ClusterIP vs headless, endpoint selection, and common port mistakes 3. Ingress and L7 routing: path rules, TLS termination, and where 404s actually come from 4. Requests/limits: scheduling vs throttling vs OOMKilled, and why limits can reduce throughput 5. Probes: startup vs readiness vs liveness, and how bad probes cause restart loops 6. Storage basics: PVC/PV/SC, access modes (RWO/RWX), and what happens on node drain 7. Debugging flow: kubectl get/describe/logs, events, exec, and how to reason from symptoms to root cause

One of the most important Backend & System Design interview questions: What is the N+1 Query Problem?

Suhani @tiwarisuhani_11

2 days ago

Details of about database sharding

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3. Java (and Spring Boot) youtube.com/playlist?list=…

5. Express.js youtube.com/watch?v=nH9E25…

7. SQL youtube.com/playlist?list=…

Amazon-style design: order events + inventory updates. What I look for in interviews: 1) Components: Order API (sync), Inventory svc, Payment svc, Event bus (Kafka/SNS+SQS), consumers for reservation, shipping, analytics, DLQ, outbox relayer 2) Data model: orders(id, user, status, version), order_items(order_id, sku, qty), inventory(sku, on_hand, reserved), inventory_ledger(id, sku, delta, reason, order_id), events(event_id, type, order_id, ts) 3) APIs: POST /orders, POST /orders/{id}/cancel, POST /inventory/reserve, POST /inventory/release, POST /inventory/adjust; events: OrderCreated, PaymentAuthorized, InventoryReserved, OrderCancelled, Shipped 4) Bottlenecks: hot SKUs and cart spikes; fix with partition by sku, per-sku locks/atomic updates, batching, cache only for reads, avoid global transactions 5) Scaling tradeoffs: strong vs eventual on stock; reservation TTL; idempotency keys; at-least-once + dedupe; sagas over 2PC 6) Failure cases: duplicate/out-of-order events, consume

This is all I had to learn to clear every design round i applied to including FAANGs. If you can spend 3-4 focussed hours with each system i've mentioned, you can win the world! Here’s a beginner-friendly list to start with: HLD: - URL Shortener - Pastebin - Rate Limiter - Key Value Database - Type Ahead / autocomplete Search LLD: - Builder, Factory, Singleton Pattern - Strategy and Observer Pattern - Tic tac toe game - Movie Booking System - inventory system Here's glimpse to my notes. Happy learning!

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pulkit mittal @pulkit_mittal_

4 days ago

for HFT interviews, i had to prepare for computer science round even for a senior role. and all companies ask these questions from freshers. here's the list of most commonly asked computer science questions. Operating Systems (OS) 1. Process vs thread 2. Virtual memory, paging,

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As a Backend Engineer, make sure you have a strong understanding of: • SOLID Principles • Multithreading & Concurrency • Immutability Concepts • Streaming & Message Queues • Caching Strategies • Security Fundamentals (SSL, JWT, OAuth) • Design Patterns (Factory, Decorator, Singleton, Observer) • Test-Driven Development (TDD) These aren't just interview topics—they’re fundamentals that help you build scalable, maintainable, and production-ready systems. 🚀

If you are SERIOUS about SYSTEM DESIGN, WATCH ALL THESE VIDEOS:

These 20 patterns cover what actually shows up in MAANG interviews: → Sliding Window — fixed-size or dynamic window problems on arrays/strings → Islands (Matrix Traversal) — grid traversal, connected components, flood fill → Two Pointers — iterate smarter on sorted arrays and pair problems → Fast & Slow Pointers — cycle detection, middle of linked list → Merge Intervals — overlapping intervals and scheduling problems → Cyclic Sort — missing/duplicate numbers in fixed ranges → In-place Reversal of LinkedList — reverse linked structures efficiently → Breadth First Search (BFS) — level-order tree and graph traversal → Depth First Search (DFS) — recursive traversal and path exploration → Two Heaps — median, stream processing, balancing datasets → Subsets — combinations, permutations, backtracking problems → Modified Binary Search — rotated arrays and sorted search variations → Bitwise XOR — unique number and bit manipulation problems → Top K Elements — heap-based frequency and ranking problems → K-way Merge — merging multiple sorted lists/arrays → Topological Sort — dependency resolution and ordering problems → 0/1 Knapsack — dynamic programming optimization problems → Fibonacci Numbers — DP recurrence and state transition problems → Palindromic Subsequence — palindrome-based dynamic programming → Longest Common Substring — string comparison and sequence matching problems

Not getting interviews in 2026? 😔 95% of the time it’s your resume. Here’s a 0-bullshit thread that actually fixes it and gets you calls. Attaching my LinkedIn inbox screenshot for proof! Save this thread 🧵👇

If you're serious about becoming a Senior Backend Engineer in 2026, master this progression: Level 1: Postman / Bruno Test APIs properly before your users become your QA team. Contracts matter from day one. Level 2: Redis Speed is easy. Cache invalidation is the real challenge. Learn to weigh trade-offs over cleverness. Level 3: PostgreSQL Data modeling, indexing, transactions the foundation of real backend thinking. Schema design is system design. Level 4: Kafka Async systems are powerful, but retries, ordering, and idempotency separate juniors from seniors. Failure is a feature you design for. Level 5: Docker "Works on my machine" should have ended in your junior years. Consistency beats convenience every time. Level 6: OpenTelemetry Trace requests across services and distributed systems finally make sense end-to-end. Observability isn't optional it's essential. Level 7: Grafana Dashboards that show latency, errors, and throughput not just pretty graphs. If you can't measure it, you can't improve it. Level 8: Prometheus Metrics that force you to think in SLOs and system health, not just features. Reliability outpaces feature velocity in the long run. Level 9: k6 Load test your "scalable" backend. Watch it break. Then fix it. Scale is a verb, not an adjective. Level 10: Terraform Senior engineers don't just write code. They own the infrastructure it runs on. Infrastructure is code. Ownership is culture. The pattern: • Foundation: Postman/Bruno, PostgreSQL, Redis • Resilience: Kafka, Docker, k6 • Observability: OpenTelemetry, Grafana, Prometheus • Ownership: Terraform Master one layer before rushing the next. (save it)

Today's Concepts : > Normalization > Denormalization > Indexing

Suhani @tiwarisuhani_11

6 days ago

Today's Concepts: > Why NoSQL came into picture > Key-Value Databases (Redis) > Document Databases (MongoDB) > Columnar Databases > Graph Databases > Real-world applications > Polyglot Persistence with E-Commerce example

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build these 3 projects and you'll think like an engineer.

Day 13/100 of Learning System Design. Consistent Hashing – How It Powers Scalable Caches and DBs. Grab the System Design Ebook: codewithdhanian.gumroad.com/l/urcjee

Dhanian 🗯️ @e_opore

a week ago

Day 12/100 of Learning System Design. PACELC Theorem – Beyond CAP for Modern Systems. Grab the System Design Ebook: codewithdhanian.gumroad.com/l/urcjee

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Backend Engineering Interview Questions: 1. What is backend engineering, and what are the responsibilities of a backend engineer? 2. Explain the difference between monolithic, microservices, and serverless architectures. 3. How do you design scalable backend systems? 4. What are the key principles of distributed systems? 5. What is horizontal scaling vs vertical scaling? 6. What is load balancing, and how does it improve system reliability? 7. What is the CAP theorem, and why is it important? 8. Explain strong consistency vs eventual consistency. 9. What is database sharding, and when would you use it? 10. What is database replication, and how does it work? 11. What is caching, and what caching strategies have you used? 12. What is the difference between Redis and Memcached? 13. What is a message queue, and why is it used? 14. Explain the difference between Apache Kafka and RabbitMQ. 15. What is event-driven architecture? 16. What are REST APIs, and how do they differ from GraphQL? 17. What is API versioning, and how do you implement it? 18. What is rate limiting, and why is it important? 19. What is authentication vs authorization? 20. Explain JWT-based authentication. 21. How do you secure backend APIs? 22. What are common backend security vulnerabilities, and how do you prevent them? 23. What is a database index, and how does it improve performance? 24. How do you optimize slow database queries? 25. What monitoring and logging tools have you used? 26. What is observability, and why is it important? 27. How do you troubleshoot production incidents? 28. What is fault tolerance, and how do you design for failures? 29. How would you design a URL shortener system? 30. How would you design a large-scale chat application? Grab the Backend Engineering Ebook: codewithdhanian.gumroad.com/l/ungqng