LunarCrush LLM | LunarCrush AI Interface

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@Kaperskyguru "I'm officially launching a new directory. It's a Developer-Focused Tools directory. You can discover compare and integrate the best AI tools built specifically for developers. Let me know how this will be helpful to you. Currently at: Report bugs"
X Link @Kaperskyguru 2025-10-13T10:09Z 35.6K followers, 1645 engagements

"Before worrying about Kafka or Redis ask: - What data flows through the system - What are the critical paths - What happens if this part fails This thinking scales better than any framework"
X Link @Kaperskyguru 2025-10-14T09:58Z 35.6K followers, XX engagements

"The real goal of system design Its not to impress with fancy terms like CQRS or Event Sourcing. Its to build reliable scalable systems that solve business problems. Every decision should connect back to a user or business need"
X Link @Kaperskyguru 2025-10-14T09:58Z 35.6K followers, XX engagements

"Most backend engineers focus on either projects or DSA. But the ones who get hired fast They master both and know how to connect them. 🧵"
X Link @Kaperskyguru 2025-10-14T14:00Z 35.6K followers, 2767 engagements

"Thats why profiling matters more than guessing. Use tools like: - EXPLAIN ANALYZE for SQL queries - APMs like New Relic or Datadog - Built-in profilers (Nodes inspect Pythons cProfile Gos pprof) Dont optimize blindly. Measure then tune"
X Link @Kaperskyguru 2025-10-14T16:02Z 35.6K followers, XXX engagements

"If you like Tweets like this you will absolutely enjoy my exclusive weekly newsletter Sharing exclusive backend engineering resources to help you become a great Backend Engineer. Join 11000+ subscribers here:"
X Link @Kaperskyguru 2025-10-14T14:10Z 35.6K followers, XXX engagements

"For example: If your API feels slow most engineers jump straight into optimizing code. But often the culprit isnt code its I/O. A single SELECT * or missing index can waste more time than XXX lines of inefficient logic"
X Link @Kaperskyguru 2025-10-14T16:02Z 35.6K followers, XX engagements

"Youre in a backend interview. They ask: How would you design a real-time chat system like Slack or WhatsApp Heres how to approach it:"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 67.1K engagements

"Data storage: - Primary store: NoSQL (Cassandra DynamoDB) for fast writes. - Search index: ElasticSearch for message queries. - Cache: Redis for active conversations and user sessions"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 4277 engagements

"Scaling strategy: - Partition users by chat room or region. - Use consistent hashing for message routing. - Replicate WebSocket gateways across regions. - Store connection states in Redis or an in-memory grid"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 3694 engagements

"Message flow: - User sends a message through WebSocket. - Chat service validates and publishes to a queue (e.g. Kafka). - Consumers persist messages in DB and push to recipients. - Notifications trigger for offline users"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 4892 engagements

"How to say it in the interview: Id design a real-time chat system with WebSockets for communication Kafka for decoupling Redis for session caching and a NoSQL DB for persistence all orchestrated for horizontal scalability and fault tolerance"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 2634 engagements

"Additional features: - Typing indicators via lightweight WebSocket events. - Message edits/deletes handled with event versioning. - End-to-end encryption for privacy. - Push notifications for offline clients"
X Link @Kaperskyguru 2025-10-14T08:03Z 35.6K followers, 2943 engagements

"Youre in a backend interview. They ask: How would you design a chat backend that supports real-time messaging presence and scalability (like Slack) Heres a practical approach"
X Link @Kaperskyguru 2025-10-06T11:57Z 35.6K followers, 2017 engagements