cd ~/Patrick @SystemNodes

@MrCharlesky Interested please

𝟯𝟬 𝗕𝗹𝗼𝗴𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝟯𝟬 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀: 1. APIs: lnkd.in/dsbwPZ6N 2. API Gateways: lnkd.in/gtyXmvf4 3. JWTs: lnkd.in/ghtXYRqU 4. Webhooks: lnkd.in/geHxGX-7 5. REST vs GraphQL: lnkd.in/gM5VHKQS 6. Load Balancing: lnkd.in/gvxfwEUr 7. Proxy vs Reverse Proxy: lnkd.in/gMTtidBq 8. Scalability: lnkd.in/gPGhW-qK 9. Availability: lnkd.in/gQk2p4_6 10. SPOF: lnkd.in/gw_uHZWn 11. CAP Theorem: lnkd.in/g_tFqJJb 12. SQL vs NoSQL: lnkd.in/gHyC9qWc 13. ACID Transactions: lnkd.in/dB3QHiMz 14. Database Indexes: lnkd.in/g_-bQWtA 15. Database Sharding: lnkd.in/g9mc-d5m 16. Consistent Hashing: lnkd.in/gR9wFDpz 17. CDC: lnkd.in/gWhGwh9Z 18. Caching: lnkd.in/gBSeTstS 19. Caching Strategies: lnkd.in/dVk7nZ_Y 20. Cache Eviction Policies: lnkd.in/gQAEXEmq 21. CDN: lnkd.in/gaW4Vkpy 22. Rate Limiting Algorithms: lnkd.in/gYDxg8XY 23. Message Queues: lnkd.in/g-jnNGDC 24. Bloom Filters: lnkd.in/gfGjCrSZ 25. Idempotency: lnkd.in/gDB3AJij 26. Concurrency vs Parallelism: lnkd.in/gGZXhjBD 27. Long Polling vs WebSockets: lnkd.in/d9xKD28K 28. Stateful vs. Stateless Architecture: lnkd.in/gz_ccK-Y 29. Batch vs Stream Processing: lnkd.in/gKtj_qWh 30. Geohashing: lnkd.in/gjSbKdpN 🔁 Repost to help a friend. 📌 Save this post for later.

How to Build Your Own Small AI Model From Scratch (Beginner-Friendly Guide)

System Design Series - Day 8/30 API Gateway Patterns – The Front Door of Your Microservices API Gateway is the single entry point for all your clients. Without it: - Mobile/web clients call 10+ different services directly - Authentication is duplicated everywhere - Rate limiting, CORS, logging → repeated in every service - Services are fully exposed to the internet With it: - One clean URL for clients - Centralized auth, rate limiting, routing, aggregation - Backend services stay hidden and secure Here’s everything you need to know about API Gateway patterns. What is an API Gateway? Think of it as the hotel front desk Without a front desk: - Guests wander around looking for rooms - No security check - Housekeeping and room service have no coordination With a front desk: - Single check-in point - Routes guests to correct room - Handles security, coordination, and requests API Gateway does exactly that for your microservices. The Problem It Solves Before API Gateway: Mobile app needs user profile + orders: → Calls User Service directly → Calls Order Service directly → Calls Payment Service directly Problems: - Client knows internal service URLs - Multiple network calls (slow on mobile) - Auth tokens sent to every service - No centralized rate limiting or logging - Services exposed to the internet After API Gateway: Mobile app calls one URL: https://api.example. com/profile Gateway handles everything internally: - Authenticates once - Routes and aggregates calls - Returns combined response Benefits: - 1 network call from client - Services completely hidden (security win) - Centralized cross-cutting concerns - Much better client experience Core Responsibilities: 1. Routing Maps external URLs to internal services GET /api/users → User Service GET /api/orders → Order Service 2. Authentication & Authorization Validates JWT/OAuth once at the gateway. Services trust the gateway. 3. Rate Limiting Prevents abuse (e.g., 100 requests/min per user). 4. Request Aggregation Combines multiple backend calls into one response for the client. 5. Protocol Translation Client uses REST → Service uses gRPC (handled at gateway). Advanced Patterns - Circuit Breaker → Prevents cascading failures when a service is down - Request/Response Transformation → Convert old → new API formats - Caching → Cache frequent responses at the gateway level - Logging & Monitoring → Centralized observability When to Use API Gateway Use it when: - You have multiple microservices - External clients (mobile, web, third-party) - You need centralized auth, rate limiting, or aggregation Don’t use it when: - Simple monolith (overkill) - Only internal service-to-service communication - Ultra-low latency is critical (extra hop) Popular Solutions - Kong (open-source, powerful plugins) - AWS API Gateway (managed, serverless) - NGINX + Lua (DIY, lightweight) - Traefik, Envoy, KrakenD Summary API Gateway is not just a proxy. It is the security layer, traffic manager, and aggregator for your entire backend. It simplifies client code, hides internal complexity, and centralizes cross-cutting concerns. Trade-offs: - Extra network hop (adds latency) - Becomes a critical component (make it highly available) Used correctly, it’s one of the most valuable pieces in any microservices architecture. Tomorrow (Day 9): Inter-Service Communication Patterns Questions about API Gateway? Drop them below 👇 #SystemDesign #APIGateway #Microservices #Backend

Stop learning AI ……at least for now. Instead, spend the summer learning networking with me. It’s going to be intense….I’m going a little crazy. We are opening up our CCNA course on NetworkChuck Academy to EVERYONE…..for FREE. May - August. - Videos - Ebooks - Livestreams and frequent study sessions with me and @CioaraJeremy . AI isn’t going anywhere. Take a break and learn something that doesn’t change every 5 seconds……a skill that will make you dangerous with or without AI. I believe this is something that will change your life. That’s why we’re making it free. That’s why we’re doing this with you. Join for free here: ntck-ac.co/ccnasummerearl… #SummerOfCCNA #fightAI #AIresistance

📂 Backend Engineering Stack (2026 Edition) ┃ ┣ 📂 Languages ┃ ┣ 📂 JavaScript (Node.js) ┃ ┣ 📂 Python ┃ ┣ 📂 Go ┃ ┣ 📂 Java ┃ ┗ 📂 Rust ┃ ┣ 📂 Frameworks ┃ ┣ 📂 Express.js ┃ ┣ 📂 NestJS ┃ ┣ 📂 Django ┃ ┣ 📂 FastAPI ┃ ┗ 📂 Spring Boot ┃ ┣ 📂 APIs ┃ ┣ 📂 REST ┃ ┣ 📂 GraphQL ┃ ┣ 📂 gRPC ┃ ┣ 📂 WebSockets ┃ ┗ 📂 tRPC ┃ ┣ 📂 Databases ┃ ┣ 📂 PostgreSQL ┃ ┣ 📂 MySQL ┃ ┣ 📂 MongoDB ┃ ┣ 📂 Redis ┃ ┗ 📂 Cassandra ┃ ┣ 📂 ORMs / Query Builders ┃ ┣ 📂 Prisma ┃ ┣ 📂 Drizzle ORM ┃ ┣ 📂 Sequelize ┃ ┣ 📂 TypeORM ┃ ┗ 📂 Mongoose ┃ ┣ 📂 Authentication ┃ ┣ 📂 JWT ┃ ┣ 📂 OAuth ┃ ┣ 📂 Firebase Auth ┃ ┣ 📂 Auth0 ┃ ┗ 📂 Clerk ┃ ┣ 📂 Caching & Queues ┃ ┣ 📂 Redis ┃ ┣ 📂 Kafka ┃ ┣ 📂 RabbitMQ ┃ ┣ 📂 BullMQ ┃ ┗ 📂 SQS ┃ ┣ 📂 DevOps & Deployment ┃ ┣ 📂 Docker ┃ ┣ 📂 Kubernetes ┃ ┣ 📂 GitHub Actions ┃ ┣ 📂 AWS ┃ ┗ 📂 DigitalOcean ┃ ┣ 📂 Monitoring & Logging ┃ ┣ 📂 Prometheus ┃ ┣ 📂 Grafana ┃ ┣ 📂 ELK Stack ┃ ┣ 📂 Datadog ┃ ┗ 📂 Sentry ┃ ┣ 📂 Architecture Patterns ┃ ┣ 📂 Monolith ┃ ┣ 📂 Microservices ┃ ┣ 📂 Event-Driven ┃ ┣ 📂 Serverless ┃ ┗ 📂 Clean Architecture ┃ ┣ 📂 Security ┃ ┣ 📂 Rate Limiting ┃ ┣ 📂 API Gateway ┃ ┣ 📂 Encryption ┃ ┣ 📂 Zero Trust ┃ ┗ 📂 Secrets Management ┃ ┣ 📂 Testing ┃ ┣ 📂 Unit Testing ┃ ┣ 📂 Integration Testing ┃ ┣ 📂 E2E Testing ┃ ┣ 📂 Jest ┃ ┗ 📂 Cypress ┃ ┗ 📂 Future Trends ┣ 📂 AI-powered Backends ┣ 📂 Edge Computing ┣ 📂 Serverless-first Apps ┣ 📂 Real-time Systems ┗ 📂 Backend-as-a-Service

📂 AI Stack (2026 Edition) ┃ ┣ 📂 AI Models ┃ ┣ 📂 OpenAI ┃ ┣ 📂 Anthropic ┃ ┣ 📂 Google DeepMind ┃ ┣ 📂 Meta AI ┃ ┗ 📂 Mistral AI ┃ ┣ 📂 LLM APIs ┃ ┣ 📂 GPT-4o ┃ ┣ 📂 Claude 3 ┃ ┣ 📂 Gemini 1.5 ┃ ┣ 📂 LLaMA 3 ┃ ┗ 📂 Mixtral ┃ ┣ 📂 AI Agents ┃ ┣ 📂 LangChain ┃ ┣ 📂 LlamaIndex ┃ ┣ 📂 AutoGen ┃ ┣ 📂 CrewAI ┃ ┗ 📂 Haystack ┃ ┣ 📂 Vector Databases ┃ ┣ 📂 Pinecone ┃ ┣ 📂 Weaviate ┃ ┣ 📂 Qdrant ┃ ┣ 📂 Milvus ┃ ┗ 📂 Chroma ┃ ┣ 📂 RAG (Retrieval-Augmented Generation) ┃ ┣ 📂 LangChain RAG ┃ ┣ 📂 LlamaIndex RAG ┃ ┣ 📂 Haystack RAG ┃ ┣ 📂 Vectara ┃ ┗ 📂 Elastic RAG ┃ ┣ 📂 AI Deployment ┃ ┣ 📂 Replicate ┃ ┣ 📂 Modal ┃ ┣ 📂 RunPod ┃ ┣ 📂 Hugging Face ┃ ┗ 📂 AWS SageMaker ┃ ┣ 📂 Fine-Tuning ┃ ┣ 📂 LoRA ┃ ┣ 📂 QLoRA ┃ ┣ 📂 PEFT ┃ ┣ 📂 OpenAI Fine-tuning ┃ ┗ 📂 Axolotl ┃ ┣ 📂 AI Observability ┃ ┣ 📂 LangSmith ┃ ┣ 📂 Helicone ┃ ┣ 📂 PromptLayer ┃ ┣ 📂 Weights & Biases ┃ ┗ 📂 Arize AI ┃ ┣ 📂 AI UI / Frontend ┃ ┣ 📂 Vercel AI SDK ┃ ┣ 📂 Streamlit ┃ ┣ 📂 Gradio ┃ ┣ 📂 React ┃ ┗ 📂 Next.js ┃ ┣ 📂 Multimodal AI ┃ ┣ 📂 DALL·E ┃ ┣ 📂 Stable Diffusion ┃ ┣ 📂 Whisper ┃ ┣ 📂 ElevenLabs ┃ ┗ 📂 Sora ┃ ┣ 📂 Automation / Workflows ┃ ┣ 📂 Zapier ┃ ┣ 📂 Make ┃ ┣ 📂 n8n ┃ ┣ 📂 Pabbly ┃ ┗ 📂 Temporal ┃ ┣ 📂 AI Security ┃ ┣ 📂 Guardrails AI ┃ ┣ 📂 Rebuff ┃ ┣ 📂 Lakera AI ┃ ┣ 📂 Microsoft Presidio ┃ ┗ 📂 Cloudflare ┃ ┣ 📂 AI Use Cases ┃ ┣ 📂 Chatbots ┃ ┣ 📂 AI Agents ┃ ┣ 📂 Code Generation ┃ ┣ 📂 Content Creation ┃ ┣ 📂 Video Generation ┃ ┗ 📂 Voice Assistants ┃ ┗ 📂 Future Trends ┣ 📂 Autonomous Agents ┣ 📂 AI Operating Systems ┣ 📂 Real-time AI ┣ 📂 Personal AI Assistants ┗ 📂 AI-native SaaS

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This 2-hour Stanford lecture breaks down how models like ChatGPT and Claude are actually built, clearer than what many people in top AI roles ever get exposed to. Save this and set aside two hours today. It might end up being the most valuable thing you learn all week.

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How can you generate random numbers? You can count on @JosePaumard to break it down.

In a market where there are so many AI tools, I will always recommend Kombai for any frontend engineering work. Every AI tool treats codebases as if they were the same. Next.js? Vue? Svelte? Doesn't matter to them. Kombai is different. You can literally customize the agent to suit WHATEVER workflow you are using in your project: - Framework of choice - Router setup - State management - CSS architecture And way more Then it writes code that actually fits your project. No more "let me refactor this to match our patterns." It just works with your stack from the start:

SSRF & Rate Limiting Bypass: How APIs Get Abused

Backend Engineers, This Is How Hackers See Your System @ExploitforgeLTD

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Three frontend libraries every developer needs to know about.