Princeton Afeez

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Princeton Afeez

Princeton Afeez

@PrincetonAfeez

#30Days30Apps #100DaysOfCode #365DaysOfCode #BlackTechTwitter #SystemArchitect #SystemDesign

LosAngeles, CA Katılım Kasım 2020
171 Takip Edilen38 Takipçiler
Princeton Afeez
Princeton Afeez@PrincetonAfeez·
I'm going to update all my links for the first 5 apps on github
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Akshay Shinde
Akshay Shinde@ConsciousRide·
As a backend engineer. Please learn: - One server-side language deeply (Node.js/TypeScript, Python, Java, Go - pick one and master it) - API design & development (REST, GraphQL, gRPC, OpenAPI/Swagger, versioning, rate limiting) - Databases (SQL - PostgreSQL/MySQL with indexing, transactions, normalization + NoSQL like MongoDB/Redis) - Caching strategies (Redis, in-memory, CDN integration) - Authentication & authorization (JWT, OAuth2, sessions, RBAC, secure password handling) - System design fundamentals (scalability, microservices vs monolith, load balancing, sharding) - Event-driven architecture & messaging (Kafka, RabbitMQ, queues, pub/sub patterns) - DevOps & infrastructure (Docker, CI/CD with GitHub Actions, basic Kubernetes, observability - logging/monitoring/Prometheus) - Cloud platforms (AWS/GCP/Azure - compute, storage, serverless basics) - Security best practices (input validation, SQL injection prevention, HTTPS, rate limiting, secrets management) - Performance optimization & testing (query optimization, concurrency, unit/integration/load testing) Pick one language & its ecosystem deeply.
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Akshay Shinde
Akshay Shinde@ConsciousRide·
25 debugging techniques that save hours: 1. Reproduce the issue reliably. 2. Read error messages fully. 3. Check recent changes first. 4. Use logs before guessing. 5. Add temporary logs strategically. 6. Binary search the problem area. 7. Isolate components step by step. 8. Validate assumptions. 9. Check edge cases. 10. Inspect network requests. 11. Use breakpoints effectively. 12. Compare working vs broken states. 13. Roll back to last known good state. 14. Test with minimal data. 15. Check environment differences. 16. Read documentation again. 17. Search exact error text. 18. Monitor memory and CPU usage. 19. Check async flows carefully. 20. Validate input data. 21. Trace execution path. 22. Remove complexity temporarily. 23. Pair debug with someone. 24. Take a short break and return fresh. 25. Write down findings as you go.
Akshay Shinde@ConsciousRide

25 system design concepts every engineer should understand: 1. Scalability: handling growth without breaking. 2. Load balancing: distributing traffic across servers. 3. Caching: reducing repeated work. 4. Consistency models: strong vs eventual tradeoffs. 5. CAP theorem: consistency, availability, partition tolerance. 6. Sharding: splitting data across machines. 7. Replication: copying data for reliability. 8. Indexing: faster data retrieval. 9. Rate limiting: controlling traffic spikes. 10. Queues: async task handling. 11. Idempotency: safe retries. 12. Circuit breaker: stopping cascading failures. 13. API gateway: centralized request handling. 14. CDN: serving content closer to users. 15. Event-driven systems: async communication. 16. Database normalization: structured data design. 17. Denormalization: performance tradeoffs. 18. Observability: logs, metrics, traces. 19. Fault tolerance: surviving failures. 20. Horizontal scaling: adding more machines. 21. Vertical scaling: increasing machine power. 22. Backpressure: controlling overload. 23. Data partitioning: splitting datasets logically. 24. Service discovery: locating services dynamically. 25. Consistent hashing: stable distribution of data.

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Akshay Shinde
Akshay Shinde@ConsciousRide·
25 system design concepts every engineer should understand: 1. Scalability: handling growth without breaking. 2. Load balancing: distributing traffic across servers. 3. Caching: reducing repeated work. 4. Consistency models: strong vs eventual tradeoffs. 5. CAP theorem: consistency, availability, partition tolerance. 6. Sharding: splitting data across machines. 7. Replication: copying data for reliability. 8. Indexing: faster data retrieval. 9. Rate limiting: controlling traffic spikes. 10. Queues: async task handling. 11. Idempotency: safe retries. 12. Circuit breaker: stopping cascading failures. 13. API gateway: centralized request handling. 14. CDN: serving content closer to users. 15. Event-driven systems: async communication. 16. Database normalization: structured data design. 17. Denormalization: performance tradeoffs. 18. Observability: logs, metrics, traces. 19. Fault tolerance: surviving failures. 20. Horizontal scaling: adding more machines. 21. Vertical scaling: increasing machine power. 22. Backpressure: controlling overload. 23. Data partitioning: splitting datasets logically. 24. Service discovery: locating services dynamically. 25. Consistent hashing: stable distribution of data.
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Jaydeep
Jaydeep@_jaydeepkarale·
Master concepts, not tools 🔹 Git is a tool, version control is a concept. 🔹 Docker is a tool, containerization is a concept. 🔹 Kubernetes is a tool, container orchestration is a concept. 🔹 SQL is a language, relational data modeling is a concept. 🔹 React is a library, component-based UI is a concept. 🔹 TensorFlow is a library, machine learning is a concept. 🔹 Kafka is a tool, event streaming is a concept. 🔹 REST is an architecture, client-server communication is a concept. 🔹 ChatGPT is a product, large language models are a concept. 🔹 LangChain is a framework, LLM orchestration is a concept. 🔹 Pinecone is a tool, vector search is a concept. 🔹 Claude Code is an agent, agentic coding is a concept. 🔹 Prompt engineering is a skill, human-AI communication is a concept. 🔹 RAG is a pattern, grounding model outputs in external knowledge is a concept. 🔹 MCP is a protocol, tool use and context injection is a concept.
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Princeton Afeez
Princeton Afeez@PrincetonAfeez·
I've decided to restart my GitHub profile. All the links I've posted will therefore fail.
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Theo - t3.gg
Theo - t3.gg@theo·
Claude Code is kind of like if Codex was drunk. Fun, friendly, bit more creative, makes really dumb mistakes, probably shouldn't be trusted with prod.
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Can Vardar
Can Vardar@icanvardar·
if you’re still religiously using claude code and convinced it’s superior, just install codex and use it for a week
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