Videos

#WebAssembly #Javascript

Most teams chase tiny throughput differences and ignore what actually impacts production. - Throughput delta: small - Container delta: massive - Memory delta: meaningful at scale Rust wins developer velocity and safety. C++ wins runtime efficiency and footprint. Pick based on your constraints. #ru

Rust and C++ are almost tied on throughput (~40K req/s), but not on operational cost. - Rust image: 114MB - C++ image: 18.6MB (84% smaller) - Rust memory: 4.3MB RSS - C++ memory: 2.5MB RSS (42% less) Verdict: choose constraints, not benchmark hype. Full benchmark + methodology in long video. #rust

Are you subsidizing Python's Global Interpreter Lock with your cloud bill? Python optimizes for the developer. Go optimizes for the machine. Stop writing core infrastructure in a scripting language. Pick Python for the algorithm. Pick Go for the backend. Drop your stack below 👇

I benchmarked Rust (Axum) and C++ (Drogon) for cloud REST APIs with PostgreSQL JSONB workloads. Performance is nearly identical (3-5% difference), but operational costs differ wildly. 𝗞𝗲𝘆 𝗳𝗶𝗻𝗱𝗶𝗻𝗴𝘀: - Throughput: 38-42K req/s (Rust) vs 39-40K req/s (C++) — statistically equivalent - Conta

Most teams chase tiny throughput differences and ignore the real production costs. - Throughput delta: small - Container delta: massive - Memory delta: meaningful at scale Rust wins developer velocity and safety. C++ wins runtime efficiency and footprint. Pick based on your constraints. #rust #cpp

Most apps do not need a heavy Single-page application(SPA). HTMX + Go cuts bundle weight, removes hydration debt, and ships as a single binary. This video breaks down the real tradeoffs, shows the server-side pattern, and explains when SPAs still win.

Read throughput results on identical endpoints against the same PostgreSQL database: - 𝗚𝗼 𝗙𝗶𝗯𝗲𝗿: 29,068 requests/sec - 𝗥𝘂𝘀𝘁 𝗔𝘅𝘂𝗺: 11,024 requests/sec Go is 2.5x faster on reads. But this isn't Go the language beating Rust the language. Fiber uses 𝗳𝗮𝘀𝘁𝗵𝘁𝘁𝗽 — not Go's standard

956ms on a single row lookup. That's not a slow query — that's the CLR garbage collector stopping your thread mid-request. We ran the same users microservice in Rust (Axum), Go (Fiber), and ASP.NET (Minimal API) against identical endpoints and the same PostgreSQL database. Under 200 concurrent user

When junior devs discover Netflix tech blogs... 😱 That feeling when you see 12 microservices for 10 users. Resume Driven Development at its finest. Real pros: Build the monolith until it breaks. Don't distribute complexity until you HAVE complexity. 🚫 Microservices for Todo apps ✅ Monolith-firs

Cold build times on the same users microservice (5 endpoints, PostgreSQL, async background job): - 𝗥𝘂𝘀𝘁 (𝗔𝘅𝘂𝗺): 45,887ms — 45 seconds - 𝗚𝗼 (𝗙𝗶𝗯𝗲𝗿): 303ms - 𝗔𝗦𝗣.𝗡𝗘𝗧 (.𝗡𝗘𝗧 𝟭𝟬): 835ms That's 151x slower than Go. Not percent. Times. Every PR in CI. Every fresh container buil

BFF was designed for 2015 when API gateways couldn't shape payloads. In 2026, gateways handle this natively — BFF adds unnecessary operational overhead. ## Key Points - Gateways now handle payload shaping natively - 3 clients = 3 BFFs = 3 on-call rotations - BFF creates code duplication and sync ni