Videos

One chart is not enough for a production stack decision. This benchmark keeps the workload fixed and compares the same REST API in Go, Rust, and Node.js. In this video: - what each runtime wins - where tail latency changes the decision - how to pick based on your real bottleneck Github: https://git

We put Rust, Go, Java, and C# into the same log processing ring. Using the same dataset and strict benchmark rules, we tested their ability to parse production-style logs, aggregate metrics, and export JSON reports. ​Key Results: ​Winner: Rust (920,000 lines per second) ​Cold Start: Rust leads at 1

One chart is not enough for a production stack decision. Bun vs Deno vs Node: The 2026 Runtime Performance Deathmatch Is Finally Over In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Comment with your stack and

One chart is not enough for a production stack decision. Markov Chain Showdown: Full Code + Structure + Data Visualization In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Comment with your stack and workload; I

One chart is not enough for a production stack decision. Bun vs Deno vs Node: The 2026 Runtime Performance Deathmatch Is Finally Over In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Comment with your stack and w

Rust, Go, and .NET are run through the same microservice benchmark harness: same Postgres limits, same load matrix, and the same artifact pipeline. Github : https://github.com/prod-garbage-destroyer/rust-go-dotnet-microservice-2026/tree/v2-artifacts-implementations This video is an interim verdict

We rebuilt both stacks from the protocol up, then ran repeatable captures across cold and steady passes to answer one question with evidence: when does Node.js WebSocket win, and when does Rust gRPC take over? This video walks through the full request path (proto contract, server internals, benchma

Everyone says "rewrite to a lighter stack." But in enterprise systems, rewrite risk, integration breakage, and ops instability can cost more than any benchmark gain. In this video, we break down why Quarkus + Spring Boot still dominate modern backend delivery: Loom concurrency, native startup perfo

AI code feels like speed—until the architecture fractures. This short breaks down the synthetic debt trap: why LLM-generated refactors add unnecessary abstraction, how phantom dependencies inflate complexity, and why “correct” code can still be bad code. We cover the innovation vs maintenance gap an

Legacy codebases are hemorrhaging talent as maintainability collapses under the weight of unpatched dependencies and deprecated logic. We must confront the reality that staying on aging frameworks is a strategic failure. Here's why you need to migrate now. #programming #softwareengineering #archit

In this video, we break down exactly when a centralized control plane collapses under load, the exact cost curve of coordination vs. debugging, and how to use Choreography as a pressure relief valve at scale. 🔍 𝗪𝗵𝗮𝘁 𝘄𝗲 𝗰𝗼𝘃𝗲𝗿: - Control Plane Under Load (Kubernetes, Nginx, API Gateway) -

I benchmarked the same cloud API implementation in Zig, Rust, and C++ with identical routes, schema, workload, and environment. In this video we compare: - Throughput under c=100, c=250, c=500 - Tail latency (p99) behavior under load - Operational footprint (image size + memory) - Real source files