Videos

One chart is not enough for a production stack decision. Does Rust Save More Than Rust Devs Cost? In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bottleneck Watch the full breakdown on the channel for benchmark method, tr

Same microservice. Same database. Same read endpoint. Three very different throughput curves. Verified read throughput: - Go: 28,945 to 29,068 to 28,916 RPS - Rust: 11,364 to 11,024 to 11,349 RPS - ASP.NET: 24,474 to 14,055 to 14,159 RPS Go stayed flat across c=50, c=200, and c=500. Rust stayed st

We built the same HTTP API in four runtimes and measured final container image size with Podman on Apple M4. - Rust (scratch): 3.5 MB - Go (scratch): 5.65 MB - Python (Alpine): 53.4 MB - Node.js (Alpine): 163 MB Rust is 47x smaller than Node. Every pull, every deploy, every cold start in your clus

Node.js just ate 465 MB for the same API that Rust runs in 18 💀 same server, same endpoint, same machine. multiply by 100 instances and tell me memory doesn't matter.

AI agents are great at local correctness: generate code, pass the happy path, open the PR. But that does not prove system behavior. Retries, redirects, session state, cache invalidation, and fallback paths still have to be validated by humans. If QA is the first team discovering the design bug, y

Flutter teams asked the right follow-up: if Rust wins over pure Dart through dart:ffi, does Zig close the gap enough to change the pick? This video reruns the benchmark with the same shared Dart bridge, the same checksum gate, and a wider scenario sweep: - boundary-heavy - balanced - compute-heavy

Vector search won the overall quality chart in this benchmark. That does not mean you should delete grep from your stack. This short benchmarks 4 retrieval lanes across 255 documents, 112 labeled queries, and 7 developer-search scenarios: - `grep` for exact string search - `BM25` for lexical ranki

Manual sharding really did win the local throughput chart. That still was not the real verdict. This short compresses the important part of the benchmark: - manual Postgres shards were fastest locally - the first TiDB loss included a harness SQL dialect bug - after the rerun, the honest claim beca

One chart is not enough for a production stack decision. Sharding Is A Last Resort Github : https://github.com/prod-garbage-destroyer/sharding-is-a-last-resort-benchmark In this video: - what each runtime/language wins - where tail latency changes the decision - how to pick based on your real bot

Rust can make Flutter-adjacent compute much faster, but the native boundary is not free. This benchmark compares a pure Dart data-processing lane against a direct `dart:ffi` Rust lane using the same seeded `Uint32List` workload, the same checksum path, two dataset sizes, and repeated measurement ro

Java Streams vs Rust iterators under the compiler Pretty syntax is not the same thing as cheap runtime behavior. This short compares a clean Java Stream pipeline with a clean Rust iterator chain, then looks at what survives after lowering: Java bytecode with stream stages and boxing, and Rust code

One chart is not enough for a production stack decision. Rust Won. Then Lost. Then .NET Won. In this video: what each runtime/language wins where tail latency changes the decision how to pick based on your real bottleneck Watch the full breakdown on the channel for benchmark method, tradeoffs, an