I've used Java/C/C++/Ada/Perl/Go and most recently Python all professionally in one aspect or another. I settled on Python. So being a professional Python/Dja

I've used Java/C/C++/Ada/Perl/Go and most recently Python all professionally in one aspect or another. I settled on Python. So being a professional Python/Django coder, I was aware of all these issues. And yet, those issues do not seem to stop the Python train from moving forward. A couple of issues to note in his article: Everything he says is true, but the conclusions are mostly false. 1. Optimizing databases and data access are the number one scalability issue. It's the hardest thing going from a monolith to a microservice architecture. Goroutines, threads, etc. don't solve that for you. 2. Threads are terrible in any language (except Erlang maybe), and reliable code cannot be used with primitive thread constructs. Goroutines are good enough, sure. Also python asyncio. But not threads. I've seen production systems that no one could debug, because 3000 threads ran amok, thread deadlocks, race conditions, etc. And you can't unit test threaded code effectively either. 3. All software has multiple build systems. C/C++ and autotools, CMake, Scons, Waf. Java and Ant or Maven or Gradle or whatever. Go is sane for the most part, until you get to dependency management -- goglide, govendor, etc. 4. Strongly typed, statically typed systems (Java, C++) usually aren't. Usually people rely upon that as a crutch to think they don't have to worry about types, until they see NullPointerExceptions (java) or segfault (C/C++) in production. 5. Python code is only as reliable as the person who wrote it. But that's true of C/Java/C++ etc. People have to understand where the pitfalls of a language are, and that's usually documented in coding standards or style guides.