I retired (after 18+ years at Google) last August, and as of that date A LOT of production code used languages different from C++ -- Go, Java, Kotlin, AND Python, plus a few more (Rust, Dart, and many others). In my successful, long career at Google I did use C++ (I had "readability" in C++), but rarely: only when "ridiculous scalability" was needed.
For example, collecting Stackoverflow posts about GCP products, and distributing the needed subsets of them among vendors and employees in tech support to potentially answer, comment, edit, vote on, re-tag, &c, used to be all Python (and the "scale" was a few hundred or thousands of posts and people at a time -- ridiculously small "by Google `production` standards", and perfectly adequate for the much-higher-programmer-productivity Python has always afforded... I know, because I did the vast majority of that coding, including maintenance, ongoing monitoring of performance, and VERY occasional optimizations if and when monitoring showed them to be desirable).
That was the core of my job for my last several years at Google -- I won't even list the many other NON-prototyping tasks I did in previous years (decades, almost), the vast majority of them in Python. And -- the majority of my performance reviews during those 18+ years were rated "exceeds expectations", so it seems that world-class Python skill (which clearly was crucial to me getting a hiring offer back in 2004, though, alas, visa issues delayed my start to early 2005) were extremely useful for at least some of us Google engineers.
Thanks! Unfortunately, there's a link to Cloud Tasks API on that page that 404s and there's not much else info on it. As far as I can tell, it's alpha. Maybe I can find the Google Next presentation on it.
Incidentally, the best way to "let us know" about bugs in GCP (App Engine or whatever else) is via the Issue Trackers, as per https://cloud.google.com/support/docs/issue-trackers (disclaimer: making this and similar processes work is my current job at Google).
If I had to guess, I'd say the most relevant changes for App Engine use may be the optimizations documented at https://docs.python.org/3/whatsnew/3.7.html#whatsnew37-perf : the `sort` method of lists about 50% faster in common cases, the `copy` method of dicts up to 5 times faster, etc.
Actually, when we started (GAE) with Python, my friend Guido didn't YET work here -- I was finally able to convince him to join, shortly after GAE's launch, in part thanks to the prospect of working on GAE's Python (which is what he ended up doing here, especially developing ndb, but also many other little things). Python was at the heart of Google for long before that (read Levy's "In the 'plex"...!-) -- or I wouldn't have joined Google 11 years ago, BTW.
As for Java, well -- guess who announced Java to the world at Moscone Center in SF 21 years ago...? One Eric Schmidt, then Sun's VP for SW products (he reminisced about that this morning at his Next keynote)... who just happened to be Google's CEO when Java was announced as GAE's 2nd language!
For example, collecting Stackoverflow posts about GCP products, and distributing the needed subsets of them among vendors and employees in tech support to potentially answer, comment, edit, vote on, re-tag, &c, used to be all Python (and the "scale" was a few hundred or thousands of posts and people at a time -- ridiculously small "by Google `production` standards", and perfectly adequate for the much-higher-programmer-productivity Python has always afforded... I know, because I did the vast majority of that coding, including maintenance, ongoing monitoring of performance, and VERY occasional optimizations if and when monitoring showed them to be desirable).
That was the core of my job for my last several years at Google -- I won't even list the many other NON-prototyping tasks I did in previous years (decades, almost), the vast majority of them in Python. And -- the majority of my performance reviews during those 18+ years were rated "exceeds expectations", so it seems that world-class Python skill (which clearly was crucial to me getting a hiring offer back in 2004, though, alas, visa issues delayed my start to early 2005) were extremely useful for at least some of us Google engineers.
Alex