B) They weren't allocating a lot, and Go was enforcing a GC sweep every 2 minutes, and it was spending a lot of time on their LRU cache. To "reduce allocations" they had to cut their cache down, which negatively impacted latency.
The problem to get down to the core of these issues are test cases. It seems, that neither the Go developers nor many other people have run into this as an issue - I only remember noticing the regular GC some years ago, but it was not an issue for me. As they have a real-life test case exposing this problem, they are possibly the only ones, who could verify a potential fix for the problem.
So, while it is great that they identified the problem and wrote a thorough blog piece about it, the only thing we learn from this is, that in Go 1.9 there was a latency issue every 2 minutes with their style of application/heap usage. Unfortunately, we don't know whether this problem was already addressed in later Go versions, and if not, whether there should be a way to control the automatic gc intervals to address this.
> These latency spikes definitely smelled like garbage collection performance impact, but we had written the Go code very efficiently and had very few allocations. We were not creating a lot of garbage.
The problem was due to the GC scanning all of their allocated memory and taking a long time to do so, regardless of it all being necessary and valid memory usage.
In many languages with GC you can actually do manual memory management relatively easily with few helper functions. You write your own allocate() and free() functions/methods. When you allocate, you check the free list first, if nothing is available, you do normal allocation. When you call free you add the object into a free list. If you memory management leaks, it triggers GC.
Usually you need to do that kind of stuff to only in few places and few data structures to cut GC 90%.