Rancher has a load balancer built it (HAProxy). Let's compare its performance vs Docker Swarm one. I will use 3 identical nodes:192GB RAM28-cores i5 Xeon1GBit LANCentOS 7Docker 1.12Rancher 1.1.2I will benchmark against a hello world HTTP server written in Scala with Akka-HTTP and Spray JSON serialization (I don't think it matters though), sources are on GitHub. I will use Apache AB benchmark tool.As a baseline, I exposed the web server port outside the container and run the following command:ab -n 100000 -[...]

Hopac uses a bounded pool of worker threads, number of which is equal to number of CPU cores (by default). A dangerous thing about this design is that a situation is possible where all the threads are busy doing some CPU intensive work and no other Hopac jobs can proceed. A good solution for this is running such a CPU bound computations on the standard .NET thread pool, freeing Hopac pool for more intelligent work. I found a nice code in one of the older Hopac GitHub discussions which schedules a ordinary [...]

Don Syme has been working on struct tuples for F# language. Let's see if they are more performant than "old" (heap allocated) tuples in simple scenario: returning tuple from function. The code is very simple: Decompiled code in Release configuration: Everything we need to change to switch to struct tuples, is adding "struct" keyword in front of constructor and pattern matching: Decompiled code in Release configuration: I don't know about you, but I was surprised with those results. The performance roughly[...]

Let's compare performance of hashmap implementation in Rust, .NET, D (LDC) and Go.Rust: F#: As you can see, Rust is slower at about 17% on insersions and at about 21% on lookups. UpdateAs @GolDDranks suggested on Twitter, since Rust 1.7 it's possible to use custom hashers in HashMap. Let's try it: Yes, it's significantly faster: additions is only 5% slower than .NET implementation, and lookups are 32% *faster*! Great. Update: D addedLDC x64 on windows It's very slow at insertions and quite fast on loo[...]

Akka.NET Streams is a port of its Scala/Java counterpart and intended to execute complex data processing graphs, optionally in parallel and even distributed. It has quite different semantics compared to Hopac's one and it's wrong to compare them feature-by-feature, but it's still interesting to benchmark them in a scenario which both of them supports well: read lines of a file asynchronously, filter them by a regex in controlled degree of parallelism, then normalize the lines with a simple string manipulat[...]