I tried some solutions but non of them worked for my docker container that contains a big Java monolith. Some of them use nfs, Docker in Docker, Unison 2 way sync or rsync. This is typical of performance engineering, which requires significant effort to analyze slowdowns and develop optimized components. This requires tuning each component in the data path in turn - some of which require significant engineering effort.Įven if we achieve a huge latency reduction of 100sroundtrip, we will still only see a doubling of performance. To reduce the latency, we need to shorten the data path from a Linux system call to OS X and back again. With osxfs, latency is presently around 200s for most operations or 20x slower. With a classical block-based file system, this latency is typically under 10s (microseconds). Latency is the time it takes for a file system system call to complete.įor instance, the time between a thread issuing write in a container and resuming with the number of bytes written. With large sequential IO operations, osxfs can achieve throughput of around 250 MBs which, while not native speed, will not be the bottleneck for most applications which perform acceptably on HDDs. In a traditional file system on a modern SSD, applications can generally expect throughput of a few GBs. This means that, depending on your workload, you may experience exceptional, adequate, or poor performance with osxfs, the file system server in Docker for Mac.įile system APIs are very wide (20-40 message types) with many intricate semantics involving on-disk state, in-memory cache state, and concurrent access by multiple processes.Īdditionally, osxfs integrates a mapping between OS Xs FSEvents API and Linuxs inotify API which is implemented inside of the file system itself complicating matters further (cache behavior in particular).Īt the highest level, there are two dimensions to file system performance: throughput (readwrite IO) and latency (roundtrip time). There is a lot of hate so better listen to the members instead of reading all the frustrations.

Usually you would work on your source code and expect no slowdowns for building.

When you develop a big dockerized application then you are in a bad spot.

Docker Very Slow Windows 10 1000000 Records.

Docker on mac very slow