Docker for Mac and Docker Toolbox. If you need to use VMs running older versions of Docker Engine, you can use a tool like Docker Version Manager to.
You're right: Docker for Mac and Docker for Windows both run Linux containers in a Linux VM. Virtual machines are supposed to have near native performance.
However, if the host machine does not have enough memory to serve the memory requirements of the VM as well as that of the underlying OS (Mac or Windows), then there's going to be performance penalties because of things like swap thrashing and memory balooning. There could be a further slowdown if your host has a slow spinning disk instead of an SSD. So: Assigning more memory to the Linux VM will help only if there is enough memory in the host. The probably is not even usually CPU, memory, or network - it is almost always entirely down to the disk performance. Even then, it's not the disks of the VMs themselves, it's mounting folders from the host onto a VM - because it's not a native filesystem, solutions like NFS exist, different Hypervisors have their own filesystems. Docker for Mac uses a custom one called osxfs to share the host filesystem with the VM it runs. In other words, if you mount anything into your containers from your host machine, you are very likely to see worse performance.
If you don't mount anything from the host machine, you are likely to see near-native performance, as long as you haven't run out of other resources (CPU, memory, network). You can read more about osxfs here: Edit: To add to this, you may have realised from what I've just been saying - if you didn't use any host-mounted folders ever, you could actually sync the code into your VM. I've done this before using unison and you can achieve near-native performance then on macOS.
Since I did this I believe a tool has been released to handle this automatically for you, but I can't remember what it's called. I've been using Linux now for about a year and have been loving native Docker without messing around.
While still slower than running natively on Linux, there are some mitigations for performance problems for shared folders on MacOS:. If the app in your container creates cache files (like compiled code), define this cache directory as a separate volume and don't export it to your host. This will speed up access of the app to the cache folder. Try different volume caching strategies (default is to always synchronize, which is slow.
You might not need that strict guarantees):. Sync code between host and container using instead of shared volumes. You can speed up file sharing by using NFS instead of the native MacOS, like in Never used the latter two myself, although I heard they work well enough for a dev environment. The first two were enough for the MacOS user on my dev team to make the experience less painful. Using Linux is definitely the better option for docker. I think it depends on a lot of things. Not all set ups with Docker for Windows are very slow.
For example, I moved from running Docker on Linux to Docker for Windows on my dev box and while I did notice a slow down in volume mount performance, it didn't get unusably slow but there's room for improvement. I am using an i5 3.2GHz with an SSD (about 3 years old). The amount of indirection going on with my Windows box is high, yet I'm happy with the performance. Docker for Windows runs the Docker daemon. Windows Subsystem for Linux routes its own Docker client to that Docker for Windows daemon.
All of my source code is mounted from an external HD (not SSD) into WSL. That WSL mounted source code is also mounted back into Docker for Windows. With all of that going on, web applications with hundreds files reload faster than I can move my mouse to click refresh in a browser. Even rails applications process changes and serve requests in 100ms or less in development. The only exception is when dealing with assets. With webpack I load in 1.4mb of Javascript through babel and without any caching it takes around 500ms for it to compile a change.
Likewise 250kb of SCSS going through a lot of loaders takes 1.8 seconds without caching or optimizing anything. If anyone is curious, I wrote exact steps on how I have everything set up here:. As others have said, when you use mounted volumes from host, things are gonna slow down quite alot. And it seems that atleast for Docker for Mac every update pose another issues with speed.
For example couple of weeks ago one of our devs struggled when every docker compose up took 10-15 minutes (normally 20-30 seconds). Wasted half day trying to optimize dockerfiles/docker-compose.yml and found out that when you set env var NOPROXY=. before running docker/docker-compose the speed was restored to almost normal (atleast for mac).
I still dont know/care why this magical env var change helped. It has become better over the years, atleast I dont need to create separate dockerfiles or docker-compose.yml files to please mac devs anymore:).
I know that Docker for Windows is a new product and is still in its infancy.Docker for Windows no local Linux kernel Docker for Mac is a bit older.but still same problems as above. Docker for Linux uses the native host’s kernel, and then changes out the user space level OS. For example if I run Debian, in my Docker container I can specify CentOS user space and that is what will be present in my container + my own systems native kernel. General synopsis, You shouldn’t be running more than a few Docker instances locally for testing, they should be small, if you’re a Dev Stop putting so many dependencies in your yaml. If you’re spinning up many docker instances locally you’re either going to hurt your workstations fans (think about the heat from all that RAM that now is loaded+heat) or you’re going to put extra stress on your laptop battery/kill SSD if swap is enabled. Take it up to an AWS instance if possible, have a Dev VM server in prem or otherwise, try digitalocean/etc.
Last modification: unknown Introduction The suggested tool to support the autohoring of developed in is, a software to produce, browse and verify based on pre-processors like and rendered through. Kosmtik is a module needing a list of prerequisite software like PostgreSQL, PostGIS, Python, osm2pgsql and Node.js itself. Kosmtik also includes node versions of further software like Mapnik and Carto and at the moment it supports. To simplify the related installation process, openstreetmap-carto comes with files and, which allow to build the image through simple commands. Allows packaging applications and dependencies in that can run on a host server without altering it permanently. The software components running within containers are easy to setup and tear down individually. This helps enable flexibility and portability.
The Docker demon can use operating-system-level virtualization or a virtual machine. The Docker configuration included in openstreetmap-carto automates the setup of the Kosmtik development environment and simplifies the OSM data import process. The openstreetmap-carto repository needs to be a directory that is shared between your host system and the Docker virtual machine.
Home directories are shared by default; if your repository is in another place, you need to add this to the Docker sharing list. Sufficient disk space of several gigabytes is generally needed.
Docker creates an image for its virtual system that holds the virtualised operating system and the containers. The format (Docker.raw, Docker.qcow2,.vhdx, etc.) depends on the host system. To provide a rough idea of the sizing, the physical size might start with 2-3 GB for the virtual OS and could grow to 6-7 GB when filled with the containers needed for the database, Kosmtik, and a small OSM region. Further 1-2 GB would be needed for shape files in the openstreetmap-carto/data repository. The subsequently described step-by-step procedure allows installing and running a Docker image of Kosmtik with Ubuntu, with Windows and with macOS. The Windows configuration exploiting Docker and Doker Toolbox is definitively a great tool to allow developing openstreetmap-carto with a 64 bit Windows PC and locally testing the style through Kosmtik on the same machine. With Docker Toolbox, Kosmtik is transparently run in a VirtualBox VM, with all development data (e.g., openstreetmap-carto directory) physically residing on the Windows host system and the PostGIS database (with imported OSM data) hosted within the VM.
The next paragraph describes the. The subsequent ones detail the steps to. Ubuntu installation For a standard Kosmtik installation without using Docker, check. To go on installing Docker, first update the system. Docker-compose stop db Check also. MacOS installation With macOS, Docker provides and for Mac. Docker for Mac is a native desktop application which requires OSX Yosemite 10.10.3 or above and new hardware models supporting MMU virtualization (i.e., Extended Page Tables (EPT) and Unrestricted Mode).
Docker Toolbox allows the installation of Docker on older Macs that do not meet minimal system requirements for Docker for Mac. Check the Docker installation pages for detailed installation requirements and procedures. The setup procedure of Kosmtik with is similar to the installation of Kosmtik, while the setup of Kosmtik with is similar to the one. The steps to add the openstreetmap-carto directory to the Docker sharing list are: Docker Preferences File Sharing; Windows: Docker Settings Shared Drives.
Importing the data needs a substantial amount of RAM in the virtual machine. If you find the import process (Reading in file: data.osm.pbf, Processing) being killed by the Docker demon, exiting with error code 137, increase the Memory assigned to Docker (e.g.
Docker Preferences Advanced Adjust the computing resources). Docker copies log files from the virtual machine into the host system, their. The ‘console-ring’ appears to be a ringbuffer of the console log, which can help to find reasons for killings. While installing software in the containers and populating the database, the disk image of the virtual machine grows in size, by Docker allocating more clusters. When the disk on the host system is full (only a few MB remaining), Docker can appear stuck. Watch the system log files of your host system for failed allocations. Docker stores its disk image by default in the home directories of the user.
If you don’t have enough space here, you can move it elsewhere. Docker Preferences Disk). Windows installation Windows 10 64-bit allows installing Kosmtik and openstreetmap-carto via native Docker or Docker Toolbox.
With Windows, at the moment can only be installed on 64-bit physical machines with hardware-assisted virtualization support enabled and where the operating system provides (e.g., 64-bit Microsoft Windows 10 Professional/Enterprise/Education but not Windows 10 Home 64-bit, Windows 7 64-bit, etc.; anyway, Windows 10 Home can be upgraded to Win 10 Pro and this operation is relatively cheap). For 64-bit Windows operating systems not natively supporting Docker, can be installed, which uses Oracle Virtual Box instead of Hyper-V. Neither Docker nor Docker Toolbox can be installed on a 32-bit architecture. Nested virtualization scenarios are not generally supported. Oracle Virtual Box would need a bare metal hw and should not be run inside a VM to support a 64 bit OS. Kosmtik running through Docker Toolbox on a Windows 7 (or Windows 10 Home) takes about 2.8 GB in C: Users.docker. It is advisable to use an i5 machine with 8 GB RAM at least.
Windows with Native Docker This procedure allows installing and running a Docker image of Kosmtik with x64 Windows versions able to run native Docker. Before starting, it is important to read the documentation in.
Install Docker for Windows (enabling also the virtualization in the PC BIOS setting). Download openstreetmap-carto (at to a local subdirectory of the user’s home directory (C: users username). Download a PBF of OSM data to the same directory where openstreetmap-carto has been downloaded, as mentioned in. The downloaded file shall be named data.osm.pbf (example, download and rename it as data.osm.pbf). For further information on the downloading of appropriate.osm or.pbf file, check “”. Open a CMD prompt to this directory. Run docker-compose: docker-compose up The procedure takes many minutes to complete.
Wait for kosmtik:1 Core Loading map. Kosmtik can be run via browser pointing to. Windows with Docker Toolbox The procedure here described allows installing and running a Docker image of Kosmtik with x64 Windows versions requiring Docker Toolbox. Before starting, it is important to read the documentation in Install Docker Toolbox:. Enable the virtualization in the PC BIOS setting. Install the latest version of (this is advisable even if Docker Toolbox includes a recent version of this software). Install; select also the installation of “Git MSYS-git UNIX tools”.
Run Docker Quickstart Terminal ( All Programs, Docker, Docker Quickstart Terminal) and wait for the MINGW64 Console to start. Notice that “Waiting for an IP” takes the time needed to start a virtual machine named default and boot a Linux image included in a file named boot2docker.iso (automatically downloaded and configured by the software). The VM startup can take minutes.
Within the login message before the UNIX prompt, the MINGW64 Console shall display the VM IP address (e.g., docker is configured to use the default mackine with IP 192.168.99.100). A missing IP address means that the VM was not correctly created. An error like pywintypes.error: (2, 'WaitNamedPipe'. Means that the Docker Quickstart Terminal prompt has been started before the completion of the boot of the VM and without getting the IP address. Download openstreetmap-carto to a local subdirectory of the user’s home directory (C: users username): cd git clone cd openstreetmap-carto Download a PBF of OSM data to the same directory where openstreetmap-carto has been downloaded, as mentioned in. The downloaded file shall be named data.osm.pbf. Eval $(docker-machine env default) To totally remove the docker installation, delete the virtual machine named default ( docker-machine rm default) and the directory C: Users.docker.
While docker-compose up is running, the openstreetmap-carto development can be directly done on the PC by accessing the local directory where openstreetmap-carto has been downloaded. E.g., locally editing a stylesheet and then pressing the Kosmtik Reload button on the browser, the map gets updated.
The RAM size available to the default VM should be increased for improved performance. To increase the VM memory size. Docker-machine stop default Change the memory of the default virtual machine though Oracle VM VirtualBox (and possibly also the number of cores). Also, modify the.env file as described at the section of the documentation. Then restart the project: close and restart Docker Quickstart Terminal (e.g., All Programs, Docker, Docker Quickstart Terminal); finally issue: cd openstreetmap-carto docker-compose up kosmtik Recommendations and troubleshooting To stop Kosmtik, select the window with docker-compose running and press Control C. To start again Kosmtik without importing the OSM data. Kosmtik1 sh: 0: Can't open scripts/docker-startup.sh.
It is suggested to position the openstreetmap-carto directory under the user’s home directory (C: users username). Alternatively, the drive where the project is located (i.e., where the Dockerfile and volume are located) shall be shared though Oracle VM VirtualBox. Runtime errors such as file not found, can’t open scripts or cannot start service may indicate. If, after restarting the PC or after hibernating and resuming a PC, at docker-compose up, you get. Cd openstreetmap-carto docker-compose up Additional recommendations for Docker Toolbox.
Use direct internet access during the installation (without setting a proxy). Docker Toolbox needs to configure a Linux 64-bit VM.
![Install Install](/uploads/1/2/5/4/125401791/528941539.png)
Set all virtualization features in the BIOS before running the Docker installation. Do not manually start the interactive session of the VM VirtualBox used by Docker Toolbox (and named “default”) before running Docker Quickstart Terminal, but let this command start the VM; in case, close any Docker Quickstart Terminal, perform a shutdown -h now on the interactive session and wait for the VM to disappear. Then run Docker Quickstart Terminal.
Notice that an error like pywintypes.error: (2, 'WaitNamedPipe'. Occurs when the Docker Quickstart Terminal is activated after a manual startup of the interactive session of the VM. docker-compose up does not install or copy the openstreetmap-carto package itself on the VM and accesses the one manually downloaded to the PC. Importing the data needs a substantial amount of RAM in the virtual machine. If you find the import process (Reading in file: data.osm.pbf, Processing) being killed by the Docker demon, exiting with error code 137, increase the Memory assigned to Docker (e.g. Docker Settings Advanced Adjust the computing resources).