Failed Port Is Already Allocated Issue 1114 Docker For Mac Github

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Failed Port Is Already Allocated Issue 1114 Docker For Mac Github Windows

Alright, so an open source program I'm building and working on is really complicated and unnecessarily messy to build, to the point that you need end-of-life versions of python and visual studio to build current (2021 scheduled) releases, with a mixture of build tools, and ends up with an appimage if you build on some systems, and an installer on others, even though I can only manage to build. Tested on the following versions, but this issue is not limited to: docker-compose version 1.15.0; Docker engine 17.06-ce; Steps to Reproduce. Using docker-compose or docker run, create a service that binds a large port range: docker run -rm -d -p 0 nginx. Popular labels from issues and pull requests on open source GitHub repositories - Pulled from - labels.md. The project's Python Interpreter is set to use Docker Compose. If I point it at a docker-compose service that binds no ports, I cannot connect to the Django server from my web browser. If I add a `ports` section to that docker-compose service, the first thing I start grabs that port, and when I attempt to run other things they fail with ```.

Device Mapper is a kernel-based framework that underpins many advancedvolume management technologies on Linux. Docker’s devicemapper storage driverleverages the thin provisioning and snapshotting capabilities of this frameworkfor image and container management. This article refers to the Device Mapperstorage driver as devicemapper, and the kernel framework as Device Mapper.

For the systems where it is supported, devicemapper support is included inthe Linux kernel. However, specific configuration is required to use it withDocker.

The devicemapper driver uses block devices dedicated to Docker and operates atthe block level, rather than the file level. These devices can be extended byadding physical storage to your Docker host, and they perform better than usinga filesystem at the operating system (OS) level.

Prerequisites

devicemapper is supported on Docker Engine - Community running on CentOS, Fedora,Ubuntu, or Debian.
devicemapper requires the lvm2 and device-mapper-persistent-data packagesto be installed.
Changing the storage driver makes any containers you have alreadycreated inaccessible on the local system. Use docker save to save containers,and push existing images to Docker Hub or a private repository, so you donot need to recreate them later.

Configure Docker with the `devicemapper` storage driver

Before following these procedures, you must first meet all theprerequisites.

Configure `loop-lvm` mode for testing

This configuration is only appropriate for testing. The loop-lvm mode makesuse of a ‘loopback’ mechanism that allows files on the local disk to beread from and written to as if they were an actual physical disk or blockdevice.However, the addition of the loopback mechanism, and interaction with the OSfilesystem layer, means that IO operations can be slow and resource-intensive.Use of loopback devices can also introduce race conditions.However, setting up loop-lvm mode can help identify basic issues (such asmissing user space packages, kernel drivers, etc.) ahead of attempting the morecomplex set up required to enable direct-lvm mode. loop-lvm mode shouldtherefore only be used to perform rudimentary testing prior to configuringdirect-lvm.

For production systems, seeConfigure direct-lvm mode for production.

Stop Docker.
Edit /etc/docker/daemon.json. If it does not yet exist, create it. Assumingthat the file was empty, add the following contents.
See all storage options for each storage driver in thedaemon reference documentation
Docker does not start if the daemon.json file contains badly-formed JSON.
Start Docker.
Verify that the daemon is using the devicemapper storage driver. Use thedocker info command and look for Storage Driver.

This host is running in loop-lvm mode, which is not supported on production systems. This is indicated by the fact that the Data loop file and a Metadata loop file are on files under /var/lib/docker/devicemapper. These are loopback-mounted sparse files. For production systems, see Configure direct-lvm mode for production.

Configure direct-lvm mode for production

Production hosts using the devicemapper storage driver must use direct-lvmmode. This mode uses block devices to create the thin pool. This is faster thanusing loopback devices, uses system resources more efficiently, and blockdevices can grow as needed. However, more setup is required than in loop-lvmmode.

After you have satisfied the prerequisites, follow the stepsbelow to configure Docker to use the devicemapper storage driver indirect-lvm mode.

Warning: Changing the storage driver makes any containers you have already created inaccessible on the local system. Use docker save to save containers, and push existing images to Docker Hub or a private repository, so you do not need to recreate them later.

Allow Docker to configure direct-lvm mode

Docker can manage the block device for you, simplifying configuration of direct-lvmmode. This is appropriate for fresh Docker setups only. You can only use asingle block device. If you need to use multiple block devices,configure direct-lvm mode manually instead.The following new configuration options are available:

Option	Description	Required?	Default	Example
`dm.directlvm_device`	The path to the block device to configure for `direct-lvm`.	Yes	`dm.directlvm_device='/dev/xvdf'`
`dm.thinp_percent`	The percentage of space to use for storage from the passed in block device.	No	95	`dm.thinp_percent=95`
`dm.thinp_metapercent`	The percentage of space to use for metadata storage from the passed-in block device.	No	1	`dm.thinp_metapercent=1`
`dm.thinp_autoextend_threshold`	The threshold for when lvm should automatically extend the thin pool as a percentage of the total storage space.	No	80	`dm.thinp_autoextend_threshold=80`
`dm.thinp_autoextend_percent`	The percentage to increase the thin pool by when an autoextend is triggered.	No	20	`dm.thinp_autoextend_percent=20`
`dm.directlvm_device_force`	Whether to format the block device even if a filesystem already exists on it. If set to `false` and a filesystem is present, an error is logged and the filesystem is left intact.	No	false	`dm.directlvm_device_force=true`

Edit the daemon.json file and set the appropriate options, then restart Dockerfor the changes to take effect. The following daemon.json configuration sets all of theoptions in the table above.

See all storage options for each storage driver in thedaemon reference documentation

Restart Docker for the changes to take effect. Docker invokes the commands toconfigure the block device for you.

Warning: Changing these values after Docker has prepared the block devicefor you is not supported and causes an error.

You still need to perform periodic maintenance tasks.

Configure direct-lvm mode manually

The procedure below creates a logical volume configured as a thin pool touse as backing for the storage pool. It assumes that you have a spare blockdevice at /dev/xvdf with enough free space to complete the task. The deviceidentifier and volume sizes may be different in your environment and youshould substitute your own values throughout the procedure. The procedure alsoassumes that the Docker daemon is in the stopped state.

Identify the block device you want to use. The device is located under/dev/ (such as /dev/xvdf) and needs enough free space to store theimages and container layers for the workloads that host runs.A solid state drive is ideal.
Stop Docker.
Install the following packages:
- RHEL / CentOS: device-mapper-persistent-data, lvm2, and alldependencies
- Ubuntu / Debian: thin-provisioning-tools, lvm2, and alldependencies
Create a physical volume on your block device from step 1, using thepvcreate command. Substitute your device name for /dev/xvdf.
Warning: The next few steps are destructive, so be sure that you havespecified the correct device!
Create a docker volume group on the same device, using the vgcreatecommand.
Create two logical volumes named thinpool and thinpoolmeta using thelvcreate command. The last parameter specifies the amount of free spaceto allow for automatic expanding of the data or metadata if space runs low,as a temporary stop-gap. These are the recommended values.
Convert the volumes to a thin pool and a storage location for metadata forthe thin pool, using the lvconvert command.
Configure autoextension of thin pools via an lvm profile.
Specify thin_pool_autoextend_threshold and thin_pool_autoextend_percentvalues.
thin_pool_autoextend_threshold is the percentage of space used before lvmattempts to autoextend the available space (100 = disabled, not recommended).
thin_pool_autoextend_percent is the amount of space to add to the devicewhen automatically extending (0 = disabled).
The example below adds 20% more capacity when the disk usage reaches80%.
Save the file.
Apply the LVM profile, using the lvchange command.
Ensure monitoring of the logical volume is enabled.
If the output in the Monitor column reports, as above, that the volume isnot monitored, then monitoring needs to be explicitly enabled. Withoutthis step, automatic extension of the logical volume will not occur,regardless of any settings in the applied profile.
Double check that monitoring is now enabled by running thesudo lvs -o+seg_monitor command a second time. The Monitor columnshould now report the logical volume is being monitored.
If you have ever run Docker on this host before, or if /var/lib/docker/exists, move it out of the way so that Docker can use the new LVM pool tostore the contents of image and containers.
If any of the following steps fail and you need to restore, you can remove/var/lib/docker and replace it with /var/lib/docker.bk.
Edit /etc/docker/daemon.json and configure the options needed for thedevicemapper storage driver. If the file was previously empty, it shouldnow contain the following contents:
Start Docker.
systemd:
service:
Verify that Docker is using the new configuration using docker info.
If Docker is configured correctly, the Data file and Metadata file isblank, and the pool name is docker-thinpool.
After you have verified that the configuration is correct, you can remove the/var/lib/docker.bk directory which contains the previous configuration.

Manage devicemapper

Monitor the thin pool

Do not rely on LVM auto-extension alone. The volume groupautomatically extends, but the volume can still fill up. You can monitorfree space on the volume using lvs or lvs -a. Consider using a monitoringtool at the OS level, such as Nagios.

To view the LVM logs, you can use journalctl:

If you run into repeated problems with thin pool, you can set the storage optiondm.min_free_space to a value (representing a percentage) in/etc/docker/daemon.json. For instance, setting it to 10 ensuresthat operations fail with a warning when the free space is at or near 10%.See thestorage driver options in the Engine daemon reference.

Increase capacity on a running device

You can increase the capacity of the pool on a running thin-pool device. This isuseful if the data’s logical volume is full and the volume group is at fullcapacity. The specific procedure depends on whether you are using aloop-lvm thin pool or adirect-lvm thin pool.

Resize a loop-lvm thin pool

The easiest way to resize a loop-lvm thin pool is touse the device_tool utility,but you can use operating system utilitiesinstead.

Use the device_tool utility

A community-contributed script called device_tool.go is available in themoby/mobyGithub repository. You can use this tool to resize a loop-lvm thin pool,avoiding the long process above. This tool is not guaranteed to work, but youshould only be using loop-lvm on non-production systems.

If you do not want to use device_tool, you can resize the thin pool manually instead.

To use the tool, clone the Github repository, change to thecontrib/docker-device-tool, and follow the instructions in the README.mdto compile the tool.
Use the tool. The following example resizes the thin pool to 200GB.

Use operating system utilities

If you do not want to use the device-tool utility,you can resize a loop-lvm thin pool manually using the following procedure.

In loop-lvm mode, a loopback device is used to store the data, and anotherto store the metadata. loop-lvm mode is only supported for testing, becauseit has significant performance and stability drawbacks.

If you are using loop-lvm mode, the output of docker info shows filepaths for Data loop file and Metadata loop file:

Follow these steps to increase the size of the thin pool. In this example, thethin pool is 100 GB, and is increased to 200 GB.

List the sizes of the devices.
Increase the size of the data file to 200 G using the truncate command,which is used to increase or decrease the size of a file. Note thatdecreasing the size is a destructive operation.
Verify the file size changed.
The loopback file has changed on disk but not in memory. List the size ofthe loopback device in memory, in GB. Reload it, then list the size again.After the reload, the size is 200 GB.
Reload the devicemapper thin pool.
a. Get the pool name first. The pool name is the first field, delimited by ` :`. This command extracts it.
b. Dump the device mapper table for the thin pool.
c. Calculate the total sectors of the thin pool using the second field of the output. The number is expressed in 512-k sectors. A 100G file has 209715200 512-k sectors. If you double this number to 200G, you get 419430400 512-k sectors.
d. Reload the thin pool with the new sector number, using the following three dmsetup commands.

Resize a direct-lvm thin pool

To extend a direct-lvm thin pool, you need to first attach a new block deviceto the Docker host, and make note of the name assigned to it by the kernel. Inthis example, the new block device is /dev/xvdg.

Follow this procedure to extend a direct-lvm thin pool, substituting yourblock device and other parameters to suit your situation.

Gather information about your volume group.
Use the pvdisplay command to find the physical block devices currently inuse by your thin pool, and the volume group’s name.
In the following steps, substitute your block device or volume group name asappropriate.
Extend the volume group, using the vgextend command with the VG Namefrom the previous step, and the name of your new block device.
Extend the docker/thinpool logical volume. This command uses 100% of thevolume right away, without auto-extend. To extend the metadata thinpoolinstead, use docker/thinpool_tmeta.
Verify the new thin pool size using the Data Space Available field in theoutput of docker info. If you extended the docker/thinpool_tmeta logicalvolume instead, look for Metadata Space Available.

Activate the `devicemapper` after reboot

If you reboot the host and find that the docker service failed to start,look for the error, “Non existing device”. You need to re-activate thelogical volumes with this command:

How the `devicemapper` storage driver works

Warning: Do not directly manipulate any files or directories within/var/lib/docker/. These files and directories are managed by Docker.

Use the lsblk command to see the devices and their pools, from the operatingsystem’s point of view:

Use the mount command to see the mount-point Docker is using:

When you use devicemapper, Docker stores image and layer contents in thethinpool, and exposes them to containers by mounting them undersubdirectories of /var/lib/docker/devicemapper/.

Image and container layers on-disk

The /var/lib/docker/devicemapper/metadata/ directory contains metadata aboutthe Devicemapper configuration itself and about each image and container layerthat exist. The devicemapper storage driver uses snapshots, and this metadatainclude information about those snapshots. These files are in JSON format.

The /var/lib/docker/devicemapper/mnt/ directory contains a mount point for each imageand container layer that exists. Image layer mount points are empty, but acontainer’s mount point shows the container’s filesystem as it appears fromwithin the container.

Image layering and sharing

The devicemapper storage driver uses dedicated block devices rather thanformatted filesystems, and operates on files at the block level for maximumperformance during copy-on-write (CoW) operations.

Snapshots

Another feature of devicemapper is its use of snapshots (also sometimes calledthin devices or virtual devices), which store the differences introduced ineach layer as very small, lightweight thin pools. Snapshots provide manybenefits:

Layers which are shared in common between containers are only stored on diskonce, unless they are writable. For instance, if you have 10 differentimages which are all based on alpine, the alpine image and all itsparent images are only stored once each on disk.
Snapshots are an implementation of a copy-on-write (CoW) strategy. This meansthat a given file or directory is only copied to the container’s writablelayer when it is modified or deleted by that container.
Because devicemapper operates at the block level, multiple blocks in awritable layer can be modified simultaneously.
Snapshots can be backed up using standard OS-level backup utilities. Justmake a copy of /var/lib/docker/devicemapper/.

Devicemapper workflow

When you start Docker with the devicemapper storage driver, all objectsrelated to image and container layers are stored in/var/lib/docker/devicemapper/, which is backed by one or more block-leveldevices, either loopback devices (testing only) or physical disks.

The base device is the lowest-level object. This is the thin pool itself.You can examine it using docker info. It contains a filesystem. This basedevice is the starting point for every image and container layer. The basedevice is a Device Mapper implementation detail, rather than a Docker layer.
Metadata about the base device and each image or container layer is stored in/var/lib/docker/devicemapper/metadata/ in JSON format. These layers arecopy-on-write snapshots, which means that they are empty until they divergefrom their parent layers.
Each container’s writable layer is mounted on a mountpoint in/var/lib/docker/devicemapper/mnt/. An empty directory exists for eachread-only image layer and each stopped container.

Each image layer is a snapshot of the layer below it. The lowest layer of eachimage is a snapshot of the base device that exists in the pool. When you run acontainer, it is a snapshot of the image the container is based on. The followingexample shows a Docker host with two running containers. The first is a ubuntucontainer and the second is a busybox container.

How container reads and writes work with `devicemapper`

Reading files

With devicemapper, reads happen at the block level. The diagram below showsthe high level process for reading a single block (0x44f) in an examplecontainer.

An application makes a read request for block 0x44f in the container. Becausethe container is a thin snapshot of an image, it doesn’t have the block, but ithas a pointer to the block on the nearest parent image where it does exist, andit reads the block from there. The block now exists in the container’s memory.

Writing files

Writing a new file: With the devicemapper driver, writing new data to acontainer is accomplished by an allocate-on-demand operation. Each block ofthe new file is allocated in the container’s writable layer and the block iswritten there.

Updating an existing file: The relevant block of the file is read from thenearest layer where it exists. When the container writes the file, only themodified blocks are written to the container’s writable layer.

Deleting a file or directory: When you delete a file or directory in acontainer’s writable layer, or when an image layer deletes a file that existsin its parent layer, the devicemapper storage driver intercepts further readattempts on that file or directory and responds that the file or directory doesnot exist.

Writing and then deleting a file: If a container writes to a file and laterdeletes the file, all of those operations happen in the container’s writablelayer. In that case, if you are using direct-lvm, the blocks are freed. If youuse loop-lvm, the blocks may not be freed. This is another reason not to useloop-lvm in production.

Device Mapper and Docker performance

allocate-on demand performance impact:
The devicemapper storage driver uses an allocate-on-demand operation toallocate new blocks from the thin pool into a container’s writable layer.Each block is 64KB, so this is the minimum amount of space that is usedfor a write.
Copy-on-write performance impact: The first time a container modifies aspecific block, that block is written to the container’s writable layer.Because these writes happen at the level of the block rather than the file,performance impact is minimized. However, writing a large number of blocks canstill negatively impact performance, and the devicemapper storage driver mayactually perform worse than other storage drivers in this scenario. Forwrite-heavy workloads, you should use data volumes, which bypass the storagedriver completely.

Performance best practices

Keep these things in mind to maximize performance when using the devicemapperstorage driver.

Use direct-lvm: The loop-lvm mode is not performant and should neverbe used in production.
Use fast storage: Solid-state drives (SSDs) provide faster reads andwrites than spinning disks.
Memory usage: the devicemapper uses more memory than some other storagedrivers. Each launched container loads one or more copies of its files intomemory, depending on how many blocks of the same file are being modified atthe same time. Due to the memory pressure, the devicemapper storage drivermay not be the right choice for certain workloads in high-density use cases.
Use volumes for write-heavy workloads: Volumes provide the best and mostpredictable performance for write-heavy workloads. This is because they bypassthe storage driver and do not incur any of the potential overheads introducedby thin provisioning and copy-on-write. Volumes have other benefits, such asallowing you to share data among containers and persisting even when norunning container is using them.
Note: when using devicemapper and the json-file log driver, the logfiles generated by a container are still stored in Docker’s dataroot directory, by default /var/lib/docker. If your containers generate lots of log messages, this may lead to increased disk usage or the inability to manage your system dueto a full disk. You can configure a log driver to store your containerlogs externally.

Related Information

container, storage, driver, device mapper

Estimated reading time: 16 minutes

Failed port is already allocated issue 1114 docker for mac github version

Did you know that Docker Desktop now offers support for developers subscribed to a Pro or a Team plan? Click here to learn more.

This page contains information on how to diagnose and troubleshoot Docker Desktop issues, request Docker Desktop support (Pro and Team plan users only), send logs and communicate with the Docker Desktop team, use our forums and Success Center, browse and log issues on GitHub, and find workarounds for known problems.

Troubleshoot

Choose > Troubleshootfrom the menu bar to see the troubleshoot options.

The Troubleshoot page contains the following options:

Restart Docker Desktop: Select to restart Docker Desktop.
Support: Developers on Pro and Team plans can use this option to send a support request. Other users can use this option to diagnose any issues in Docker Desktop. For more information, see Diagnose and feedback and Support.
Reset Kubernetes cluster: Select this option to delete all stacks and Kubernetes resources. For more information, see Kubernetes.
Clean / Purge data: Select this option to delete container and image data. Choose whether you’d like to delete data from Hyper-V, WSL 2, or Windows Containers and then click Delete to confirm.
Reset to factory defaults: Choose this option to reset all options onDocker Desktop to their initial state, the same as when Docker Desktop was first installed.

Diagnose and feedback

In-app diagnostics

If you experience issues for which you do not find solutions in thisdocumentation, on Docker Desktop for Windows issues onGitHub, or the Docker Desktop for Windowsforum, we can help youtroubleshoot the log data. Before reporting an issue, we recommend that you read the information provided on this page to fix some common known issues.

Choose > Troubleshootfrom the menu.
Sign into Docker Desktop. In addition, ensure you are signed into your Docker account.
Click Get Support. This opens the in-app Diagnose & Support (Diagnose & Feedback for free users) page and starts collecting the diagnostics.
When the diagnostics collection process is complete, click Upload to upload your diagnostics to Docker Desktop.
When the diagnostics have been uploaded, Docker Desktop prints a Diagnostic ID. Copy this ID.
If you have subscribed to a Pro or a Team plan, click Get support. This opens the Docker Desktop support form. Fill in the information required and add the ID you copied earlier to the Diagnostics ID field. Click Submit to request Docker Desktop support.
Note
You must be signed in to Docker Desktop using your Pro or Team plan credentials to access the support form. For information on what’s covered as part of Docker Desktop support, see Support.
If you are not subscribed to a Pro or a team plan, you can click Upgrade your account to upgrade your existing account.
Alternatively, click Report an issue to open a new Docker Desktop issue on GitHub. This opens Docker Desktop for Windows on GitHub in your web browser in a ‘New issue’ template. Complete the information required and ensure you add the diagnostic ID you copied earlier. Click submit new issue to create a new issue.

Diagnosing from the terminal

On occasions it is useful to run the diagnostics yourself, for instance ifDocker Desktop for Windows cannot start.

First locate the com.docker.diagnose, that should be in C:ProgramFilesDockerDockerresourcescom.docker.diagnose.exe.

To create and upload diagnostics in Powershell, run:

After the diagnostics have finished, you should have the following output,containing your diagnostic ID:

Troubleshooting topics

Make sure certificates are set up correctly

Docker Desktop ignores certificates listed under insecure registries, anddoes not send client certificates to them. Commands like docker run thatattempt to pull from the registry produces error messages on the command line,like this:

As well as on the registry. For example:

For more about using client and server side certificates, seeHow do I add custom CA certificates?and How do I add client certificates? in theGetting Started topic.

Volumes

Permissions errors on data directories for shared volumes

When sharing files from Windows, Docker Desktop sets permissions on shared volumesto a default value of 0777(read, write, execute permissions for user and for group).

The default permissions on shared volumes are not configurable. If you areworking with applications that require permissions different from the sharedvolume defaults at container runtime, you need to either use non-host-mountedvolumes or find a way to make the applications work with the default filepermissions.

See also,Can I change permissions on shared volumes for container-specific deployment requirements?in the FAQs.

Volume mounting requires shared folders for Linux containers

If you are using mounted volumes and get runtime errors indicating anapplication file is not found, access is denied to a volume mount, or a servicecannot start, such as when using Docker Compose,you might need to enable shared folders.

With the Hyper-V backend, mounting files from Windows requires shared folders for Linux containers. Click and then Settings > Shared Folders and share the folder that contains theDockerfile and volume.

Support for symlinks

Symlinks work within and across containers. To learn more, see How do symlinks work on Windows? in the FAQs.

Avoid unexpected syntax errors, use Unix style line endings for files in containers

Any file destined to run inside a container must use Unix style n lineendings. This includes files referenced at the command line for builds and inRUN commands in Docker files.

Docker containers and docker build run in a Unix environment, so files incontainers must use Unix style line endings: n, not Windows style: rn.Keep this in mind when authoring files such as shell scripts using Windowstools, where the default is likely to be Windows style line endings. Thesecommands ultimately get passed to Unix commands inside a Unix based container(for example, a shell script passed to /bin/sh). If Windows style line endingsare used, docker run fails with syntax errors.

For an example of this issue and the resolution, see this issue on GitHub:Docker RUN fails to execute shellscript.

Virtualization

Your machine must have the following features for Docker Desktop to function correctly.

WSL 2 and Windows Home

Virtual Machine Platform
Virtualization enabled in the BIOS
Hypervisor enabled at Windows startup

Hyper-V

On Windows 10 Pro or Enterprise, you can also use Hyper-V with the following features enabled:

Hyper-Vinstalled and working
Virtualization enabled in the BIOS
Hypervisor enabled at Windows startup

Docker Desktop requires Hyper-V as well as the Hyper-V Module for WindowsPowershell to be installed and enabled. The Docker Desktop installer enablesit for you.

Docker Desktop also needs two CPU hardware features to use Hyper-V: Virtualization and Second Level Address Translation (SLAT), which is also called Rapid Virtualization Indexing (RVI). On some systems, Virtualization must be enabled in the BIOS. The steps required are vendor-specific, but typically the BIOS option is called Virtualization Technology (VTx) or something similar. Run the command systeminfo to check all required Hyper-V features. See Pre-requisites for Hyper-V on Windows 10 for more details.

To install Hyper-V manually, see Install Hyper-V on Windows 10. A reboot is required after installation. If you install Hyper-V without rebooting, Docker Desktop does not work correctly.

From the start menu, type Turn Windows features on or off and press enter.In the subsequent screen, verify that Hyper-V is enabled.

Virtualization must be enabled

In addition to Hyper-V or WSL 2, virtualization must be enabled. Check thePerformance tab on the Task Manager:

If you manually uninstall Hyper-V, WSL 2 or disable virtualization,Docker Desktop cannot start. See Unable to run Docker for Windows onWindows 10 Enterprise.

Hypervisor enabled at Windows startup

If you have completed the steps described above and are still experiencingDocker Desktop startup issues, this could be because the Hypervisor is installed,but not launched during Windows startup. Some tools (such as older versions of Virtual Box) and video game installers disable hypervisor on boot. To reenable it:

Open an administrative console prompt.
Run bcdedit /set hypervisorlaunchtype auto.
Restart Windows.

You can also refer to the Microsoft TechNet article on Code flow guard (CFG) settings.

Windows containers and Windows Server

Docker Desktop is not supported on Windows Server. If you have questions about how to run Windows containers on Windows 10, seeSwitch between Windows and Linux containers.

A full tutorial is available in docker/labs onGetting Started with Windows Containers.

You can install a native Windows binary which allows you to develop and runWindows containers without Docker Desktop. However, if you install Docker this way, you cannot develop or run Linux containers. If you try to run a Linux container on the native Docker daemon, an error occurs:

Running Docker Desktop in nested virtualization scenarios

Docker Desktop can run inside a Windows 10 VM running on apps like Parallels or VMware Fusion on a Mac provided that the VM is properly configured. However, problems and intermittent failures may still occur due to the way these apps virtualize the hardware. For these reasons, Docker Desktop is not supported in nested virtualization scenarios. It might workin some cases, and not in others.

For best results, we recommend you run Docker Desktop natively on a Windows system (to work with Windows or Linux containers), or on Mac to work with Linux containers.

If you still want to use nested virtualization

Make sure nested virtualization support is enabled in VMWare or Parallels.Check the settings in Hardware > CPU & Memory > Advanced Options > Enablenested virtualization (the exact menu sequence might vary slightly).
Configure your VM with at least 2 CPUs and sufficient memory to run yourworkloads.
Make sure your system is more or less idle.
Make sure your Windows OS is up-to-date. There have been several issues withsome insider builds.
The processor you have may also be relevant. For example, Westmere based MacPros have some additional hardware virtualization features over Nehalem basedMac Pros and so do newer generations of Intel processors.

Typical failures we see with nested virtualization

Slow boot time of the Linux VM. If you look in the logs and find some entriesprefixed with Moby. On real hardware, it takes 5-10 seconds to boot theLinux VM; roughly the time between the Connected log entry and the *Starting Docker ... [ ok ] log entry. If you boot the Linux VM inside aWindows VM, this may take considerably longer. We have a timeout of 60s or so.If the VM hasn’t started by that time, we retry. If the retry fails we printan error. You can sometimes work around this by providing more resources tothe Windows VM.
Sometimes the VM fails to boot when Linux tries to calibrate the time stampcounter (TSC). This process is quite timing sensitive and may fail whenexecuted inside a VM which itself runs inside a VM. CPU utilization is alsolikely to be higher.
Ensure “PMU Virtualization” is turned off in Parallels on Macs. Check thesettings in Hardware > CPU & Memory > Advanced Settings > PMUVirtualization.

Networking issues

IPv6 is not (yet) supported on Docker Desktop.

Workarounds

Reboot

Restart your PC to stop / discard any vestige of the daemon running from thepreviously installed version.

Unset `DOCKER_HOST`

The DOCKER_HOST environmental variable does not need to be set. If you usebash, use the command unset ${!DOCKER_*} to unset it. For other shells,consult the shell’s documentation.

Make sure Docker is running for webserver examples

Failed Port Is Already Allocated Issue 1114 Docker For Mac Github Commands

For the hello-world-nginx example and others, Docker Desktop must berunning to get to the webserver on http://localhost/. Make sure that theDocker whale is showing in the menu bar, and that you run the Docker commands ina shell that is connected to the Docker Desktop Engine. Otherwise, you might start the webserver container but get a “web pagenot available” error when you go to docker.

How to solve `port already allocated` errors

If you see errors like Bind for 0.0.0.0:8080 failed: port is already allocatedor listen tcp:0.0.0.0:8080: bind: address is already in use ...

These errors are often caused by some other software on Windows using thoseports. To discover the identity of this software, either use the resmon.exeGUI and click “Network” and then “Listening Ports” or in a Powershell usenetstat -aon | find /i 'listening ' to discover the PID of the processcurrently using the port (the PID is the number in the rightmost column). Decidewhether to shut the other process down, or to use a different port in yourdocker app.

Docker Desktop fails to start when anti-virus software is installed

Some anti-virus software may be incompatible with Hyper-V and MicrosoftWindows 10 builds. The conflicttypically occurs after a Windows update andmanifests as an error response from the Docker daemon and a Docker Desktop start failure.

For a temporary workaround, uninstall the anti-virus software, orexplore other workarounds suggested on Docker Desktop forums.

Support

Docker Desktop offers support for developers subscribed to a Pro or a Team plan. Click here to upgrade your existing account.

This section contains instructions on how to get support, and covers the scope of Docker Desktop support.

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How do I get Docker Desktop support?

If you have subscribed to a Pro and Team account, please raise a ticket through Docker Desktop support.

Docker Community users can get support through our Github repos for-win and for-mac, where we respond on a best-effort basis.

What support can I get?

If you are a Pro or a Team user, you can request for support on the following types of issues:

Desktop upgrade issues
Desktop installation issues
- Enabling virtualization in BIOS
- Enabling Windows features
- Installation crashes
- Failure to launch Docker Desktop on first run
Usage issues
- Crash closing software
- Docker Desktop not behaving as expected
Configuration issues
Basic product ‘how to’ questions such as ‘how to work efficiently on WSL 2’

What is not supported?

Docker Desktop excludes support for the following types of issues:

Use on or in conjunction with hardware or software other than that specified in the applicable documentation
Running on unsupported operating systems, including beta/preview versions of operating systems
Support for the Docker engine, Docker CLI, or other bundled Linux components
Support for Kubernetes
Features labeled as experimental
System/Server administration activities
Supporting Desktop as a production runtime
Scale deployment/multi-machine installation of Desktop
Routine product maintenance (data backup, cleaning disk space and configuring log rotation)
Third-party applications not provided by Docker
Altered or modified Docker software
Defects in the Docker software due to hardware malfunction, abuse, or improper use
Any version of the Docker software other than the latest version
Reimbursing and expenses spent for third-party services not provided by Docker
Docker Support excludes training, customization, and integration

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What versions are supported?

We currently only offer support for the latest version of Docker Desktop. If you are running an older version, you may be asked to upgrade before we investigate your support request.

How many machines can I get support for Docker Desktop on?

As a Pro user you can get support for Docker Desktop on a single machine.As a Team, you can get support for Docker Desktop for the number of machines equal to the number of seats as part of your plan.

What OS’s are supported?

Docker Desktop is available for Mac and Windows. The supported version information can be found on the following pages:

Can I run Docker Desktop on Virtualized hardware?

No, currently this is unsupported and against the terms of use.

windows, troubleshooting, logs, issues