If you’ve moved your development environment to Docker, you might have noticed your web application stacks might be slower than another native environment you’ve been used to. There are things we can do to return your response times back down to how they were (or thereabouts).
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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. End goal was building iOS apps w/o any mac hardware. Using some open source patches to clang, libimobiledevice, and a whole bunch of other tools, I was able to write an iOS app in 'good ole C in emacs' on my linux laptop, cross compile it for the iPhone, and even code sign, upload and run it on the phone. This was several years ago. Docker for Mac In this section we'll walk you through the steps to get a single Solace PubSub+ software event broker Docker container up-and-running in macOS using Docker Compose. If you're interested in setting up event brokers in an HA redundancy group on a macOS platform, take a look at HA Group Configuration for macOS. OpenFOAM® Installation on Mac. Uses Docker Hub to distribute pre-compiled versions of OpenFOAM for Linux, Mac OS X and Windows, including a complete development environment. Docker containers enable binaries compiled on a given Linux environment to be run on other platforms without any performance degradation.
Overview
1. Volume optimisations
Modify your volume bind-mount consistency. Consistency cache tuning in Docker follows a user-guided approach. We prefer delegated for most use-cases.
2. Use shared caches
Make sure that common resources are shared between projects — reduce unnecessary downloads, and compilation.
3. Increase system resources
Default RAM limit is 2GB, raise that up to 4GB — it won’t affect system performance. Consider increasing CPU limits.
4. Further considerations
A few final tips and tricks!
Introduction
Most of our web projects revolve around a common Linux, Nginx, MySQL, PHP (LEMP) stack. Historically, these components were installed on our machines using Homebrew, a virtual machine, or some other application like MAMP.
At Engage, all our developers use Docker for their local environments. We’ve also moved most of our pre-existing projects to a Dockerised setup too, meaning a developer can begin working on a project without having to install any prerequisites.
When we first started using Docker, it was incredibly slow in comparison to what we were used to; sharp, snappy response times similar to that of our production environments. The development quality of life wasn’t the best.
Why is it slower on Mac?
In Docker, we can bind-mount a volume on the host (your mac), to a Docker container. It gives the container a view of the host’s file system — In literal terms, pointing a particular directory in the container to a directory on your Mac. Any writes in either the host or container are then reflected vice-versa.
On Linux, keeping a consistent guaranteed view between the host and container has very little overhead. In contrast, there is a much bigger overhead on MacOS and other platforms in keeping the file system consistent — which leads to a performance degradation.
Docker containers run on top of a Linux kernel; meaning Docker on Linux can utilise the native kernel and the underlying virtual file system is shared between the host and container.
On Mac, we’re using Docker Desktop. This is a native MacOS application, which is bundled with an embedded hypervisor (HyperKit). HyperKit provides the kernel capabilities of Linux. However, unlike Docker on Linux, any file system changes need to be passed between the host and container via Docker for Mac, which can soon add a lot of additional computational overhead.
1. Volume optimisations
We’ve identified bind-mounts can be slow on Mac (see above).
One of the biggest performance optimisations you can make, is altering theguarantee that file system data is perfectly replicated to the host and container. Docker defaults to a consistent guarantee that the host and containers file system reflect each other.
For the majority of our use cases at Engage we don’t actually need a consistent reflection — perfect consistency between container and host is often unnecessary. We can allow for some slight delays, and temporary discrepancies in exchange for greatly increased performance.
The options Docker provides are:
Consistent | The host and container are perfectly consistent. Every time a write happens, the data is flushed to all participants of the mount’s view. |
Cached | The host is authoritative in this case. There may be delays before writes on a host are available to the container. |
Delegated | The container is authoritative. There may be delays until updates within the container appear on the host. |
The file system delays between the host and the container aren’t perceived by humans. However, certain workloads could require increased consistency. I personally default to delegated, as generally our bind-mounted volumes contain source code. Data is only changing when I hit save, and it’s already been replicated via delegated by the time I’ve got a chance to react.
Some other processes, such as our shared composer and yarn cache could benefit from Docker’s cached option — programs are persisting data, so in this case it might be more important that writes are perfectly replicated to the host.
See an example of a docker-compose.yml configuration below:
Docker doesn’t do this by default. It has a good reason, which states that a system that was not consistent by default would behave in ways that were unpredictable and surprising. Full, perfect consistency is sometimes essential.
Further reading:https://docs.docker.com/docker-for-mac/osxfs-caching/
2. Using shared caches
Most of our projects are using Composer for PHP, and Yarn for frontend builds. Every time we start a Docker container, it’s a fresh instance of itself. HTTP requests and downloading payloads over the web adds a lot of latency, and it brings the initial builds of projects to a snail’s pace — Composer and Yarn would have to re-download all it’s packages each time.
Another great optimisation is to bind-mount a ‘docker cache’ volume into the container, and use this across similar projects. Docker would then pull Composer packages from an internal cache instead of the web.
See an example of bind-mounting a docker cache into the container, we do this in the docker compose configuration:
3. Increasing system resources
If you’re using a Mac, chances are, you have a decent amount of RAM available to you. Docker uses 2GB of RAM by default. Quite a simple performance tweak would be to increase the RAM limit available to Docker. It won’t hurt anything to give Docker Desktop an extra 2GB of RAM, which will greatly improve those memory intensive operations.
You can also tweak the amount of CPUs available; particularly during times of increased i/o load, i.e running yarn install. Docker will be synchronising a lot of file system events, and actions between host and container. This is particularly CPU intensive. By default, Docker Desktop for Mac is set to use half the number of processors available on the host machine. Increasing this limit could be considered to alleviate I/O load.
4. Further considerations
This post isn’t exhaustive, as I’m sure there are other optimisations that can be made based on the context of each kind of setup. In our use cases though, we’ve found these tweaks can greatly improve performance.
Some final things to consider are:
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- Ensure the Docker app is running the latest version of Docker for Mac.
- Ensure your primary drive, Macintosh HD, is formatted as APFS. this is Apple’s latest proprietary HDD format and comes with a few performance optimisations versus historical formats.
Final notes
Docker are always working on improving the performance of Docker for Mac, so it’s a good idea to keep your Docker app up to date in order to benefit from these performance optimisations. Most of the performance of file system I/O can be improved within Hypervisor/VM layers. Reducing the I/O latency requires shortening the data path from a Linux system call to MacOS and back again. Each component in the data path requires tuning, and in some cases, requires a significant amount of development effort from the Docker team.
Matthew primarily focuses on web application development, with a focus on high traffic environments. In addition, he is also responsible for a lot of our infrastructure that powers all of our various apps and systems.
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Recently out of private beta, Docker’s new native applications aim to replace the current methods for running Docker on Windows and Mac, creating a better experience for developers using those platforms.
For the previous solution, Docker Toolbox used VirtualBox to create a small Linux virtual machine that hosted your images and containers. It worked pretty well but could be unreliable at times and required workarounds that sometimes resulted in unexpected outcomes or not working at all.
Docker for Mac removes the dependency on VirtualBox and instead uses virtualization technology that is already part of Mac OS X, HyperVisor. Docker for Windows uses Microsoft’s virtualization technology, Hyper-V. These changes aim to make your Docker containers run faster than before, take up less disk space, and fit better into your operating system.
I am a Mac user, so I’ll be focusing on the Mac version of Docker’s new application, but I’ll highlight any significant differences with the Windows version. Adobe suite cs6 torrent for mac.
[Tweet “”An Introduction to Docker for Mac” via @ChrisChinch”]
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Install and Setup
Download the native application for your platform here.
Successive updates to the application have made the installation process and the resulting application increasingly “more native” and better integrated with the operating system. Because the application uses newer technologies only available in newer machines and OS versions, it has minimum requirements, which are:
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Mac minimum requirements
- A 2010 or newer model, with Intel’s hardware support for memory management unit (MMU) virtualization
- OS X 10.10.3 Yosemite or newer, as the Hypervisor framework used is available in Yosemite onwards
- At least 4GB of RAM
- VirtualBox prior to version 4.3.30 must not be installed as it will cause issues with Docker for Mac
Windows minimum requirements
- 64bit Windows 10
Co-existing with Docker Toolbox
If you are using Docker Toolbox, your images and containers can typically coexist together. This is thanks to Docker Toolbox using VirtualBox to host images and containers, and installing command line tools to more “Linux” path locations. Both Docker for Mac and Windows are fully native to the host platform and install everything into locations you would expect (e.g., The Applications folder), only using symlinks to make certain tools accessible on the command line.
When you first run the Docker application, it will check your system for compatibility and requirements, show a welcome screen, and then start the Docker process. Your main interaction with the Docker application will be via a menu bar item: to stop and start the Docker process, open Kitematic for GUI access to your containers, find documentation, and access preferences.
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Preferences and Configuration
General
The General pane has settings for configuring the specs of the virtual machine, updates, and excluding the virtual machine from backups (Mac only). This is a simple but useful feature to have, as it can end up being a large file.
Advanced
Many enterprise users of Docker use their own registries for custom images. The advanced settings pane lets you define custom registries to search for images that you trust.
The application should automatically detect any HTTP(s) proxy settings you have at an operating system level, but you can check them here. While not a part of this preference pane, it will also automatically detect any VPN settings you have, allowing access to any containers running within it.
File sharing
While sharing volumes between Docker containers and the host operating system was possible with Docker Toolbox, it could be slow and suffer permissions issues. Docker for Mac uses a new file system created by Docker called “osxfs.” I can’t find much detail on the new file system, but there is some information here.
You can add or remove share local paths to share with containers using the + and – buttons, but these paths shouldn’t overlap (e.g., not Users and Users/homefolder).
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Using Docker Natively
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Little of the process for using Docker has changed, except that it requires fewer steps. For example, with the application running, you can use Kitematic or the command line to download and start images as containers. Here’s the “Hello World” image running in Kitematic:
Notice something else cool there? No more custom IP addresses to remember! All your Docker containers now run on localhost and will be port mapped to the address.
Other Docker commands such as docker-compose and docker-machine work, but for Machine (and thus Swarm) you will need to define a non-native driver. This means you can manage Docker Machine from your Mac, but the machines will still be hosted elsewhere and still need to be managed by the traditional eval $(docker-machine env default) commands.
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The Future?
I personally use Docker for rapid testing and prototyping ideas, and so rarely take my containers off my Mac. Of course, few people will use Docker with Mac or Windows in production, so many might ask if there is much point in the Docker team making native applications for these platforms.
Still, a lot of developers will be using these platforms during development, and I for one thank the Docker team for making my experience feel much more friendly and accessible. The applications are still considered betas, and the team welcomes any feedback you have to help them improve, so if you also appreciate the effort made, then help them out.
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[Tweet “”Here’s why native apps matter even if you’re not using Docker with Mac or Windows in production.””]
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