Deleting a Age Of Mythology For Mac Full Game is just as easy as creating one, but the trial version won’t let you edit any virtual drives, making it tough for us to evaluate this program’s full potential. Although novices will be grateful for VirtuaDisk’s ease of use, those seeking high-end features should keep looking.There are two ways to use Age Of Mythology For Mac Full Game: Ask for Opinions or Give Your Opinion. On the plus side, installation is quick, and we detected no drain on system performance. We generated a new Age Of Mythology For Mac Full Game for our PC in a matter of seconds,and we appreciate the ability to password-protect, compress, and print logs of virtual drives. Even if you’ve never used this type of software, Age Of Mythology For Mac Full Game won’t confuse, as it walks you through the creation process with a step-by-step tutorial.
With Docker Desktop for Mac, file systems operate in containers in the same way as. Most inotify events are supported in bind mounts, and likely dnotify. How to speed up shared file access in Docker for Mac. Docker just released a native MacOS runtime environment to run containers on Macs with ease. They fixed many issues, but the bitter truth is they missed something important. The read and write access for mounted volumes is terrible.
In this post, I’m going to explain why installing, configuring, and maintainingsoftware in development, testing, and production environments can be a completenightmare. After that, I’m going to show you a better way to do it usingDocker. Finally, I’ll introduce a small open sourceproject I created called docker-osx-dev, which makesit easier to setup a productive development environment with Docker on OS X.
Motivation
Let’s say you just started at a new company or you discovered a handy new opensource library and you’re excited to get things running. You git clone thecode, search for install instructions, and come up empty. You ask yourco-workers where you can finddocumentation,and they laugh. “We’re agile, we don’t waste time on documentation.” Everyoneremembers that setting things up the first time was painful—a hazingritual for new hires—but no one really remembers all the steps, andbesides, the code has changed and the process is probably different now anyway.
Even if you do find documentation, it’s inaccurate, out of date, and incomplete.You copy some files here and there. You install a programming language or two.You run a random shell script. You fiddle with environment variables. Eventually,you figure out that you need a specific version of some library installed, andso off you go to upgrade OS X, or to figure out how to run Python 2 side-by-sidewith Python 3, or to add symlinks to ensure you’re using the proper version ofJava, or to download the multi-gigabyte XCode installer (seriously, why is it sofreaking huge?). And, of course, some of the requirements from one projectconflict with the requirements of another project. Before you know it, you’respending hours reading about RVM and RBEnv so you can run multiple versions ofRuby, you’re fighting with strange errors with C header files, and you’rewondering what the F#@K is Nokogiri and why does it never install correctly?
Eventually, you find yourself in an infinite loop of 1) try to run thecode, 2) get an obscure error message, 3) Google it, 4) try random suggestionsyou find on StackOverflow, 5) go back to step 1. The last straw is when youfind out you have to deal with Satan himself in the form of software fromOracle. Seriously, have you ever installed Oracle DB? It’s a multi-day processthat involves formatting half your hard drive, a drug induced trip into theHimalayas to find a rare blue Orchid, and a two day session where Oracle’slawyers beat you with reams of legal documents. And why the F#[email protected] does theOracle Java updater try to install the MOTHERF&#[email protected] Ask Toolbar?
Installing and configuring software is the ultimate form of YakShaving.The complexity of getting software running is responsible for:
- Driving many people away from programming. Most people are not masochisticenough to deal with a user experience that is equal parts out-of-datedocumentation, XML configuration files, arcane error messages, and frantic,rage-driven Google searches.
- Wasting a huge amount of time. Not only do you have to go through this awfulinstallation process in your development environment, but every otherdeveloper on your team does too.
- A huge percentage of bugs. Even if you get the software running in yourdevelopment environment, getting it to work the same way in the testing andproduction environments is the same nightmare all over again. The probabilityof missing a step or something going out of sync is approximately 100%.
There have been many attempts to automate this process, but they all have majordrawbacks. For example, you could create custom shell scripts and lotsof documentation for how to setup your code, but this is always a nightmare tomaintain, update, and test. You could use Configuration Management (CM)software, such as Chef, Puppet,and Ansible, which make it easier to automate yourtesting and production environments, but they are fairly useless for settingup a development environment, and incur too much overhead and cost to use for asmall open source or side project. Finally, you could package your code intoVirtual Machine (VM) images, which will run the same way everywhere, but VMimages incur a lot of performance overhead, which causes problems in theproduction environment, and they use a lot of resources and are slow to start,which causes problems in the development environment.
Introducing Docker
This is where Docker comes in. Docker runs your codein a container, which is like a lightweight VM. Whereas a full VM virtualizesall the hardware and the operating system, a container runs your code directlyon the host operating system and hardware, but in an isolated userspace. Thisway, you get all the isolation and consistency benefits of a VM, but with verylittle overhead. Not all operating systems support isolated userspaces. Docker,in particular, relies on the Linux kernel and the LinuxContainers (LXC) project. If you run your codeon top of Linux in production, then Docker is for you.
The easiest way to understand Docker is to walk through an example. If you haveDocker installed, the first thing you need to do is to pull a Docker image:
A Docker image defines a set of files and some instructions for running them.In this case, the image we are using is of the Ubuntu operatingsystem. The pull command will download this image(which is about 188MB) and cache it on your computer so you won’t have todownload it again. Public images are stored in the Docker HubRegistry, which is a bit like GitHub:it’s a collection of open source Docker images (such as Ubuntu) that anyone candownload using docker pull (like git pull) and anyone can contribute tousing docker push (like git push).
Now that you have the image on your computer, you can use docker run to runit:
What just happened? Well, the run command fired up the ubuntu image and toldit to execute the command echo 'Hello, World'. That’s right, you’re firing upthe entire Ubuntu operating system just to print “Hello, World” to theterminal. How long does it take? You can use the time command to find out:
0.183 seconds! This is on my Apple laptop, which runs OS X. On a high poweredLinux desktop, it would be even faster. Whereas starting up an operating systemin a VM is a big operation that can take minutes, in Docker, it’s a trivialoperation that takes a fraction of a second. There is no trick here. It’s thereal Ubuntu OS and it is completely isolated from my host OS. For example, hereis a quick screencast of firing up bash in an Ubuntu container and running afew commands:
Docker containers start and stop so quickly, and are so lightweight, that youcould easily run a dozen of them on your developer work station (e.g. one for afront-end service, one for a back-end service, one for a database, and so on).But what makes Docker even more powerful is that a Docker image will runexactly the same way no matter where you run it. So once you’ve put in thetime to make your code work in a Docker image on your local computer, you canship that image to any other computer and you can be confident that your codewill still work when it gets there.
One of the easiest and most effective ways to create a Docker image is to writea Dockerfile. Instead ofconfiguring your tech stack through manual steps and documentation, aDockerfile allows you to define your infrastructure ascode.For example, here is a Dockerfile that defines a Ruby on Rails stack:
Let’s go through this file line by line. The FROM ubuntu:14.04 command saysthat this image will run on top of Ubuntu version 14.04. Next, there are severalRUN commands which will execute code in this image. The first RUN commanduses apt-get, the Ubuntu package manager, to install Ruby and a bunch ofdependencies for Rails (notice how many dependencies there are just for avanilla Rails app!). The next RUN command uses gem, the Ruby packagemanager, to install Rails itself. After that, a RUN command creates a /srcfolder, another one uses rails new to create a new Rails app called my-app,and the WORKDIR command sets /src/my-app as the working directory.Finally, the CMD command will execute rails server when you use docker runon this image and the EXPOSE command makes port 3000 visible to the host OS.
You can use the docker build command to turn this Dockerfile into a Dockerimage:
Once the image is created, you can use the docker images command to see allthe images on your computer:
You can see the ubuntu image from earlier, as well as the new my-rails-appimage from running docker build. You can use the docker run command to testthis new image and you’ll see that it starts up the Rails server on port 3000:
You can now test your Rails app by visiting http://localhost:3000 (note: onOS X, the URL for testing will be different, as I’ll discuss later). Oneimportant thing to note is that the code for this Rails app, which was generatedby the rails new command, is inside of the Docker container and therefore notvisible on the host OS. But what if you wanted to checkout and edit the code inthe host OS (e.g. OS X) while still being able to run the code inside theDocker container? To do that, you can mount a folder using the -v flag indocker run:
The command above will take the /foo folder in the host OS and make itavailable in the Docker container at /bar. This way, you can use all the texteditors, IDEs, and other tools you already have installed to make changes in/foo and you’ll see them reflected immediately in the Docker container in/bar.
Once you get your Docker image working locally, you can share it with others.You can run docker push to publish your Docker images to the public Dockerregistry or to a private registry within your company. Or better yet, you cancheck your Dockerfile into source control and let your continuous integrationenvironment build, test, and push the images automatically. Once the image ispublished, you can use the docker run command to run that image on anycomputer—such as another developer’s workstation or in test or inproduction—and you can be sure that app will work exactly the same wayeverywhere without anyone having to fuss around with dependencies orconfiguration. Many hosting providers have first class support for Docker, suchas Amazon’s EC2 Container Serviceand DigitalOcean’s Docker support.
Once you start using Docker, it’s addictive. It’s liberating to beable to mess around with different Linux flavors, dependencies, libraries, andconfigurations, all without leaving your developer workstation in a messy state.You can quickly and easily switch from one Docker image to another (e.g. whenswitching from one project to another), throw an image away if it isn’t working,or use Docker Compose to work with multipleimages at the same time (e.g. connect an image that contains a Rails app toanother image that contains a MySQL database). And you can leverage thethousands of open source images in the Docker Public Registry. For example,instead of building the my-ruby-app image from scratch and trying to figureout exactly which combination of libraries make Rails happy, you could usethe pre-built rails imagewhich is maintained and tested by the Docker community.
Docker on OS X
If you’re already using Linux as your desktop operating system, Docker is ano-brainer. Unfortunately, there are many, manyreasonsyou might not want to use Linux on the desktop, and prefer OS Xinstead. If so, there is a problem: OS X is built on top of Unix, not Linux,so you can’t run Docker on it directly. Instead, you have to run Linux in a VM(which is why on OS X, instead of using localhost in your URLs, you need touse the IP of the VM). But wasn’t the whole point of Docker to avoid heavyweightVMs? This in and of itself isn’t actually as big of a problem as it sounds forthree reasons:
- You only need the VM in the development environment, so the performanceoverhead does not affect production.
- You only need to run a single VM no matter how many Docker containers youwant to run on top of it. You pay the penalty of starting this VM just onceand you leave it running in the background. You can then run as manydocker containers as you want on top of this VM, with each container startingand stopping in a fraction of a second.
- Thanks to the Boot2Docker project, you can use astripped down version of Linux specially tailored for Docker as your VM. Itruns completely in RAM, takes up only 27MB, and boots up in about 5 seconds!
In other words, Boot2Docker provides a great experience for using Docker onOS X. Except for one thing: mounted folders. By default, the Boot2Docker VMimage runs inside of VirtualBox, a free and opensource hypervisor. VirtualBox is great, but the system it uses to mount folders,called vboxsf, is agonizingly slow. For example, here is how long it takesJekyll to compile my homepagecode if I don’t useany mounted folders and just include the code directly inside the Docker imageitself:
And here is the exact same Docker image, but this time, I mount the source codefrom OS X:
7 seconds versus 74 seconds! And that’s on a small, simple Jekyllproject. With more complicated projects, using vboxsf leads to a 10-20xslowdown in compilation speed, server startup time, and just about everythingelse.
Another major problem with vboxsf is that it breaks file watchers. Build systemslike Jekyll, SBT, Grunt, and many others listen for file changes usingOS-specific technologies such as inotify on Linux and FSEvents on OS X. Thatway, when you change a file, those build systems get a notification about thechange immediately, and can recompile it quickly so you can rapidly iterate onyour code using a make-a-change-and-refresh development cycle. Unfortunately,vboxsf breaks inotify and FSEvents, so those build systems never getnotifications about file changes. Your only option is to enable polling, forcingthe build systems to linearly scan through all files, which consumes a lot ofresources and takes a lot longer to spot a change and recompile the code. Inshort, vboxsf is completely unusable for active development.
I spent a few days looking for a solution. I tried to follow advice in randomBoot2Docker bug discussionsand GitHub Gists.I tried many different technologies, including Vagrant, NFS, Unison, and Samba.I made a StackOverflow threadto ask for help. After lots of trial and error, I finally found something thatworks great on OSX and I’ve packaged it up as a small open source project calleddocker-osx-dev.
docker-osx-dev
The best alternative I found to using vboxsf was to usersync, a common Unix utility that can cansync files quickly. With rsync, I found that build performance in my Dockercontainers with mounted folders was on par with running the build withoutmounted folders, and file watch mechanisms based on inotify all work correctly.I’ve been using docker-osx-dev for a couple weeks andhave been very productive as I switch between three different projects withthree totally different tech stacks.
To use docker-osx-dev, you must first install HomeBrew. Afterthat, just download the docker-osx-dev script and run the install command:
This will setup your entire Docker development environment, includingBoot2Docker, so the only thing left to do is to kick off file syncing and startrunning your Docker containers:
By default, docker-osx-dev will sync the current folder (/foo/bar in theexample above) to the Boot2Docker VM. Alternatively, you can use the -s flagto specify which folders to sync:
If you are using Docker Compose, thedocker-osx-dev script will automatically sync any folders marked asvolumes in yourdocker-compose.yml file:
Now, in a separate tab, you can start and stop as many docker containers as youwant and mount the /foo/bar folder in them. This will happen automaticallywhen you run docker-compose up. Alternatively, you can specify folders tomount manually using the -v flag of docker run:
You can test this Rails app by going to http://dockerhost:3000 in your browser,as docker-osx-dev automatically configures dockerhost as a URL for yourdocker VM. Also, with docker-osx-dev running, you can edit any of the files inmounted folders using the tools you’re used to in OS X, and the changesshould propagate instantly into the Docker container using rsync. Moreover,your builds should be fast and all file watchers should work normally.
Conclusion
I hope that in the future, more and more companies will package their techstacks as Docker images so that the on-boarding process for new-hires will bereduced to a single docker run or docker-compose up command. Similarly, Ihope that more and more open source projects will be packaged as Docker imagesso instead of a long series of install instructions in the README, you just usedocker run, and have the code working in minutes. As an experiment,I’ve created Docker images for a few of my open source projects, includingping-play,hello-startup, and myhomepage, which you’rereading now.
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I also hope that some day, the issues with vboxsf will be fixed, but in themeantime, I’ll be using docker-osx-dev for all of mycoding and encourage you to give it a try. The code is new and fairly rough, sofeel free to give me feedback, file bugs, and send pull requests.
Finally, if you want to learn how to take your Docker containers and run themin production, check out my follow-up blog posts,Running Docker on AWS from the ground up andInfrastructure as code: running microservices on AWS using Docker, Terraform, andECS.