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All right, last talk of the conference and we are gathered here today to talk about containers.
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My name is Tony; I'm from Indiana where we have corn and every two years we can muster a decent professional sports team.
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This is the current state of local development. It may not look as complicated to many of you now, but as your team grows and your company expands, it'll start to look much more complex.
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If you're on a Mac, like many of us are, we likely have Homebrew installed, a Ruby version manager in place, a database up and running, and at least one app.
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As your company evolves, that single app will probably turn into multiple apps, or worse, a microservice architecture, where one of those apps might become legacy and you won't bother upgrading Ruby on it.
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You then find yourself stuck with an older version of Ruby while everything else starts upgrading, or worse, one app insists on using Postgres 12, but everything else is on Postgres 10.
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You can really only have one version of Postgres installed. So, how do you manage that?
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Well, containers are trending right now in DevOps and deployment, but let's explore whether they're worth using for development.
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Some ground rules for this talk: we'll use Docker Community Edition for all of these setups and Docker Compose for configuration.
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Although Kubernetes is likely the future of orchestration, it's much more complicated than Docker Compose.
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For local development, Docker Compose works out pretty well.
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Keep in mind, I'm not an expert; I've only been working with containers for about two years.
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With everything in development, there's no one correct setup.
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When I refer to a Ruby app, I'm typically talking about a web app—it could be Rails, Sinatra, or another framework—essentially something that handles web requests.
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And while it doesn't have to be, if your production app is already containerized by DevOps, you already have a significant head start.
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You can leverage what they've done for you and simply add any additional components you need.
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Fair warning, this is not a tutorial on how to use Docker, but rather on how Docker can be configured to work better for local development.
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We'll go through three primary scenarios to demonstrate how you can utilize containerization for your local workflow.
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These scenarios are backed by companies already using these setups or personal experience.
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The first scenario involves having one app or multiple Ruby apps that are entirely siloed.
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They do not share resources, they don't interact, and they operate separately with individual databases.
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Next, we have a more complex setup where multiple Ruby applications do communicate with each other. This could involve microservices or several monolithic applications needing to interoperate.
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In this case, they may share a database or have separate ones, and finally, the third scenario involves standard Ruby work.
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Perhaps you're a gem author, and we'll evaluate whether it's worth containerizing the development process just to work on gems.
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To kick things off, you'll need an app. For this example, let's pretend it's a highly complicated multi-million dollar application.
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Though realistically, it's just a Sinatra app with a single endpoint.
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We'll require Postgres, Redis, and the ImageMagick binary since we want to perform image manipulation.
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For convenience, let's assume all configuration variables are managed with environment variables.
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The only actual change needed for an existing application to be dockerized is that it should bind to the IP 0.0.0.0 instead of localhost.
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This allows the internal container networking to bind more easily, since they can't see localhost.
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For Sinatra, if you're using Rails, set it with the -b flag to bind to an IP address of your choice instead of localhost.
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Next, we'll need a Dockerfile for our application.
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We're going to build a Dockerfile to support our app. Every Dockerfile has a base image that you're starting from; in this case, we want to use the Ruby stock image from Docker Hub, specifically, the 2.6 tag with Debian stretch.
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The benefit of version tagging is that you can closely match what's running in production.
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If you're running Ubuntu, choose the Ubuntu container; if you're using a different Ruby version, make sure to specify that exact version.
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A major advantage of this approach is that when you want to update Ruby, you simply change that tag, rebuild your containers, and suddenly your local development runs on the new Ruby version.
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You don't have to wait for RVM to propagate updates or compile Ruby from scratch again.
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Next, expose any ports necessary from your web app; in this case, for Sinatra, we expose port 4567.
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You may also set custom environment variables that will be embedded in the container.
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In this specific case, I'm overriding the default location where our gems are installed, setting it to /bundle within the Docker volume.
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This is not a necessity, but I prefer it for local use so I can easily access the gem code for debugging.
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Without this, they install in /usr/local/bundle, a path that's quite cumbersome to remember.
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Next, we'll install any external dependencies that we need to run our application.
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In this case, we're adding the Postgres repository using apt-get and installing the client libraries required for the PG gem, along with the ImageMagick binary.
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These commands are analogous to any you would run in a terminal on a standard Linux distribution.
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If you've previously used Vagrant, this is akin to the Vagrantfile, which outlines step-by-step how to build the Vagrant box.
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It's crucial to keep the number of commands minimal.
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Notice that the slashes at the end are intentional, indicating that all of this is one command.
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Every line in the Dockerfile corresponds to a separate snapshot of the state of the container.
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If a line changes later on, previous unchanged lines will be reused during a rebuild.
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Next, we'll add a work directory, a key difference from a production container: this specifies where the app code will reside. Many tutorials will place it in /app, but you can choose a different location if you prefer.
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We'll physically copy the Gemfile and Gemfile.lock into the volume to ensure those files exist, allowing us to run 'bundle install' to install all gems into the Docker volume.
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At the point we specify the work directory, the app code isn't necessarily present in the container.
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That's why we need to move the Gemfile inside the container.
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Finally, every container needs a command to run by default. I typically use 'RUN bash' just to get things started, but we can override this later.
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Alternatively, you might specify an entry point with a shell script to execute multiple commands.
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For instance, if you want gem installation to occur after the container starts, you could place a 'bundle install' in there.
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Here’s the completed Dockerfile: it's the minimal necessary configuration to run our Ruby application. Yes, we need Postgres and Redis, but they're not running within our container.
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By design, each container should do one thing well; in this case, run our Ruby application.
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Now, we're dealing with multiple containers since we need both a database and a Redis container.
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That's managed via the Docker Compose file, which tells Docker how to handle these different containers.
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In the services section, we start with the web service, which is our web container. We'll specify that all the code it needs is housed in the current directory, essentially at the root of your app code.
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Typically, for local development, developers might place it in the root of their GitHub repository.
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If you have DevOps, they often maintain a separate repository for their Docker files, or embed them in your code repository.
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Next, we want to mount two volumes against our web service. Using '.' at the beginning specifies the current directory, which contains all our code.
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We mount it to /app and give it a delegated tag. This is another change from what you would see in production.
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This instructs Docker to ensure any local changes sync directly with /app in the container, allowing for real-time code changes without needing to rebuild the entire container.
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Next, we override the default command. Here, we simply specify 'ruby app.rb' to initiate Sinatra.
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We then declare which ports we want to expose from Docker's network to our local network.
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In our case, we'll expose Docker's port 4567, allowing access through localhost:4567.
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Now, we add two more services: database and Redis. We specify the default Postgres 12 and Redis containers.
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In the Docker Compose file, we can specify the logging driver to none, which effectively turns off logging.
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You can remove these lines if you need debugging, but they can clutter your logs.
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We also introduce an environment section in our web service. These are custom environment variables exposed only to the container.
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This allows us to modify or add variables without needing to rebuild the entire container.
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For our mock application, we’ll expose the database URL and the Redis URL.
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Lastly, we include a 'depends on' section to ensure the database and Redis services start up alongside the web service.
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Here’s our complete Docker Compose file, which outlines the various services involved with our application and how to expose and link them.
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As for workflow, the first step after adding these files is to run 'docker compose build,' which will execute all commands in the Dockerfile and pull down the necessary containers.
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You can run this command repeatedly with no changes if nothing in the Dockerfile has been modified.
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If you decide to adjust the Dockerfile, the first change point is reflected in the web container.
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Next, you'll want to start everything up with 'docker compose up,' which will launch all the services.
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You'll see various logs in your terminal; if you wish to start a specific service, provide its name with the command.
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Keep in mind the dependencies we outlined earlier.
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To turn everything off, you can hit Ctrl+C or run 'docker compose down' in a separate terminal window.
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But that’s just the basics; we need to engage with our code beyond merely executing it.
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Essentially, we need to run rake tests or drop into a console for debugging.
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The flow for that involves using 'docker compose exec', where you specify a service name along with the command to run.
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For instance, if you want to list all rake tasks, run 'docker compose exec web rake -T'.
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Similarly, you can access IRB, the Rails console, or invoke 'bash' to troubleshoot within the container directly.
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This is essentially the workflow when using containers locally. To summarize, we change into our app directory and run 'docker compose up'.
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You'll see that DB, Redis, and the web container all start successfully.
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Sinatra will listen on the designated port, and accessing localhost:4567 will connect you to your endpoint.
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Congratulations! You've successfully containerized a local app from scratch.
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Now, let's consider whether all of this effort is truly worthwhile.
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We've discussed three scenarios, the first being about multiple Ruby applications that are completely independent from one another.
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The setup I find most effective here involves creating a distinct Dockerfile and Docker Compose file for each repository.
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You manage your app dependencies by navigating into each app directory and running it individually.
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This is beneficial for side projects or small teams, especially when you only have a single app.
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However, if you have multiple apps, this approach fosters clear separation of context.
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If I want to switch from app 1 to app 2, I simply stop app 1, change directories to app 2, and start it.
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The apps won't interfere with one another, and since this is essentially virtualization, they won't compete for laptop resources.
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But I should note, Docker does consume a fair amount of RAM.
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An alternative setup involves using Docker solely for external dependencies, like the database.
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This is a hybrid approach, allowing your Ruby code to run natively on your machine while utilizing Docker only for database services.
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This method reduces the hassle of managing Postgres upgrades.
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To upgrade Postgres, you simply dump the existing database, remove the old Postgres installation, install the new one, and restore from a backup.
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With Docker, you just change the tag in the Compose file, remove the containers, bring up the new one, and restore your dev database.
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Also, every team can work on their respective apps without impacting each other's setups.
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This hybrid approach also enables experimentation with different database versions or data stores.
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You can pull down containers to test with different configurations without the need for local installations.
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The workflow remains similar; you can specify just the database and Redis containers, then manually execute whatever command you need to start your local server.
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The general consensus is that using Docker with all other dependencies is worth it.
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It's particularly beneficial for context switching, especially with multiple projects.
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Personally, I maintain four different Ruby applications, which makes context switching much easier. I can shift between them without concerns.
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You won’t worry about a conflict between a MySQL and a Postgres installation because everything's contained within Docker.
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A company called Lessonly in Indiana explicitly uses this Docker configuration. It expedites onboarding.
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Their onboarding steps are simplified: install Ruby, install gems, and install Docker.
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Simply run one command to get your database set up—no need to deal with Homebrew, Postgres versioning, or complex environment URL configurations.
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This method saves you from managing Docker volumes manually, streamlining your workflow.
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Okay, now let’s consider a scenario involving a client-facing application using Sidekiq for background jobs.
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That application has a Redis instance, and your company develops a second application that utilizes Elasticsearch.
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That app also contains its own Redis instance and potentially shares its main database.
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Now with the addition of apps three, four, and five, each may involve varying dependencies and altering configurations.
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In a large-scale environment, effective communication is paramount.
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By deploying a system allowing teams to manage different containers per their requirements, you minimize dependency clashes.
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One possible framework would be to have every team checking out code into a unified directory.
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Let’s say the code resides in '/home/your_user/work/projects/app_1, app_2...', and so forth.
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Then, introduce a bootstrap repository holding all the necessary Docker and Docker Compose files.
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The bootstrap repository orchestrates all the services required by the applications, ensuring they work smoothly.
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This makes for a neat, organized setup and aids in seamless teamwork.
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A more condensed version of the Docker Compose file can manage dependencies efficiently.
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If all developers agree to use Postgres 12, they only need to check out the necessary services available.
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Share one database cluster to manage multiple database services, which keeps data organized.
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Docker supports mounting volumes effectively so that multiple apps can work on distinct namespaces of the database.
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This setup ensures that each app can interact with the necessary databases without conflicting with one another.
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Each team thus focuses solely on the apps they need, running 'docker-compose up' without worrying about unrelated services.
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The development flow becomes much simpler.
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New developers check out just the bootstrap and the apps they’re interested in, reducing unnecessary complexity.
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In doing so, another team could make updates independently without disrupting others.
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However, it does call for synchronized communication among teams. For example, if a major Postgres upgrade is on the horizon...
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the bootstrap app maintainer simply pulls a new request, updates the tag, which is followed by an announcement to all teams.
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Everyone then rebuilds their containers accordingly.
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No one needs to worry about the intricacies of integrating their applications with the latest changes.
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So, is this structure worth it? Absolutely, especially for companies managing multiple applications.
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It's particularly beneficial to manage numerous apps without requiring direct configurations from all developers.
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SpringBuck is one example of an Indiana company leveraging this structure.
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They've adeptly scaled their environment with five applications ringing alongside three databases.
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All new devs simply sync with the bootstrap repository and follow a few explicit steps to start their setup.
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This leads to less confusion and a more productive environment for everyone.
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However, there is a caveat. What if you're developing gems?
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Spoiler alert: this can be challenging. I've tried maintaining a few gems, and this is what I came up with.
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You have a Dockerfile and a Docker Compose file set up in a root directory, while keeping your gem code above these directories.
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The goal is to have one standard Dockerfile that essentially just executes Ruby.
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This setup allows all directories to mount as volumes.
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It leads to oversimplified Dockerfiles that handle a multitude of tasks, further complicating the actual work.
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Using the default container may necessitate complexities that gem tasks sometimes present.
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This might involve setting up Ruby versions but is clumsy at best.
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If you want to run your tests against every database, you can indeed create corresponding entries but requires more setup effort.
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This also enables you to run all your external dependencies in one network.
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But I found myself overwhelmed while exploring this for gems—it's not worth it for standard Ruby developers.
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Instead, I recommend using the first scenario as a template, which keeps the original gems isolated to easy work.
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This way, external contributors can pull the repository and easily set everything up they require.
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There are certainly pros shared across these examples.
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They simplify bootstrapping: you avoid applying installations manually and can construct your development environment quickly.
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It's critical to have your development environment closely resemble production; discrepancies can introduce costly errors.
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Dependency management becomes easier as well, with applications utilizing Postgres, and upgrades seem virtually effortless.
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The ultimate workaround is to completely rebuild the container if issues arise, relieving cumbersome environmental factors.
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Nonetheless, there are some cons to containers: running everything on a VM does introduce some speed limitations.
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If you’re running heavy computations, expect to wait a little longer compared to a native install.
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Also, using linters like Rubocop might be slow, since those run in the Docker container, rather than directly.
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You might still need to install Ruby locally, depending on your workflow.
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Furthermore, Mac OS presents its own difficulties—especially regarding file system performance.
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Changes made on your Mac may not always reflect in Docker containers immediately.
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Some junior developers face a learning curve since they're not familiar with Docker.
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They need to remember that the code runs in a container and requires consideration from the outside in.
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Docker consumes considerable resources, like RAM and hard drive space.
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Frequent Docker image builds can consume space quickly, necessitating a clean-up process.
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Overall, while local containers may slow down development, they can benefit larger applications and teams significantly.
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Still, for smaller projects, it may be best to evaluate requirements and adjust based on the intended use.
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It’s a significant change in workflow, matching towards more orchestrated systems.
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Ultimately, if your growth projections suggest more apps on the horizon, using Docker could simplify the future development process.
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So, there you have it: my perspective on whether local containerization is worthwhile.
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You may have already seen some slides or materials supporting the use of containers.
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Thank you for spending your time here at the conference, and I hope you learned something beneficial today.
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Any questions? I have about a minute or so. Thank you!
