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Hello everyone, a very good afternoon! I really enjoyed the lightning talks. Thanks, everyone! I hope you guys are slightly awake.
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This talk is slightly off the central topic; it's more about DevOps rather than Ruby on Rails per se.
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I'd like to know who here is already familiar with Docker, who has tried it out, or who at least knows what it does.
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Okay, not too many. Sorry about that! I've been a web developer for quite some time, and a good part of that has been with Ruby on Rails.
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I actually remember the days when the 15-minute video came out.
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Over the years, I've also been involved in setting up servers for the Ruby teams that I’ve worked with, and I’ve been a Linux guy for as long as I can remember.
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Lately, I’ve been observing what’s happening on the production side of things.
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So, how many of you have set up your own Linux servers and maintained them?
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Oh, quite a few! Okay, then this should be relevant to what you're doing.
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We're going to talk about zero downtime deployments with Docker.
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So, what is Docker? The first thing that Docker does is it commoditizes Linux containers.
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You can think of containers as something like a chroot jail that you have in Linux.
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It basically gives you a separate folder as a root directory from where you can run your processes.
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All the child processes are only allowed to access that part of the directory as a root directory.
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A container extends this concept by providing network-level isolation and disk-level isolation.
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Linux containers are a fairly old technology, but they have been primarily understood by those who are deeply familiar with Linux and production.
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Docker makes this technology accessible to all of us, allowing for portable deployments across different machines.
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You have a Vagrant box that runs a specific version, but you can also run production systems from another version.
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You get a lot of flexibility for moving your production images around.
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This also enables efficient and quick provisioning while saving disk space through copy-on-write installations.
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Docker achieves near-native performance; it's essentially process virtualization, so you don’t have the overhead of hardware virtualization.
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You have a base image, say Ubuntu, and you can install applications like Emacs and make it into another image.
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This process allows for a lot of reusability. You can push these images to a public repository that Docker maintains at index.docker.io.
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If they're public and open for sharing, others can use your custom image as needed.
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The major difference between how Linux containers work and how Docker encourages the use of containers is as an application.
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Instead of treating a container like a lightweight server where you install everything, Docker promotes the idea of having a specific application in each container.
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For instance, you could have your database MySQL in one container, your app server in another, and so on.
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At the most basic level, Docker provides OS-level virtualization for Linux.
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This is much faster and lighter compared to hardware virtualization methods.
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Docker sets up its own process space, network interface, and init system within the container.
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Isolation is achieved through control groups (cgroups). Cgroups allow you to put limits on resource usage like network, disk, and processing power.
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The catch is that it shares the kernel with the host, so you cannot run incompatible images.
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A typical Docker image consists of a kernel, cgroups, namespaces, and device mappers. Docker achieves image versioning through a union file system.
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Debian-based installations utilize AUFS, which has limitations in its integration with the Debian kernel.
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However, alternatives like device mapper have been integrated to overcome these challenges.
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The base image is shipped from Docker registry, and any additions you make will lead to new read-only images.
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The basic workflow involves pulling Docker images from the public registry, running them, adding your changes, and then pushing them back.
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Docker also provides a Dockerfile which allows you to build your own images. You can also set up private repositories for workgroups.
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A private registry is useful when you want to share images within your company and not publicly.
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I'll now show you a simple deployment workflow using a Dockerfile to explain the process further.
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At the most basic level, when you pull from Docker, it checks for layers available on your system and adjusts accordingly.
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This eliminates redundant downloads, which saves time and resources.
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Kicking off a container is simple: you have to specify an entry point and it will drop you into a root prompt where you can start installing applications.
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The basic idea is to have a very minimalistic Docker image, where you can add your software on top and then commit it.
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So, let's say I install the nano editor; this process should be pretty quick.
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If I switch to another window, I can check the running containers.
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You can see each container has its own name and status. You can rename them, which is a relatively new feature.
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Each container also provides insights into what's happening inside it.
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You can commit changes made inside a container to create a new image.
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So after making my edits, let’s say I want to commit the changes and give it a name.
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Now, you can see the newly created images, and you can push them to the public registry to share them.
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The public repository is a central place where you can search for images necessary for your deployments.
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You can also install Docker on your private servers to ensure that your images are secure.
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Next, I’ll discuss the Dockerfile, which is similar to a Rakefile or Makefile you may use in your projects.
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The Dockerfile is essentially a glorified shell script that provides a straightforward way to build images.
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You can use directives like FROM, RUN, and CMD to define the behavior of your Docker images.
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The FROM directive specifies the base image, and RUN allows you to execute commands like installing packages.
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The CMD specifies what command to run, and ENTRYPOINT sets the executable that runs inside the container.
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In summary, you can mount directories as volumes and configure your containers with a variety of commands.
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Docker is designed to be simple and straightforward, making it easy to start using and learn without a lot of overhead.
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Now, let’s shift our focus to zero downtime deployments. Why do we need them?
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The most important aspect involves continuous delivery and continuous deployments. While similar, they differ subtly.
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Continuous delivery involves regularly delivering software updates, maintaining tight communication with clients.
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On the other hand, continuous deployment takes this one step further, aiming to make deployments as seamless as possible with minimal disruptions.
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As developers, we are all familiar with long deployments, particularly during schema migrations.
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During heavy migrations or other processes, it’s common to put up maintenance pages to avoid errors.
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However, these problems extend beyond Rails and can also occur in Django or other frameworks.
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To address this, Docker is a framework-agnostic solution that allows different applications to coexist.
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When considering zero downtime deployments, one of the tasks to tackle is database synchronization.
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In scenarios with databases, it's essential to ensure that master and slave databases are in sync.
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Tools like Zookeeper help manage the master/slave relationships.
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A simpler case can be illustrated by using HAProxy.
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HAProxy is essentially a robust load balancer, acting like a reverse proxy.
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You can set up multiple active and backup servers, where the backup servers remain idle until all the active servers are down.
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During deployment, you can build the new Docker image while still serving from the active servers, maintaining availability.
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Once the new services are up and running, you take down the old active servers and switch to the new backup servers.
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This ensures that at least during the switch, requests are routed correctly with minimal interruptions.
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While this setup won’t allow for migrations seamlessly, it greatly reduces compile times and downtime.
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Let’s quickly recap the workflow; open up your HAProxy and observe how it balances requests among the different servers.
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Also, review your deployment scripts and ensure you have configured the versions correctly.
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Later, I will show a simple Dockerfile representing the setup process.
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You can start from an Ubuntu image and perform package installations as needed.
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Let’s proceed with the deployment and I will explain the steps involved.
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This deployment process runs in the background while I explain further.
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What I'm effectively doing is automating tasks that would otherwise be manual.
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In this Dockerfile, I'm installing some basic dependencies and setting configurations.
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Using Docker simplifies the deployment process while also allowing easier maintenance.”},{
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By exposing ports, containers can communicate easily with each other and the host system.
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Next, I will show you the HAProxy configuration for managing the traffic.
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The setup allows for different active and backup configurations within the deployment strategy.
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You configure HAProxy to balance requests accordingly, ensuring availability.
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I’ll revisit the deployment summary soon, and we will review how to ensure smooth transitions.
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At the conclusion, I'll provide important links where you can find more resources on Docker.
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These resources include documentation, tutorials, and further reading to enhance your understanding.
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One key resource is the Docker book by James Turnbull; it is an excellent read for beginners and experienced users alike.
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Lastly, there are several tools available that build on Docker's systems, which can help streamline development and deployment.
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If you have any questions, feel free to reach out to me after the session.
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Thank you very much for your attention!
