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Thank you for having me today. I will talk about scalable deployments and how we deploy our web application at Cookpad.
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Today, I will focus solely on deployment, so let's dive into that. My name is Shota Fukumori, and I'm from Japan.
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I'm currently one of the youngest Ruby coaches at the age of 17. I've worked hard to gain my parents' approval to be here today, and I want to give them peace of mind about my journey in technology.
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At Cookpad, we're running the largest recipe-sharing website in Japan, and we utilize a significant infrastructure that includes over 120 app servers. Deployments for us need to be efficient and effective.
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We perform deployments of our application many times a day, especially during peak usage times. Our developers need the ability to deploy independently, ideally during working hours.
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Next, let me outline our deployment flow. We utilize a continuous integration approach where we perform build checks. If the build is successful, it will automatically deploy to a staging server before going live.
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In the past, we've used Capistrano combined with SSH to manage our deployments. However, this setup began to create a bottleneck as our server count increased, leading to slower deployments.
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We discovered that our deployments were taking longer than expected. Each deployment could stretch to over 10 minutes, causing frustration among developers who wanted to quickly release changes.
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At one point, the deployment process became a hindrance rather than a help, with developers often waiting for teammates which could result in additional delays.
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Therefore, we needed a faster, more efficient way to handle our deployment process. We started looking for ways to enhance our current toolset.
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This led us to explore how we could build a new deployment tool, which we named Mamiya. With Mamiya, we could greatly accelerate our deployment process.
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Mamiya allows us to achieve deployment times of less than a minute across all our 140 servers, significantly reducing the time developers spend waiting on deploys.
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In exploring Mamiya, we found that using it instead of traditional Capistrano deployments streamlined the entire process, resulting in quicker and more reliable rollouts.
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This tool was developed with considerations for scalability and speed, allowing our team to focus more on coding rather than managing deployment bottlenecks.
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Let me walk you through how Mamiya operates. Essentially, it handles packages that need to be deployed, ensuring that each package goes through stages of preparation before it reaches production.
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Mamiya is configured to handle multiple servers efficiently, and during deployment, it utilizes a structure of master nodes and agents for better distribution of tasks.
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The deployment flow involves several steps, including packaging, preparing the deployment environment, and finally switching over to the new code seamlessly.
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We also ensure that the entire process allows for quick rollbacks if any issues are detected post-deployment. This greatly enhances our confidence when rolling out new features or updates.
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Through implementing these changes, our deployment times have improved drastically, allowing for precise and timely updates without impacting user experience.
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In summary, while Mamiya is still evolving, it addresses many of the persistent problems we faced with our earlier deployment methods.
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The focus now is on continuing to improve this tool further, understanding that the needs of our deployment processes will only grow into the future.
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We hope to keep enhancing Mamiya, continuously adapting it to ensure our deployments remain efficient, safe, and scalable as our service grows.
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Thank you for listening, and I'm excited to see how we can further optimize our deployment processes in the near future.
