Modern Distributed App Deployment with Kubernetes & MongoDB Atlas

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Storytelling is one of the parts of being a Developer Advocate that I enjoy. Sometimes the stories are about the special moments when the team comes together to keep a system running or build it faster. But there are less than glorious tales to be told about the software deployments I’ve been involved in. And for situations where we needed to deploy several times a day, now we are talking nightmares.

For some time, I worked at a company that believed that deploying to production several times a day was ideal for project velocity. Our team was working to ensure that advertising software across our media platform was always being updated and released. One of the issues was a lack of real automation in the process of applying new code to our application servers.

What both ops and development teams had in common was a desire for improved ease and agility around application and configuration deployments. In this article, I’ll present some of my experiences and cover how MongoDB Atlas and Kubernetes can be leveraged together to simplify the process of deploying and managing applications and their underlying dependencies.

Let’s talk about how a typical software deployment unfolded:

The developer would send in a ticket asking for the deployment
The developer and I would agree upon a time to deploy the latest software revision
We would modify an existing bash script with the appropriate git repository version info
We’d need to manually back up the old deployment
We’d need to manually create a backup of our current database
We’d watch the bash script perform this “Deploy” on about six servers in parallel
Wave a dead chicken over my keyboard

Some of these deployments would fail, requiring a return to the previous version of the application code. This process to “rollback” to a prior version would involve me manually copying the repository to the older version, performing manual database restores, and finally confirming with the team that used this system that all was working properly. It was a real mess and I really wasn’t in a position to change it.

I eventually moved into a position which gave me greater visibility into what other teams of developers, specifically those in the open source space, were doing for software deployments. I noticed that — surprise! — people were no longer interested in doing the same work over and over again.

Developers and their supporting ops teams have been given keys to a whole new world in the last few years by utilizing containers and automation platforms. Rather than doing manual work required to produce the environment that your app will live in, you can deploy applications quickly thanks to tools like Kubernetes.

What’s Kubernetes?

Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. Kubernetes can help reduce the amount of work your team will have to do when deploying your application. Along with MongoDB Atlas, you can build scalable and resilient applications that stand up to high traffic or can easily be scaled down to reduce costs. Kubernetes runs just about anywhere and can use almost any infrastructure. If you’re using a public cloud, a hybrid cloud or even a bare metal solution, you can leverage Kubernetes to quickly deploy and scale your applications.

The Google Kubernetes Engine is built into the Google Cloud Platform and helps you quickly deploy your containerized applications.

For the purposes of this tutorial, I will upload our image to GCP and then deploy to a Kubernetes cluster so I can quickly scale up or down our application as needed. When I create new versions of our app or make incremental changes, I can simply create a new image and deploy again with Kubernetes.

Why Atlas with Kubernetes?

By using these tools together for your MongoDB Application, you can quickly produce and deploy applications without worrying much about infrastructure management. Atlas provides you with a persistent data-store for your application data without the need to manage the actual database software, replication, upgrades, or monitoring. All of these features are delivered out of the box, allowing you to build and then deploy quickly.

In this tutorial, I will build a MongoDB Atlas cluster where our data will live for a simple Node.js application. I will then turn the app and configuration data for Atlas into a container-ready image with Docker.

MongoDB Atlas is available across most regions on GCP so no matter where your application lives, you can keep your data close by (or distributed) across the cloud.

Figure 1: MongoDB Atlas runs in most GCP regions


To follow along with this tutorial, users will need some of the following requirements to get started:

Google Cloud Platform Account (billing enabled or credits)
MongoDB Atlas Account (M10+ dedicated cluster)

First, I will download the repository for the code I will use. In this case, it’s a basic record keeping app using MongoDB, Express, React, and Node (MERN).

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