Local Development with the MongoDB Atlas CLI and Docker

Need a consistent development and deployment experience as developers work across teams and use different machines for their daily tasks? That is where Docker has you covered with containers. A common experience might include running a local version of MongoDB Community in a container and an application in another container. This strategy works for some organizations, but what if you want to leverage all the benefits that come with MongoDB Atlas in addition to a container strategy for your application development?

In this tutorial we’ll see how to create a MongoDB-compatible web application, bundle it into a container with Docker, and manage creation as well as destruction for MongoDB Atlas with the Atlas CLI during container deployment.

Get Hyped: Using Docker + Go with MongoDB

In the developer community, ensuring your projects run accurately regardless of the environment can be a pain. Whether it’s trying to recreate a demo from an online tutorial or working on a code review, hearing the words, “Well, it works on my machine…” can be frustrating. Instead of spending hours debugging, we want to introduce you to a platform that will change your developer experience: Docker.

Docker is a great tool to learn because it provides developers with the ability for their applications to be used easily between environments, and it’s resource-efficient in comparison to virtual machines. This tutorial will gently guide you through how to navigate Docker, along with how to integrate Go on the platform. We will be using this project to connect to our previously built MongoDB Atlas Search Cluster made for using Synonyms in Atlas Search. Stay tuned for a fun read on how to learn all the above while also expanding your Gen-Z slang knowledge from our synonyms cluster. Get hyped!

TPDP Episode #33: Containers, Virtual Machines, and Orchestration, Part 1

I’m pleased to announce that Containers, Virtual Machines, and Orchestration has been published to all of the popular podcast networks. This is the 33rd episode of the show and the first two-part episode to make an appearance.

This episode features Marek Sadowski from IBM and dives into the DevOps space, focusing particularly on deployment strategies such as virtual machines and containers, and how to orchestrate potentially massive amounts of them in an efficient and automated fashion.

If you’re not quite comfortable with Docker, virtual machines, Kubernetes (K8s), and similar, this is an episode you should listen to, since all are very relevant and necessary skills for developers.

Fix GLIBCXX Errors From Serverless Framework And AWS Lambda

While I haven’t done too much with Serverless Framework and Functions as a Service (Faas) recently, I did in the past and it isn’t something that I’ve forgotten. In the past I demonstrated how to deploy Node.js functions to Amazon Web Services (AWS) Lambda that contain native dependencies. While not a necessity for all Lambda functions, it is for functions that use libraries for specific operating systems and architectures. For example, my previous article titled, Use AWS Lambda and API Gateway with Node.js and Couchbase NoSQL, fell into this situation. Making use of an EC2 instance or a Docker container with Amazon Linux will help most of the time, but there are scenarios where a little bit extra must be done to accomplish the task.

In certain circumstances everything may package and deploy correctly, but still throw errors. For example, a common error is around libstdc++ and a version of GLIBCXX not being found.

In this tutorial we’re going to see how to resolve library errors that might not be caught in a typical packaging and deployment scenario with Serverless Framework and AWS Lambda.

Getting Started With MongoDB As A Docker Container Deployment

MongoDB is one of the most popular NoSQL databases on the market right now and is used heavily with Node.js development in particular. So what if you wanted to give MongoDB a spin and see what it’s all about?

There are plenty of deployment options when it comes to using MongoDB. For example, I had recently written a tutorial titled, Developing a RESTful API with Node.js and MongoDB Atlas which focused on the MongoDB cloud solution called Atlas. However, you can also install MongoDB on premise using multiple options.

In this tutorial we’re going to focus on using Docker to deploy MongoDB as a container and interact with it with the shell client.

Continuous Integration With GitLab CI And Docker Using A Raspberry Pi

I know I’ve mentioned this before, but I’ve recently started to get serious about my content production and deployment approach on The Polyglot Developer. My goal is to be able to write my tutorials in Markdown, push to GitLab, and have it automatically deployed as a Docker container on my production server. Being able to automate things and take advantage of Docker will definitely improve my productivity in the long term.

So I’ve been playing around with tools on the subject, more specifically GitLab, because that is what I’m using to save a history of the blog. GitLab is a source code repository, but also a whole lot more given its ability to do continuous integration, continuous deployment, and work with Docker directly.

We’re going to take a look at installing GitLab and Docker on a Raspberry Pi, then configuring a GitLab CI Runner to take control of our continuous integration process every time we push some code. While it might sound easy, there are some certain things that aren’t so obvious in the setup and configuration.

Serve Your Web Applications With Minimal Effort Using Caddy

I’ve been in the web game for quite some time and have my fair share of web server software. I’ve used Microsoft’s Internet Information Services (IIS), Apache httpd, as well as NGINX, and while they all thrive in their own ways, they’ve been overkill for most of my use cases. This is where Caddy comes in, a lightweight alternative to these seasoned, but often heavy web servers.

We’re going to see how to use Caddy and learn why it is so powerful while using minimal effort on a developer operations side.