• Part 1: SSH Tunnel — AWS EC2
• Part 2: Creating an AWS EC2 instance
• Part 3: Fully Managed MongoDB — DocumentDB
• Part 4: Creating an AWS DocumentDB cluster

AWS Released a new service called, DocumentDB. Which allows you to run fully managed MongoDB workloads in minutes. That can scale to 16 instances and 15 read replicas. Madness! 🔥

Amazon DocumentDB is designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and developers can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs).

For more information check out the DocumentDB AWS product page, https://us-west-2.console.aws.amazon.com/docdb.

Why am I excited?

Recently, we’ve been working with a customer who has been running MongoDB on premises along with the rest of their web application. They hired Serverless Guru to help move them from on premises to the cloud.

The project was broken down into three core parts.

1. Moving the Angular Frontend to S3 + CloudFront (HTTPS) with an automated multi-stage/multi-region deployment strategy. Along with a CI/CD to trigger deployments automatically off GitHub pushes to the dev or master branches via Google Cloud Build.
2. Moving the Java Spring Boot APIs to AWS in a scalable, ideally fully managed solution. Version 2, refactoring the codebase away from relying on an active server completely to lambda functions (#serverless).
3. Picking up the MongoDB database and finding a fully managed solution to support the effort. The initial decision was towards MongoDB Atlas. However, DocumentDB has now arrived!

Why DocumentDB over MongoDB Atlas?

Well to be perfectly fair to MongoDB Atlas, we have a lot more experience working in the AWS environment. All though we did become comfortable working with MongoDB Atlas. Atlas did give us some weird behavior. Either way, Atlas was much better than running our own cluster from scratch on AWS or GCP.

Note: We are not long term customers of MongoDB Atlas, your results may vary.