Jump to Content
Google Cloud

A better way to bootstrap MongoDB on Google Cloud Platform

June 21, 2016
Sandeep Parikh

Cloud Native Advocate

We like to think that Google Cloud Platform is one of the best places to run high-performance, highly-available database deployments and MongoDB is no exception. In particular, with an array of standard and customizable machine types, blazing fast persistent disks and a high performance global network, Google Compute Engine is a great option for MongoDB deployments, which can then be combined with managed big data services like Google BigQuery, Cloud Dataproc and Cloud Dataflow to support all manner of modern data workloads.

There are a number of ways to deploy MongoDB on Cloud Platform, including (but not limited to):

  • Creating Compute Engine instances and manually installing/configuring MongoDB
  • Using Google Cloud Launcher to quickly create and test drive a MongoDB replica set
  • Provisioning Compute Engine instances and using MongoDB Cloud Manager to install, configure and manage MongoDB deployments
Today we’re taking things one step further and introducing updated documentation and Cloud Deployment Manager templates to bootstrap MongoDB deployments using MongoDB Cloud Manager. Using the templates, you can quickly deploy multiple Compute Engine instances, each with an attached persistent SSD, that will download and install the MongoDB Cloud Manager agent on startup. Once the setup process is complete, you can head over to MongoDB Cloud Manager and deploy, upgrade and manage your cluster easily from a single interface.

https://storage.googleapis.com/gweb-cloudblog-publish/images/using-mongodb-1zrqn.max-600x600.PNG

By default, the Deployment Manager templates are set to launch three Compute Engine instances for a replica set, but they could just as easily be updated to launch more instances if you’re interested in deploying a sharded cluster.

Check out the documentation and sample templates to get started deploying MongoDB on Cloud Platform. Feedback is welcome and appreciated; comment here, submit a pull request, create an issue or find me on Twitter @crcsmnky and let me know how I can help.

Posted in