Choosing the right compute option in GCP: a decision tree
When you start a new project on Google Cloud Platform (GCP), one of earliest decisions you make is which computing service to use: Google Compute Engine, Google Container Engine, App Engine or even Google Cloud Functions and Firebase.
GCP offers a range of compute services that go from giving users full control (i.e., Compute Engine) to highly-abstracted (i.e., Firebase and Cloud Functions), letting Google take care of more and more of the management and operations along the way.
Here’s how many long-time readers of our blog think about GCP compute options. If you're used to managing VMs and want a similar experience in the cloud, pick Compute Engine. If you use containers and need to coordinate more than one container in your solution, you can abstract away some of the necessary management overhead by using Container Engine. If you want to focus on your code and avoid the infrastructure pieces entirely, use App Engine. Finally, if you want to focus purely on code and build microservices that expose API endpoints for your applications, use Firebase and Cloud Functions.
Over the years, you've told us that this model works great if you have no constraints, but can be challenging if you do. We’ve heard your feedback and propose another way to choose your compute options using a constraint-based set of questions. (It should go without saying that we’re considering very small aspects of your project.)
3. Does your solution already exist somewhere else? Does it include licensed software? Does it require anything other than HTTP/S? If you answered “no,” App Engine is worth a look. App Engine is a serverless solution that runs your code on our infrastructure and charges you only for what you use. We scale it up or down for you depending on demand. In addition, App Engine has access to all the Google SDKs available so you can take advantage of the full Google Cloud ecosystem.
4. Are you looking to build a container-based system? Do you require orchestration? If you're building a multi-container solution, orchestration becomes a consideration. Container orchestration is service that handles deployment, redundancy and load distribution of your containers. One of the most mature, and popular, orchestrators is Kubernetes. If you're considering using Kubernetes on GCP, you should just use Container Engine. (You should think about it wherever you're going to run Kubernetes actually.) Container Engine reduces building a Kubernetes solution to a single click. Additionally, it auto-scales Kubernetes cluster members, allowing you to build Kubernetes solutions that grow and shrink based on demand.
5. Are you looking to use GPUs in your solution? Are you building a non-Kubernetes container-based solution? Are you migrating an existing on-prem solution to the cloud? Are you using licensed software? Do you need a custom kernel or arbitrary OS? Have you not found another solution to meet your needs? If you answered “yes” to any of these questions, you’re probably going to need to run your solution on virtual machines on Compute Engine. Compute Engine is our most flexible computing product, and allows you the most freedom to configure and manage your VMs however you like.
Put all of these questions together and you get the following flowchart:
This is by no means a comprehensive decision tree, and each one of our products supports a wider range of use cases than is presented here. But this should be a good guide to get you started.