Next, create a project in Wing Pro with New Project in the Project menu and selecting SDK for Python and verify that it is working by starting it outside of Wing and testing it I'd go with Cloud Run.Ĭloud functions are also great but they force you writing web applications in a way that I don't like.īut I do love using Cloud Functions for event-based systems, data ingestion or pipeline based on events.Before trying to configure a project in Wing Pro, first install and set up Google App Engine They are also well integrated with the Stackdriver products (now Operations), that means you get centralized log and monitoring out of the box.Īnd yes, you can use structlog and get you json logs parsed, just remember to convert level to severity ( check this snippet).Īpp Engine and Cloud Run both support traffic splitting between different revisions, so you get A/B testing or canary deployment for free. The lock-in factor is also pretty low, especially for App Engine and Cloud Run.īeing full-fledged applications you can pack them into containers and run them somewhere else. Serverless VPC access is really neat, you can build complex topology on serverless stack, like mixing virtual machines and serverless applications inside the same network. They all support private VPC connections through Serverless VPC access. You need to be careful if you access services where the number of concurrent clients is limited, a good example is services connecting to PostgreSQLĪpp Engine, Cloud Run and Cloud functions all come with a pretty good free tier and you pay only when you use them.You can't create shiny network topologies and decide how requests are routed, you need to build on top of the GCP integrations (and limits).Headers and Payload size are also limited.Websockets, GraphQL subscriptions and streaming are limited by the request timeout.No, leaving cost aside there are certain things you can't do or can't do well: In my case I decided to use the GCP Build service and push the image to the GCP Container registry.Īfter you cloned the repository you can run this commandĪgain really nice results. It can be a publicly available image, or an image hosted on the GCP Container Registry. To deploy an application on top of Cloud Run you only need a docker image that can be pulled by the Cloud Run service. In case you want to play with Cloud Run you can find (another) runnable example. You are not limited by the supported languages or versions.One single instance can handle multiple requests at the same time.That means you can run Cloud Run on your GKE cluster or on a cluster managed directly by Google.Ĭloud Run offers a few pluses compared to App Engine and Cloud Functions: The entrypoint is the command that you want to run (like web in a Heroku procfile).Ĭloud Run is a recent new addition to the serverless GCP suite, it uses knative to run serverless workloads on top of a Kubernetes cluster. The app.yaml needs at least two entries: runtime and entrypoint.Īpp Engine supports both Python 3.7 and Python 3.8, so you can select the runtime you want to use. I use Poetry as dependency management tool and I export the requirements as requirements.txt.There's a repository with a runnable example, with a few things to notice: You need an app.yaml, a requirements.txt and then you are ready to go. If you are a fan of Heroku, App Engine is the closest experience you can get inside GCP. Gcloud config configurations create Īpp Engine has two versions, standard and flexible environment, here we are focusing on the standard version. # You can use whatever you like for CONFIGURATION-NAME You need to configure the gcloud sdk, these are the magic lines you need to run:.We are going to use the gcloud sdk, so it's better to have it setup properly: It can scale up and down (to zero instances/functions) automagicallyīefore starting: configure the gcloud sdk.You pay (almost) zero if you don't receive any request.You don't need to pre-allocate resources (like number of machines). What does serverless mean in this context? There are 5 different ways in which you can deploy a Python application on GCP:Īpp Engine, Cloud Functions and Cloud Run are 3 different ways to deploy serverless workloads on GCP. Let's focus on the serverless offer and discover how you can run Python serverless applications on top of GCP. It really helps you focus on what matters, whether you are building an MVPs, a data ingestion pipeline, a single function or full-fledged style application. I've used the Google Cloud Platform extensively in the last years and, as a cloud platform, is one of the most enjoyable you can work with.
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