deploy-cloud-functions VS dockerfile-rails

One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on.

I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights.

Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment.

Lambda is made for your use case :). It doesn’t have to be AWS there are plenty of other serverless computing services like: - Google cloud functions - Azure functions Etc

Once you have some basic familiarity with programming, try deploying one of your Python programs to the cloud. Start with Cloud Functions, because that doesn't require any knowledge of Linux server administration.

If the customer prefers making REST-like calls: Deploy a simple Cloud Function that the customer would invoke by making a regular HTTP call with some parameters. The Cloud Function would validate the customer's credentials, and then send a query to BigQuery using one of the client libraries. You can write Cloud Functions in Node.js, Python, Go, Java, C#, Ruby, or PHP. You are only charged when the function runs.

Cloud Functions: A serverless platform for event-driven functions

I propose starting with Cloud Functions. You can use your Python experience, you can do rapid prototyping by writing your code in a text-box in the Google Cloud Console, and there will be no server setup or maintenance.

AWS Lambda If you're in Azure, your equivalent service is Azure Functions. For Google, this is Google Functions (yes, AWS just HAD to be different). Regardless of its name, all of these services fulfill the same purpose - a small compute building block to house your business logic code. An AWS Lambda function is simply the code you want to run, written in your language of choice (I preference Python, but Typescript and Java are popular options). In your infrastructure code, you specify some lambda function basics, like name, path to the business logic code, security role, and what runtime you're using, and optionally have the ability to control more parameters like timeout, concurrency, aliases, and more. Lambda even has built in integrations to other AWS services, such as S3 and SQS (we'll get to these) to make application development even easier. Additionally, lambda functions are priced based on the number of times they're invoked and the duration of time they run, making them exceptionally affordable.

If you want to automatically generate Dockerfiles for more versions of Rails (not just the latest) that detect OS packages that need to be installed from gems present in your Gemfile, check out https://github.com/fly-apps/dockerfile-rails

You can install it in your rails app by running:

1. bundle add dockerfile-rails

2. rails g dockerfile

> I felt bad

Don't. I can honestly say that I didn't write this post targeting HN. I'll go further... this post wasn't meant for people who are unlikely to use https://github.com/fly-apps/dockerfile-rails#overview. I recently added some features to that gem whose usage may not be intuitively obvious. I wrote this post to explain some of the motivation for those features.

I don't know how to mark posts as not intended for HN (and truth be told, if there was such a feature, I'd be inclined to overuse it). I don't know where else I should have posted this content, but I'm not sure I would be inclined to move it. In any case, this post, as written, serves a purpose for me. Somebody not you and not me felt it belonged here. We can both second guess that decision. Either way, there is no reason for either of us to feel bad.

Did you try migrating with this guide? https://fly.io/docs/rails/getting-started/migrate-from-herok...

The issues you ran into with older versions of Rails was probably because the Dockerfile that `fly launch` generated was for new versions of Rails. We switched to https://github.com/rubys/dockerfile-rails to streamline Dockerfile generation and support older versions of Rails.

If you try it again and run into issues you can open an issue at https://github.com/rubys/dockerfile-rails/issues or post in https://community.fly.io and somebody will help get that sorted out.

The more versions of Rails we can deploy the better!

At the moment Rails is focused on simplicity/readability. I've got a gem that I'm proposing (and DHH is evaluating) that adds caching as an option: https://github.com/rubys/dockerfile-rails#overview

even though the article does not go deep into multistage builds Fly.io does provide cookbooks and even a link to a Rails generator there.