Verdaccio VS Google Cloud Functions

Another option is to publish our package is with azure artifacts, npm with free version public. But if we want to make it private, we need to pay or set up our own private npm repository. In this moment is where Verdaccio comes in to help us. - Source: dev.to / about 1 month ago

And finally, we extracted our own Verdaccio setup that we've been using to run our e2e tests in the Nx repo s.t. You can use it for your own plugin development as well. Check out this video for a walkthrough on how this works. - Source: dev.to / 5 months ago

A local install of Verdaccio running next to our app. - Source: dev.to / 8 months ago

You may want to look into setting up a “Private NPM Registry”. My company maintains 5-6 apps and have many shared libraries just like you describe. We use Verdaccio. I don’t know our costs. Source: 11 months ago

All my source code is in GitHub, I run my own private NPM Registry (Verdaccio) for my private packages and it also acts as a cache, and I use pnpm instead of npm. Source: 11 months ago

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. - Source: dev.to / 5 months ago

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. Source: 7 months ago

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. - Source: dev.to / 9 months ago

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. Source: 11 months ago

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. Source: 12 months ago