The first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / about 1 month ago

The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / about 1 month 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 / 7 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: 8 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 / 11 months ago

It is hard to imagine any big and complex Rails project without background jobs processing. There are many gems for this task: **Delayed Job, Sidekiq, Resque, SuckerPunch** and more. And Active Job has arrived here to rule them all. - Source: dev.to / 20 days ago

Rollbar is a great error-tracking service. It alerts us on exceptions and errors, provides analysis tools and dashboard, so we can see, reproduce, and fix bugs quickly when something went wrong. This service has a possibility to log not only uncaught exceptions but any messages. By default, the messages are reported synchronously, but you can enable asynchronous reporting using Sidekiq, girl_friday, or Resque.... - Source: dev.to / 22 days ago

You can use a background job queue like Resque to scrape and process data in the background, and a scheduler like resque-scheduler to schedule jobs to run your scraper periodically. Source: about 2 years ago

So how do we trigger such a long-running process from a Rails request? The first option that comes to mind is a background job run by some of the queuing back-ends such as Sidekiq, Resque or DelayedJob, possibly governed by ActiveJob. While this would surely work, the problem with all these solutions is that they usually have a limited number of workers available on the server and we didn’t want to potentially... - Source: dev.to / about 2 years ago

Background jobs are another limitation. Since only the Aha! Web service runs in a dynamic staging, the host environment's workers would process any Resque jobs that were sent to the shared Redis instance. If your branch hadn't updated any background-able methods, this would be no big deal. But if you were hoping to test changes to these methods, you would be out of luck. - Source: dev.to / about 2 years ago