Google Cloud Functions VS Azure Functions

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

This article shows with the simple example how to manage Java-based serverless APIs build with Azure functions. It uses azure-functions plugin to integrate Apache APISIX API Gateway with Azure Serverless Function that invokes the HTTP trigger functions and return the response from Azure Cloud. - Source: dev.to / over 1 year ago

GitHub Actions for Azure: This GitHub Action allows developers to automate tasks on the Microsoft Azure platform. With this action, developers can easily integrate Azure services into their workflows, such as Azure Functions, App Services, and Kubernetes. This can help streamline DevOps workflows by automating tasks such as deployment, testing, and scaling on the Azure platform. - Source: dev.to / over 1 year ago

NoOps is best suited for born-in-the-cloud environments that leverage PaaS and serverless solutions. Microservices and API-based application architectures fit the bill perfectly, as they offer fine-grained modularity along with automation. Leading cloud service providers like AWS, Azure, and GCP have a laser focus on providing more services and capabilities in PaaS and serverless, which would help accelerate the... - Source: dev.to / almost 3 years ago