Google Cloud Platform

Cloud Code has been providing IDE support for the development cycle of Kubernetes and Cloud Run applications for a while now. I’m happy to report that the Dec 2022 version (1.21.0) of Cloud Code now supports Cloud Functions!

In this first release of Cloud Functions support, you can:

• Use the Cloud Functions Explorer to view your project’s Cloud Functions properties and source code.
• Download your Cloud Functions to edit your code locally, then configure your local workspace to deploy those changes directly from Cloud Code.
• Invoke your HTTP-triggered functions from VS Code.
• Use the Cloud Code Logs Viewer to view logs from your Cloud Functions.

Let’s take a closer look.

This is a three-part series of posts, in which we summarize Workflows and service orchestration patterns. In this third and final post, we talk about managing workflow life cycles and the benefits of using Firestore with Workflows.

If you’re not careful, the workflow definitions you create with YAML or JSON can get out of hand pretty quickly. While it is possible to use subworkflows to define snippets of a workflow that can be reused from multiple workflows, Workflows does not support importing these subworkflows. Thankfully, there are other tools, such as Terraform, that can help.

This is part 2 of a three-part series of posts, in which we summarize Workflows and service orchestration patterns. You can apply these patterns to better take advantage of Workflows and service orchestration on Google Cloud.

In the first post, we introduced some general tips and tricks, as well as patterns for event-driven orchestrations, parallel steps, and connectors. This second post covers more advanced patterns.

Let’s dive in!

Design for resiliency with retries and the saga pattern It’s easy to put together a workflow that chains a series of services, especially if you assume that those services will never fail. This is a common distributed systems fallacy, however, because of course a service will fail at some point. The workflow step calling that service will fail, and then the whole workflow will fail. This is not what you want to see in a resilient architecture. Thankfully, Workflows has building blocks to handle both transient and permanent service failures.

For the last couple of years, we’ve been using Workflows, Google Cloud’s service orchestrator, to bring order to our serverless microservices architectures. As we used and gained more experience with Workflows and service orchestration, we shared what he had learned in conference talks, blog posts, samples, and tutorials. Along the way, some common patterns and best practices emerged.

To help you take better advantage of Workflows and service orchestration on Google Cloud, we’ve summarized these proven patterns and best practices in a three-part series of blog posts.

.NET 7 was released a few days ago with new features and performance improvements and it’s already supported on Cloud Run on Google Cloud!

In this short blog post, I show you how to deploy a .NET 7 web app to Cloud Run.

Create a .NET 7 web app

First, make sure you’re on .NET 7:

dotnet --version
7.0.100

Create a simple web app:

In a previous post, I showed how to manage the lifecycle of a virtual machine using Workflows and the Compute Engine connector. This works well when there’s a connector for the resource you’re trying to manage. When there is no connector, you can try to use the API of the resource from Workflows, if there’s one. Alternatively, you can also use my favorite command line tool to manage the resource: gcloud. Or if you’re managing a Kubernetes cluster, maybe you want to call kubectl instead.

I’ve been writing a series of posts to showcase Google Workspace and Google Cloud Workflows integration.

In my first post, I showed an IT automation use case in which a Google Sheets spreadsheet triggers a workflow to create virtual machines in Google Cloud. In the second post, I showed how to feed a Google Sheets spreadsheet with data from BigQuery using a workflow.

In this third and final post of the series, I show how to design a workflow that pauses and waits for human approvals from Google Sheets.

Back in August, we announced the 2nd generation of Cloud Functions with longer request processing times, larger instances, new event sources with Eventarc, and more.

A few weeks ago, .NET 6 support (public preview) was silently added to Cloud Functions.

Let’s see how to deploy some .NET 6 functions to Cloud Functions 2nd gen.

Functions Framework for .NET

Functions Framework for .NET is the easiest way to create .NET functions for consuming HTTP or CloudEvent requests.

In my previous post, I showed how to trigger a workflow in Google Cloud from a Google Sheets spreadsheet using Apps Script. In this post, I show how to do the reverse: write to Google Sheets from a workflow in Google Cloud.

Use case

Imagine you have some dataset in BigQuery. Periodically, you want to query and extract a subset of the dataset and save it to a Google Sheets spreadsheet. You can implement such a process with Workflows quite easily.

In a previous post, I showed how to use a GitOps approach to manage the deployment lifecycle of a service orchestration. This approach makes it easy to deploy changes to a workflow in a staging environment, run tests against it, and gradually roll out these changes to the production environment.

While GitOps helps to manage the deployment lifecycle, it’s not enough. Sometimes, you need to make changes to the workflow before deploying to different environments. You need to design workflows with multiple environments in mind.