I wanted to track the number of views, and also likes, of some YouTube videos I was featured in. For example, when I present a talk at a conference, often the video becomes available at a later time, and I’m not the owner of the channel or video. At first, I wanted to use the YouTube Data API, but I had the impression that I could only see the stats of videos or channels I own, however I think I might be wrong, and should probably revisit this approach later on.

In this article, let’s revisit the topic of deploying Java apps on Cloud Run. In particular, I’ll deploy a Micronaut app, written with Java 17, and built with Gradle.

With a custom Dockerfile

On Cloud Run, you deploy containerised applications, so you have to decide the way you want to build a container for your application. In a previous article, I showed an example of using your own Dockerfile, which would look as follows with an OpenJDK 17, and enabling preview features of the language:

It’s all Richard Seroter’s fault, I ended up dabbling with Golang! We were chatting about a use case using Google Cloud Workflows and a Cloud Run service implemented in Go. So it was the occasion to play a bit with Go. Well, I still don’t like error handling… But let’s rewind the story a bit!

Workflows is a fully-managed service/API orchestrator on Google Cloud. You can create some advanced business workflows using YAML syntax. I’ve built numerous little projects using it, and blogged about it. I particularly like its ability to pause a workflow execution, creating a callback endpoint that you can call from an external system to resume the execution of the workflow. With callbacks, you’re able to implement human validation steps, for example in an expense report application where a manager validates or rejects an expense from someone in their team (this is what I implemented in this article).

Every year in France, around mid-September, there’s a special weekend where everyone can visit some famous places, usually closed the rest of the year. That’s “Journée du Patrimoine”. For example, you can visit places like the Elysée Palace or the Matignon Palace, if you want to see where the French president, or the French prime minister work. However, for some of those places, it’s tricky to register online to book a slot, as there’s always a high demand for them. Furthermore, you have to be there at the right time to register, and often, you don’t even know when that day or time is! So I thought I could monitor the website of the Elysée Palace to see when the registration would open, by tracking changes on the Elysée website.

Time to spill the beans and show the gems, to our friendly snakes and elephants: we’ve got some great news for Java, Ruby, Python and PHP serverless developers today. Google App Engine and Cloud Functions are adding new modern runtimes, allowing you to update to the major version release trains of those programming languages.

In short, here’s what’s new:

• Access to App Engine legacy bundled services for Java 11/17, Python 3 and Go 1.12+ runtimes, is Generally Available

  Read more...

There are different ways to launch the execution of a workflow. In previous articles, we mentioned that you can use the gcloud command-line tool to create an execution, you can also use the various client libraries to invoke Workflows, or use the REST API. A workflow itself can also invoke other workflows!

But today, I’d like to tell you how to schedule the execution of a workflow. For that purpose, we’ll take advantage of Cloud Scheduler. The documentation is actually covering this topic in detail, so be sure to grab all the info there. However, I’ll go quickly through the steps, and tell you about a nice new feature in the cloud console to ease the scheduling of workflows!

Workflows allows you to call APIs, whether from or hosted on Google Cloud, or any external API in the wild. A few days ago, for example, we saw an example on how to use the SendGrid API to send emails from a workflow. However, in that article, I had the API key hard-coded into my workflow, which is a bad practice. Instead, we can store secrets in Secret Manager. Workflows has a specific connector for Secret Manager, and a useful method to access secrets.

Following up the article on writing and reading JSON files in cloud storage buckets (GCS), we saw that we could access the data of the JSON file, and use it in our workflow. Let’s have a look at a concrete use of this.

Today, we’ll take advantage of this mechanism to avoid hard-coding the URLs of the APIs we call from our workflow. That way, it makes the workflow more portable across environments.

Following up the article on writing and reading JSON files in cloud storage buckets, we saw that we could access the data of the JSON file, and use it in our workflow. Let’s have a look at a concrete use of this.

Today, we’ll take advantage of this mechanism to avoid hard-coding the URLs of the APIs we call from our workflow. That way, it makes the workflow more portable across environments.

At enterprises across industries, documents are at the center of core business processes. Documents store a treasure trove of valuable information whether it’s a company’s invoices, HR documents, tax forms and much more. However, the unstructured nature of documents make them difficult to work with as a data source. We call this “dark data” or unstructured data that businesses collect, process and store but do not utilize for purposes such as analytics, monetization, etc. These documents in pdf or image formats, often trigger complex processes that have historically relied on fragmented technology and manual steps. With compute solutions on Google Cloud and Document AI, you can create seamless integrations and easy to use applications for your users. Document AI is a platform and a family of solutions that help businesses to transform documents into structured data backed by machine learning. In this blog post we’ll walk you through how to use Serverless technology to process documents with Cloud Functions, and with workflows of business processes orchestrating microservices, API calls, and functions, thanks to Workflows.