The schedule for Google Cloud Next was unveiled this week, and there’s lots of interesting sessions to attend. With the many parallel tracks, it’s difficult to make a choice, but I wanted to highlight some of the talks I’d like to watch!

The Google Cloud Platform is a pretty rich one, with many options for your compute needs. How do you choose which one is best for your use case? Brian Dorsey covers this in detail in this session:

The purpose of this article is to deploy a Ratpack web application on Google App Engine Flex.

For my demos at conferences, I often use frameworks like Ratpack, Grails or Gaelyk, which are based on the Apache Groovy programming language. In a previous article, I already used Ratpack, but on a slightly more complex use case, but this time, I want to share a quick Ratpack hello world, and deploy it on Flex.

I started with a hello world template generated by Lazybones (a simple project creation tool that uses packaged project templates), that I had installed with SDKman (a tool for managing parallel versions of multiple Software Development Kits). But you can go ahead with your own Ratpack apps obviously. Feel free to skip the next section if you already have an app.

The GA release of Cloud Natural Language API is easier to use, better at recognizing language nuances and adds additional support for Spanish and Japanese

Earlier in November, we announced general availability for the Cloud Natural Language API and highlighted the key new improvements. This launch included many additions to the API like expanded entity recognition, granular sentiment analysis with expanded language support, improved syntax analysis with additional morphologies and more.

Many of these improvements were the result of feedback from beta users, so thank you for your contributions! But concretely, what do these updates mean? Let’s take a closer look.

All sorts of voice-powered assistants are available today, and chat bots are the new black! In order to illustrate how such tools are made, I decided to create my own little basic conference assistant, using Google’s Cloud Speech API and Cloud Natural Language API. This is a demo I actually created for the Devoxx 2016 keynote, when Stephan Janssen invited me on stage to speak about Machine Learning. And to make this demo more fun, I implemented it with a shell script, some curl calls, plus some other handy command-line tools.

Gradle is becoming the build automation solution of choice among developers, in particular in the Java ecosystem. With the Github archive published as a Google BigQuery dataset, it’s possible to analyze those build files, and see if we can learn something interesting about them!

This week, I was at the G3 Summit conference, and presented about this topic: I covered the Apache Groovy language, as per my previous article, but I expanded my queries to also look at Grails applications, and Gradle build files. So let’s see what the dataset tells us about Gradle!

Probably for vanity sake, or perhaps even out of jealousy seeing friends becoming “twitter verified”, I was curious to see if, me too, I could get those little ticks beside my name on my Twitter profile.

Generally speaking, verified accounts are accounts of “public interest”. It can range from your usual movie stars, to politicians, from well-known artists, to company CEOs, but also persons somehow well known in the twittosphere, including tech luminaries, representative of particular tech communities, etc. So, seeing my tech friends getting the little tick, I thought I should try that out.

When you’re following a project, a company, a platform, you’re looking for the latest news, about the latest feature announcement, to take advantage of what’s coming up.

Last time, I blogged about the gcloud command line tool, which nicely shows you the latest updates since the last time you updated its components.

If you go to the Google Cloud Platform website, you’ll see dedicated release notes pages for pretty much all products. For example, here are the release notes for:

As I was working on a demo for one of my talks at Devoxx, I was encountering a bug in my Groovy code (a Gaelyk app using Glide). I had deployed a new version of my App Engine app, changing some code to persist some data in the Datastore. After those changes, I saw a trace in the logs:

Looks like there’s an error in receiveTweet.groovy on line 11. And there’s a link! Although I hadn’t linked the source code to the application, I was surprised to see this link. But I knew that Stackdriver is able to pick up sources in different ways (from uploaded local files, from a Google code source repository, from Github or BitBucket, or with a “source capture”).

How do you filter access to your VMs on Google Cloud Platform? During a discussion with a customer, I was asked this question: only certain IP addresses or a range of IP addresses should have access to a particular VM. Let’s see that in action!

Let’s assume you already have an account on Google Cloud Platform, but if you don’t, don’t miss the $300 credits for a free trial! I created a new project, then navigated to the Compute Engine section to create a new VM instance. I used all the default parameters, except that I checked the checkbox for “Allow HTTP traffic”, at the bottom of the following screenshot:

I was playing with the new IntelliJ IDEA plugin for Google App Engine yesterday. The plugin depends on the gcloud SDK to do its work. And I started exploring gcloud a little bit more.

I was experiencing some odd bug which prevented me to run my application locally with the App Engine’s local app server. It was a bug which was present in an old version of gcloud and its App Engine component, so I had to update the SDK and its App Engine Java component to fix it. No big deal, but what I wanted to highlight here was a little detail about that upgrade process.