Posts

Just before heading to Google Cloud Next, I was notified I was listed 4th in JAX London’s Top 20 Java influencers of 2018 on social media! It’s an honor to be listed among famous figures like Josh Bloch, Brian Goetze, Martin Thompson, Arun Gupta, Jessica Kerr, Mario Fusco, Josh Long, Venkat Subramanian, Charles Nutter and many others. You can see the full list of the top influencers here.

Powerful machine learning APIs are at your fingertips if you’re developing with Google Cloud Platform, as client libraries are available for various programming languages. Today, we’re investigating the Cloud Vision API and its Java SDK, using the Apache Groovy programming language—a multi-faceted language for the Java platform that aims to improve developer productivity thanks to a concise, familiar and easy to learn syntax.

At GR8Conf Europe, in Denmark, the conference dedicated to the Apache Groovy ecosystem, I spoke about the machine learning APIs provided by Google Cloud Platform: Vision, Natural Language, Translate, and Speech (both recognition and synthesis). Since it’s a groovy conference, we presented samples and demos using a pretty Groovy language. I wanted to share the underlying examples with a wider audience, so here’s the first of a series of blog posts covering the demos I presented. I’ll start with the Google Cloud Vision API, and I will cover the other APIs in future posts.

On the Google Cloud front today, the big news is the release of the new Node.JS 8 runtime for Google App Engine Standard. It’s been a while since a completely new runtime was added to the list of supported platforms (Python, Java, PHP, Go). You could already run anything in custom containers on App Engine Flex, including your own containerized Node app, but now you can have all the nice developer experience on the Standard environment, with fast deployment times, and 0 to 1 to n instance automatic scaling (you can see the difference between those two environments here).

Last week at GR8Conf Europe, I spoke about the machine learning APIs provided by  Google Cloud Platform: Vision, Natural Language, Speech recognition and synthesis, etc. Since it’s GR8Conf, that means showing samples and demos using a pretty Groovy language, and I promised to share my code afterwards. So here’s a series of blog posts covering the demos I’ve presented. We’ll start with the Vision API.

The Vision API allows you to:

• Get labels of what appears in your pictures,
• Detect faces, with precise location of face features,
• Tell you if the picture is a particular landmark,
• Check for inappropriate content,
• Give you some image attributes information,
• Find if the picture is already available on the net,
• Detects brand logos,
• Or extract text that appears in your images (OCR).

You can try out those features online directly from the Cloud Vision API product page:

The venerable Google App Engine platform celebrated its 10th anniversary!

Back in 2008, it started with Python, as its first runtime, but I got way more interested in App Engine when the Java runtime would launch the following year. It’s a bit of a special story for me, as I’ve always been a fan of App Engine, since the beginning.

Over the years, I’ve built several apps running on App Engine. For instance, this blog you’re reading now is running on App Engine, as well as my personal picture / video sharing app, some Github post-commit webhook for the Apache Groovy project, or the Groovy Web Console to share / edit / run Groovy scripts in the cloud.

The Java Champions recently nominated me to become a Java Champion!

Please welcome the new Java Champions. @antoine_sd @javajudd @glaforge @kenkousen @kito99 @vlad_mihalcea
@leomrlima @net0pyr @shelajev @rgransberger @rmehmandarov  @Sander_Mak @SeanMiPhillips Well done to all of you @OracleDevs @java #odevcommunity pic.twitter.com/X9yeek641s

— Java Champions (@Java_Champions) November 22, 2017

There’s also a post on the Java Champions’ blog, and InfoQ also echoed the new nominees recently.

I’m super happy and proud of this nomination, and I’m looking forward to continuing being involved in the Java ecosystem, present at Java-friendly conferences, contribute to Open Source projects using Java and Apache Groovy, and write articles here and there using my favorite languages.

A few weeks ago, I’ve started a new blog dedicated to Google Cloud Platform, to share tips’n tricks I come across while exploring the platform, getting to know new products, or gathered through experience with a particular service I’ve been using:

https://googlecloud.tips/

With the holidays season, I went with a “2018 countdown” approach (like an “advent calendar” without the religious connotation), where I publish a tip every day of the month of December.

Once in a while, when talking about Gradle with developers, at conferences or within the Groovy community (but with the wider Java community as well), I hear questions about Gradle. In particular Gradle vs Maven, or whether developers adopt the Kotlin DSL for Gradle builds.

In the past, I blogged several times about using BigQuery and the Github dataset to analyze open source projects hosted on Github, by running some SQL queries against that dataset. You might want to have a look at this past article on some Gradle analysis with BigQuery. Considering those questions popped up recently, I decided to do a quick run through those questions with some simple queries.

In my timeline, I saw a tweet from Joe Walnes about the built-in HTTP server available in the JDK since Java 6. It’s super convenient, starts super fast, easy to use, but I often forget about it. I’d probably not use it for serving planet-wide load, but it’s very useful when you need to create a quick service, a little mock for testing some web or micro-service.

Here’s a little hello world for the fun.

Today, there were some interesting announcements for Actions on Google, for building your conversational interfaces for the Google Assistant. Among the great news, one item particularly caught my attention: the improved SSML support: