Machine Learning APIs with Apache Groovy

At GR8Conf Europe last year, I talked about how to take advantage of the Google Cloud machine learning APIs using Apache Groovy

With Groovy, you can call the Vision API that recognises what's in your pictures, or reads text.
You can invoke the Natural Language API to understand the structure of your text.
With the Speech-To-Text API, you can get transcriptions of what's been said in an audio stream, or with Text-To-Spech, you can also generate human-like voices from your own text. 

With those ready-made APIs, no need to be an expert data scientist! Just call an SDK or a REST API, and you're ready to go.

Here's the video of the presentation:

And here are the slides that I showed:

In a previous article, I also presented one of the sample that I used with the Vision API.

The Call for Paper for the new edition of GR8Conf Europe is still open, so don't miss the opportunity to tell the world about all the cool things you've been doing with Apache Groovy!

Interview InfoQ en français sur les microservices sur Google Cloud Platform

Une fois n'est pas coutume, je vais parler de Google Cloud Platform en français ! Lors de la conférence Voxxed Days Microservices, que j'ai couverte récemment, j'ai eu l'occasion de répondre à une interview pour InfoQ France.

Voici la liste des questions auxquelles j'ai répondues, et je vous laisserai écouter les réponses sur InfoQ France !

  • Pour ceux qui ne te connaissent pas, peux-tu nous dire qui tu es ?
  • Elles sont où les équipes produits ?
  • Et les utilisateurs, en France, il y en a beaucoup ?
  • Pour les néophytes, les microservices, qu'est-ce que c'est ?
  • C'est quoi le "nouveau" par rapport aux architectures dites distribuées, soa, webservices ?
  • On va parler de la platforme cloud de google, où ça en est ?
  • C'est quoi serverless, le retour du mainframe ?
  • Quelles nouveautés ?
  • Et Google vis à vis de java ?
  • C'est quoi les langages que vous poussez le plus ?
  • Le futur des microservices ?

New serverless solutions on Google Cloud for functions, apps and containers

At Voxxed Days Microservices, in Paris, I talked about the latest development in serverless solutions on Google Cloud Platform, to deploy functions, apps and even containers

I answered an interview on the theme of microservices, and how this maps to the Google cloud products.

And the video of my presentation was published on YouTube:

Here's the abstract of the session:

Plenty of novelties in the Serverless offering of Google Cloud Platform, whether you’re developing functions, apps or containers.

Let’s get started with the new modern runtimes for the venerable Google App Engine, sandboxed thanks to the open source gVisor container sandboxing technology. Cloud Functions is now GA with Node.js, but also offers new languages like Python to let you implement your functions. If you need more flexibility, you will also be able to run serverless containers: just dockerize your project and off you go!

But the crux of the show has to be the new open source project, Knative, a collaboration of Google with key vendors like Pivotal, IBM, Red Hat or SAP, which offers a set of portable building blocks on top of Kubernetes to build serverless platforms. Additionally, you will be able to try out Knative on Google Kubernetes Engine thanks to a dedicated add-on.

In this session, we’ll review all the new serverless-related features of Google Cloud Platform with concrete demos, so you can get started easily and rapidly.

Deploy a Micronaut application containerized with Jib to Google Kubernetes Engine

A few weeks ago, I had the chance to be at Devoxx Belgium once again, to meet developers and learn about new things from awesome speakers. Google Cloud Platform had its own booth on the exhibition floor, and the team was running codelabs: 10 laptops were at the disposal of attendees to go through various hands-on tutorials on several GCP products. I took a chance at crafting my own codelab: deploying a Micronaut application, containerized with Jib, to Google Kubernetes Engine.

For the impatient, follow this link:

Note: If you haven't got a GCP account already, know that there's a free trial with $300 of cloud credits to get started.

More information on the tools used:

  • Micronaut is a modern, JVM-based, full-stack framework for building modular, easily testable microservice and serverless applications. Micronaut aims to deliver great startup time, fast throughput, with a minimal memory footprint. Developers can develop with Micronaut in Java, Groovy or Kotlin.
  • Jib is an open source tool that lets you build Docker and OCI images for your Java applications. It is available as plugins for Maven and Gradle, and as a Java library.
  • Kubernetes is an open source project which can run in many different environments, from laptops to high-availability multi-node clusters, from public clouds to on-premise deployments, from virtual machines to bare metal.

In this codelab, you deploy a simple Groovy-based Micronaut microservice to Kubernetes running on Kubernetes Engine. 

The goal of this codelab is for you to run your microservice as a replicated service running on Kubernetes. You take code that you have developed on your machine, turn it into a Docker container image built with Jib, and then run and scale that image on Kubernetes Engine.

An intro to Google Cloud Platform

In a matter of a few years, Google Cloud Platform has evolved from a very small set of products or APIs to a wealth of close to a hundred of products, services and APIs that developers can take advantage of. 

This week, at the event Le Meilleur Dev de France, I gave an introduction to the whole platform, focusing on three key axis: compute, storage and machine learning. After an introduction on famous users of GCP, like Snapchat, Spotify or PokemonGo, I also gave a few examples of big French companies as well as French startups who have decided to go to the cloud with Google.

Later on, over the course of three sections, as I was covering the multiple solutions in each areas (compute / storage / ML), I also tried to give concrete hints as to when to use what, depending on your application needs. Indeed, as many solutions are at your disposal, comes the paradox of choice, as with more options, choice becomes more complicated.

Here are the slides I presented:

© 2012 Guillaume Laforge | The views and opinions expressed here are mine and don't reflect the ones from my employer.