With my partner in crime, Mete Atamel, we ran two editions of our “Pic-a-Daily” serverless workshop. It’s an online, hands-on, workshop, where developers get their hands on the the serverless products  provided by Google Cloud Platform:

• Cloud Functions — to develop and run functions, small units of logic glue, to react to events of your cloud projects and services
• App Engine — to deploy web apps, for web frontends, or API backends
• Cloud Run — to deploy and scale containerised services

Requirements:

• an existing Google Cloud Platform account and project
• Cloud Functions should be enabled for that project

Compared to the previous tip when using Exress’ request path attribute, we can take advantage of Express routing.

So to support the following paths:

https://us-central1-myproject.cloudfunctions.net/api/customers
https://us-central1-myproject.cloudfunctions.net/api/customers/32
https://us-central1-myproject.cloudfunctions.net/api/customers/32/address

We can have our functions require Express by adding Express in package.json:

{
  "name": "mini-api-router",
  "version": "0.0.1",
  "dependencies": {
    "express": "^4.17.1"
  }
}

Then we can require that dependency in our new functions script:

Requirements:

• an existing Google Cloud Platform account and project
• Cloud Functions should be enabled for that project

We often use individual HTTP Cloud Functions as a single endpoint, and we pass data to the functions with either query parameters, or via a POST body payload. Although it’s a good practice to keep the scope of a function small, however, you can easily write mini Web APIs for a given function, with different paths for different needs, like with usual Web frameworks.

At DataXDay 2019, last week, I had the chance to present an updated version of my introductory talk on the serverless compute options on Google Cloud Platform. There’s always something new to cover!

For instance, if I put my Java Champion hat on, I’d like to mention that there are new runtimes for App Engine standard, like the beta for Java 11, and there’s twice the amount of memory as before. On Cloud Functions, we have an alpha for Java as well (currently Java 8, but it’ll be soon moved to Java 11 instead, as customers are more interested in the latest LTS version)

Last week at the Google Cloud Next conference, I had the chance to speak about the Java developer’s journey through the “serverless” offering of Google Cloud Platform, with my colleague Vinod Ramachandran (Product Manager on some of our serverless products):

Serverless Java in 2019 is going to be ubiquitous in your favorite cloud. Well, it’s actually been 10 years since you could take advantage of Java on Google App Engine. But now you can run your apps on the brand-new Java 11 runtime. Not only servlet-based apps but also executable JARs. And what about authoring functions? Until now, you could only use Node or Python, but today, Java is the third runtime available for Google Cloud Functions. We will review the various ways you can develop your Java functions. Last but not least, thanks to serverless containers, containerized Java workloads run serverlessly, without you caring for infrastructure, scaling, or paying for idle machines. Through various demos, we will look at the many ways Java developers will be able to write, build, test, and deploy code in Java on the rich serverless offering of Google Cloud Platform.

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:

A coupe weeks ago, I had the chance to talk at Cloud Next 2018, in San Francisco, with my colleague and friend Alexis. We talked about building and deploying microservices with Google App Engine and Cloud Functions. I’ve been a big fan of App Engine since 2009 when Google released the Java flavor, and have been enjoying doing a bit of Node / JavaScript on Cloud Functions since it came in beta. So I was very happy to be able to talk about those two serverless solutions.

My buddy Wassim and I were back on stage together to talk about chatbots, with Actions on Google and Dialogflow, at DevFest Lille and Best of Web Paris. I’d like to share with you the slides of the presentation (the video has been recorded and will be available at a later time.)

You might be interested in those two codelabs to get started on this journey:

• Build Actions for the Google Assistant - level 1
• Build Actions for the Google Assistant - level 2

Here’s the presentation given at DevFest Lille:

A few weeks ago, my buddy Wassim and I had the chance to present again on the topic of chatbots, with API.AI and Cloud Functions, at the DevFest Toulouse conference.

Here’s the latest update to our slide deck:

There’s also a video (in French) of the same content from Devoxx France, where I was showing how to build a conference chatbot:

Chatbots, per se, are not really new, in the sense that we’ve been developing bots for things like IRC for a long time, but back in the day, it was simply some regular expression labor of love, rather than the natural language that we use today. The progress in machine learning, in both speech recognition (for when you use devices like Google Home) and natural language understanding (NLU), is what led us to being able to speak and chat naturally to those chatbots we encounter now.

That’s Devoxx France this week, and I’ve had the pleasure of delivering today another talk on the theme of chatbots, using Cloud Functions for the business logic, API.AI for the bot cleverness, with a bonus of a demo through Google Home and the Google Assistant platform.

I’ll post the YouTube video recording once it’s online, but in the meantime, I wanted to share my slides here:

And the video in French: