iTunes extension for Scratch

June 9th, 2026

In this post, I want to share a new Scratch extension I made today.

screenshot

It uses the iTunes Search API to let you search for songs, and play 30 second previews of them, in your Scratch projects.

The blocks are simple, and hopefully self-explanatory, but here is a short demo of them in action if it’s not obvious.

I’ve added this extension to the version of Scratch I host for Machine Learning for Kids, so you’ll need to go there to try it out. (To access the extensions library, click on the extensions button in the bottom left.)

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Presenting at Current / Kafka Summit

May 21st, 2026

A few of us at Current this week were talking about how Current (formerly “Kafka Summit”) has changed over the years, and it got me remembering the bits I’ve contributed.

I dug through some old posts to find seven Current / Kafka Summit talks I’ve done… it makes for an eclectic set when I see it in one list!

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Embedding Tiny Language Models in Flink SQL

May 20th, 2026

I gave a talk at Current yesterday about how to embed a tiny language model inside your Flink SQL pipeline.

I used a fun mix of demos to show what I think are the main approaches available for using generative AI with Kafka events from a Flink SQL job. Some demos were definitely more sensible than others!

These are the slides I used, and what I’d planned to say.

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In this session, I’ll be talking about your options for running language models for Flink SQL jobs.

I’ll cover:

  • your options for where you run them, in relation to Flink
  • what sorts of choices you have for the models you run
  • how to use them – the sorts of prompts and settings we’d want for Flink
  • how to keep an eye on it that it’s working well
  • and finally, some thoughts on when it’s a good idea to do any of this

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Instrumenting a Kafka Connect connector with metrics

May 2nd, 2026

Metrics can help provide operational insight over Kafka Connect connectors, informing users of how to better configure them. With simple updates, a Kafka Connect connector can be instrumented to make this possible by emitting useful metrics.

A couple years ago, I created a simple skeleton Connect connector project to help developers at a hackathon create their first Kafka connector.

I’ve updated the source connector from that sample to emit metrics. In this post, I’ll walk through what I did, as an example for how to add metrics to your own Kafka connector.

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How to create a Scratch extension

April 27th, 2026

A few years ago, I ran a workshop about how to create custom Scratch blocks.

I made a template repository, based on the Scratch Team repos, but with a skeleton extension and some extra scripts and automation to handle building and publishing it. I included step-by-step instructions for building different types of Scratch extensions, including Scratch blocks based on web APIs, and Scratch blocks based on JavaScript modules from npm.

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22 years at IBM

April 26th, 2026

Looking back at my career so far, and what this could mean for what comes next…

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What do people use to access Machine Learning for Kids?

April 23rd, 2026

I use Cabin for analytics on Machine Learning for Kids. (If you’re not familiar with them, their blog post on how to do analytics in a way that prioritizes user privacy is worth a read – the approach is simple but elegant. And you can see a demo of what a Cabin dashboard looks like.).

I thought it might be interesting to share what Cabin tells me about who has used Machine Learning for Kids over the last seven days.

What Operating Systems are people using?

Operating System Uniques
Windows 404,873
iOS 132,971
macOS 67,848
Android 55,176
Mac OS 35,743
Chrome OS 23,536
Linux 21,852
Ubuntu 10,780
Chromium OS 8,484
HarmonyOS 408
Raspbian 31
OpenHarmony 17
PlayStation 13
Tizen 10
android 3

At work, I’m mostly surrounded by MacBooks and don’t often see a Windows computer. It’s easy to assume that is normal, so this is a reminder that I’m in a bit of a bubble. Windows is still dominant.

Interesting to see “macOS” and “Mac OS” separate (I was tempted to combine them, but I decided to leave the data I get from Cabin as-is.)

My favourite part of looking at this is wondering who are the thirteen people who visited my site from a PlayStation???

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“How many Kafka events will Flink process per second?”

April 11th, 2026

I’m often asked this. The specific question varies, but it’s typically some variation of asking how quickly a single CPU of Flink processes events from a Kafka topic.

Why “per CPU”? Maybe because enterprise software is typically charged per CPU? Maybe because I tend to talk to people who run everything in Kubernetes, who think of running software in terms of requests / limits? Not sure, but the question tends to be framed from the perspective of asking how much processing they can expect to get from a CPU.

I try to avoid doing the engineer thing of answering “it depends“… but… it really does depend!

That is the motivation behind this post: to give me something I can point at as an illustration of the degree to which Flink’s performance varies (and a taste of the range of interrelated factors that influence it).

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