Blogs

There’s a trend in the industry to make data science and machine learning more accessible, allowing engineers to build and deploy standard models without needing to have a strong data science background.

I’ve been a Tech Lead for a few years now, though I’d say I’ve only been a good Tech Lead for about a year.

As I start to think about some of the upcoming projects we’ll be working on over the next year and how we might go about building them, I wanted to consider where lambda architecture fits in our toolbox for building data services.

Postmortems are a well established process followed in the aftermath of an incident.

Many tech companies follow the “you build it, you run it” mantra - and for good reason.

The revelation by British, Dutch, and American spies of the systematic espionage by Russia was astonishing in many ways.

When some people talk about a Data Lake (or Hadoop, or even just Big Data), they go on to say that we can store all our data, unstructured, forever, and be able to analyse it at any time (maybe even in real-time!

Right now I’m drinking my 5th homebrewed beer.

I’ve been investigating using Apache Kafka with Apache Beam and set up a small prototype environment using Docker Compose.

For the last year I’ve been using Wercker to deploy this site each time I make a change (normally a new post) and push it to BitBucket.