Shine’s TEL group was established in 2011, initially to share jam-making recipes. We publicise the great technical work that Shine does, and raise the company’s profile as a technical thought-leader in the community through blogs, local meetup talks, and conference presentations. We curate all the noteworthy things that Shiners have been up to and publish a newsletter, this very one that you’re reading right now. Hey, when you read this, whose voice do you hear in your head? Is it mine? Or yours? Everything I read is in Frank Walker from National Tiles’ voice, please help me. Read on for this edition.
Google Next 2018
Due to me being kind of a big deal around here, I was sent to Google Next 18 last week. It’s a two-and-a-half-day conference in San Francisco, all about Google Cloud. I made some exciting discoveries, which I will share with you, and also went to some talks or something.
Angular Conf Melbourne 2018: Conference Recap
It was early morning rush hour on Friday, June 22nd, and the Melbourne winter sun shone on my face. I was attending Angular Conf Australia, being held at South Wharf. Arriving with just enough time to spare, I looked around the conference venue and had a quick chat with some of the participants.
After a slight delay, the conference kicked-off with a quick thanks to sponsors and supporters. In this post I’m going to give you a rundown of what I saw next.
An Introduction to Angular Progressive Web Applications
A couple of weeks ago I attended Angular Conf Australia and did a full-day workshop on Progressive Web Applications. In this post I’ll talk about what I learned. In doing so, I’ll show the basic concepts of progressive web applications and service workers, and demonstrate how service workers work in a real application.
What the heck is {N}ativescript?
Native-what?
If you’re anything like myself before embarking on this project then you might wonder the same thing. Everyone has heard of React Native, it’s a popular technology enabling a cross-platform mobile development experience, but not so many have crossed paths with Nativescript, or {N}.
Nativescript is a framework with a similar goal to React Native, providing the ability to publish native apps for both major platforms, iOS and Android, whilst only maintaining a single (mostly) JavaScript codebase. It is available in three flavours: standard, Angular, and Vue.js, allowing developers with experience in the latter two frameworks to use their existing skills whilst building for mobile.
Put simply, it’s a JavaScript runtime inside a native app, translating code on the fly into native elements. In this post, I’m going to tell you about a few of the nice experiences we’ve had recently developing with Nativescript, as well as a few of the not so nice issues that were encountered, and whether we’d use it again.
Exploring creativity at Semi Permanent 2018
Semi Permanent May 24-26, 2018
Held in Carriageworks in Sydney this design conference has been going since 2003. It covers new design ideas, presentations of great media and advertising agency work and artists recalling their own journeys developing their work and careers. The presenters include directors, photographers, typographers and illustrators. It includes big names in the design industry – past conferences have hosted Pixar, Banksy, Weta digital, Oliver Stone and VICE media.
TEL Newsletter – June 2018
Shine’s TEL group was established in 2011, initially as a money-laundering operation. We publicise the great technical work that Shine does, and raise the company’s profile as a technical thought-leader in the community through blogs, local meetup talks, and conference presentations. We curate all the noteworthy things that Shiners have been up to and publish a newsletter, in accordance with a mystical schedule that you wouldn’t understand. Read on for this edition.
Implementing A/B Tests with Adobe Target & AngularJS Decorators
Web analytics tools are used to understand the behaviour of website visitors, and A/B testing is a technique that uses such tools to optimise a site. The tools facilitate this by giving you a means to measure and analyse site traffic and conversion.
Adobe Target is a real-time metrics-collection and reporting tool that is one of the most widely-used client-side analytics platforms available. In this blog, I’m going to talk about how to create an A/B test using Adobe Target and AngularJS, where the ‘B’ version is swapped-in using Angular decorators.
Getting ya music recommendation groove on, this time on Amazon Web Services
In this blog series so far, I have presented the concepts behind a music recommendation engine, a music recommendation model for TensorFlow, and a GCP architecture to make it accessible via the web. The end result has been an ML model wrapped in a stand-alone service to give you predictions on-demand.
Before diving further into implementing more complicated ML models, I thought it would first be worth looking into how we could deploy our TensorFlow model into AWS. After some investigation, I’ve concluded that the better way is to use Lambda functions. In this post, I’ll explain why that’s the case, how you can do it, and an interesting pain point you have to keep in mind.
Let’s break the new ground!
Introducing column based partitioning in BigQuery
Some background
When we started using Google BigQuery – almost five years ago now – it didn’t have any partitioning functionality built into it. Heck, queries cost $20 p/TB back then too for goodness’ sake! To compensate for this lack of functionality and to save costs, we had to manually shard our tables using the well known _YYYYMMDD suffix pattern just like everyone else. This works fine, but it’s quite cumbersome, has some hard limits, and your SQL can quickly becomes unruly.
Then about a year ago, the BigQuery team released ingestion time partitioning. This allowed users to partition tables based on the load/arrival time of the data, or by explicitly stating the partition to load the data into (using the $ syntax). By using the _PARTITIONTIME pseudo-column, users were more easily able to craft their SQL, and save costs by only addressing the necessary partition(s). It was a major milestone for the BigQuery engineering team, and we were quick to adopt it into our data pipelines. We rejoiced and gave each other a lot of high-fives.
