When in a Postgres transaction, the data you read can change underneath you. Did you realise this? Many don't, for good reasons.

Fast build times have a number of benefits, from reliability to developer happiness. We reduces our time to deploy to <5, and it's glorious.

For a small initial investment, we've found a observability setup that works great for both production and local development. You should try it, too!

Any good investigation builds on assumptions, and when they're wrong you can end up down a dark path. Read about an incident where this happened badly, and learn some strategies to avoid falling into the same trap.

Starting next week, I'll be joining the incident.io team after logging off for the last time at GoCardless. Mostly for myself, here's some reflections on the last five years.

Working hard is a great way to accelerate learning, but it can come at a cost. This post shares my experience and lessons taken from great role models I've found along the way.

The upcoming Golang embed directive can help distribute applications that depend on non-Go code assets. See how you can embed an entire Javascript website into your Go program, simplifying distribution to single binary.

Building a modern infrastructure stack is difficult, with a bewildering number of choices to be made. Some technologies complement each other, while others have very different philosophies: it’s easy to get lost.

To help those facing similar challenges, we’re open-sourcing our “Getting Started” tutorial, which is what we ask all GoCardless developers to follow during their onboarding.

Compression is a trick that can be used to solve a load of problems. Outside of well known use cases, there are a variety of opportunities to improve efficiency or save money by leveraging compression.

This post covers one such opportunity, where a tiny change allowed us to save >$30k per year in infrastructure cost, along with a few other big-savers from judicious application of compression.

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Your company probably has a lot of data. When you expose all of these different sources under a tool that makes complex analysis as fast as thought, you'll create a load of opportunities to make data-driven decisions.

By sharing an example where 2hrs of analysis helped prioritse 2-4 weeks of engineering work, I'm going to try convincing you that the value of a connected dataset is far more than the sum of its parts.