🔊 Voiced by Amazon Polly As long as a project runs only for me, a failed deployment is annoying but harmless. That changes the moment the first LinkedIn post goes out and real readers land on the site. A broken chat widget, a dead contact form, or a failed sentiment analysis is no longer just a personal problem — it’s a bad first impression. That was the trigger to tackle two things I’d been putting off: unit tests for all Lambda functions and a pipeline that only deploys what actually changed.

🔊 Voiced by Amazon Polly OG images are the preview cards that appear when you share a link on WhatsApp, LinkedIn, or Twitter. Nobody talks about them, but everyone sees them. A bad OG image is like a bad business card — technically it works, but it doesn’t make a good impression. My first OG images were bad. V1: Hugo’s Built-In Image Pipeline Hugo can process images. There’s images.Text, images.

🔊 Voiced by Amazon Polly $4.64 in two days. For a blog with modest traffic, that’s an unexpected surprise in the AWS Cost Explorer. The culprit was easy to find — but the fix took three iterations worth writing down. The Problem My analytics system is built on Kinesis Firehose → S3 → Athena. A scheduled Lambda runs every hour, queries Athena, and writes the result as JSON to S3 where the dashboard reads it.