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I first heard the term hyperscale around 2013 when I was managing Google’s data center hard drive software team. As hard drive and SATA controller vendors came in to share their road maps, they started referring to the needs of hyperscalers as something different from those of traditional enterprise users. Google’s needs being different from traditional enterprise wasn’t new but the term hyperscale to refer to Google and others was. Google didn’t use this term internally. As far as I know, Amazon and Facebook didn’t either. Our needs didn’t always overlap either. What did the industry mean by calling us hyperscale?

Seven years later, I’m still wondering what hyperscale means. Research papers and marketing materials talk about hyperscalers without ever clarifying what it means. Who qualifies as a hyperscaler? What are the criteria? I set out to find a definition that answers these questions and, finding little, created my own.

I recently changed my DNS setup on my home network and wanted to move all the clients over to the new nameserver before turning down the old one. My DHCP server was already updated to hand out the new DNS nameserver so all I needed to do was refresh the clients. Due to a few other changes in my network, I had a multi-hour file transfer going on between two machines.

A reader has trouble with two recipes used in separate images that both generate a file with the same path. This leads to a deep dive into how Yocto sysroots work and the perils of a global sysroot cache.

If you want decent monitoring of GitLab deployed via GitLab’s helm charts, skip the built-in Prometheus config and go straight to InfluxDB. Make sure you enable InfluxDB’s UDP interface and replace the autogenerated, default retention policy with a 1h policy. Use GitLab’s Grafana dashboards by using jq to extract the dashboard node from each .json file and then changing the datasource name to match yours.