Moved a Core Web Vitals collection setup designed for shared observability infrastructure to my personal blog. Fixed a dashboard left empty by sparse traffic and changed when metrics are collected for ordinary browsers. This post records the changes from October 17 to 22, query omissions investigated on October 23, and what five days of data can support.
Sent the Core Web Vitals measured in an app webview to an observability platform shared by many teams. The webview gave no signal on leaving, and tail sampling, delta-to-cumulative conversion and Tempo queries each dropped values in their own way without raising an error. For every setting that could not be changed, re-measured what was lost in a reproduction environment.
Raise traffic 12x and it takes 31.5 seconds for a new pod to receive its first request. I pulled an itemized bill for those 31.5 seconds with a stopwatch: the structure dominated by the detection window, the conditions under which the autoscaler goes blind in the five minutes right after a deploy, the scale-down staircase, why memory-based HPA misfires on Node, and KEDA's preemptive scaling. Part 5 of the Kubernetes for frontend developers series.
Even a deploy that changes not a single line of code leaks errors. This is a measured record of tagging every failure that leaks during rolling deploys by type and timestamp, performing an autopsy on four causes, and stacking prescriptions one layer at a time until the count reaches zero. Includes the actual Next.js shutdown code, hostage draining, and the real CrashLoopBackOff timetable. Part 4 of the Kubernetes for frontend developers series.
A Service's ClusterIP is an IP attached to no machine, yet curl reaches it. iptables rules and conntrack, EndpointSlice, cluster DNS and ndots, Gateway, and port-forward: a record of opening up the entire path a request takes to a pod, directly in a kind cluster. Part 3 of the Kubernetes for frontend developers series.
The same Next.js app produced one 1.72GB image and one 208MB image. This post traces the missing 1.5GB back through the layers, and verifies with PIDs and cgroup files that a container is an isolated process. The second post of the Kubernetes for frontend developers series.
The Kubernetes vocabulary and structure that frontend developers running SSR actually encounter, organized in the order of real work: the overall cluster structure, what makes up a deploy, pod state and resources, the traffic path, and autoscaling. The first post of the series and the reference map for the rest.
I added one GC tuning flag to the same workload and peak RSS jumped from 201MB to 593MB, while the live data stayed the same. This post traces back through V8 New Space with direct measurements to show why that result is exactly what should happen, and lays out the three axes frontend developers can use to size a Node.js pod.
What question does vinext really ask?
Why GitHub Actions scheduled workflows get delayed by dozens of minutes: the structural causes, and free alternatives that actually run on time.
