It felt overwhelming—hundreds of tabs were open across my browser, each representing a piece of information I once deemed crucial. I had become a digital hoarder, accumulating resources with no plan to revisit them. It was time to act, and that’s when I stumbled upon Notion Web Clipper. As a developer based in Batam, Indonesia, my days often blur together as I juggle coding, learning, and keeping
While learning python today, I spent some time understanding how the Python shell works and how modules behave inside it. The Python shell (or REPL) is basically an interactive environment where you can run code line-by-line. It's super useful when you just want to test something quickly instead of running a full script every time. While experimenting, I tried something interesting. I created a Py
This is Part 1 of a two-part series. Part 2 (coming soon): Connecting to spoke clusters from a controller using multicluster-runtime, driven by ClusterProfile. The Cluster Inventory API (multicluster.x-k8s.io) is driven by SIG-Multicluster and centered on the ClusterProfile resource. It only delivers value when something produces those ClusterProfiles. That something is a cluster manager. Today, t
When developers travel, we usually prepare the obvious things. Laptop charger. But there is one dependency that is easy to underestimate until it breaks: mobile internet. A trip to China makes this especially obvious. Not because China is hard to travel in, but because so many basic interactions are mobile-first: navigation, translation, ride-hailing, hotel communication, ticket confirmations, pay
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A backup job missed 24 days of runs. Nobody knew. The CronJob looked fine in kubectl get cronjobs. No alerts fired. The last successful run timestamp in the status field just sat there, quietly getting older. The root cause: the CronJob controller had silently given up scheduling after missing 100 runs. Logged an error. Stopped trying. Moved on. This article explains why Kubernetes CronJobs are st
The Hidden Cost of Calling AI Too Early I stopped calling AI on every request — and everything got better. In one of my projects, I was generating AI-based insights from user activity. The initial design was simple: Every request for today’s insight → call the AI model → return a fresh response. GET /api/insights/today At first, this felt clean and correct. But in practice, it created serious
A defaced website is a curious problem. It's loud — anyone visiting the page can see something is wrong. But it's also quiet from a server's perspective: HTTP returns 200, your uptime monitor is happy, your TLS cert hasn't moved, and the CMS logs show a "successful" content update from a legitimate-looking session. The signal is on the rendered page, not in the metrics. I run a site at hi3ris.blue