Chrome Installed 4 GB of AI on My Machine Without Asking: I Inspected What It's Actually Doing and I Don't Like What I Found Why does Google assume 4 GB of your storage belongs to them? I'd been asking myself that for weeks every time I saw the same Chrome process lit up in the Activity Monitor. Today I opened it. And what I found changed my position on something I was genuinely, enthusiasticall
Chrome instaló 4 GB de IA en mi máquina sin pedirme permiso: inspeccioné qué hace realmente y no me gusta lo que encontré ¿Por qué Google asume que 4 GB del almacenamiento de tu máquina le pertenecen? Llevaba semanas preguntándomelo cada vez que veía el mismo proceso de Chrome prendido en el monitor de actividad. Hoy lo abrí. Y lo que encontré me cambió la postura sobre algo que, hace no mucho,
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
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
You just ran a dependency scan and the report shows 133 vulnerabilities. 34 are Critical. 68 are High. The dashboard is red, the backlog is exploding, and every item looks urgent. The engineering team asks the obvious question: where do we start? This is where vulnerability remediation prioritization matters. Without a clear framework, teams either panic and chase the loudest CVE, or they ignore t
We've been there. JSON Schema gets hard to write as soon as your payload is non-trivial. Conditional logic, cross-field rules, business invariants, and at some point we stop writing contracts at all. We go code-first, generate the schema from annotations, and end up with 200 lines very few understand, and error messages referencing paths like #/properties/items/allOf/0/then/Then that map to nothin
Metric Value Django Average Response Time 287ms Node.js Average Response Time 193ms Django Memory Usage (1000 users) 1.8GB We tested Django 4.2 and Node.js 18.16 under identical conditions to measure their performance for reporting dashboard workloads. The test environment consisted of AWS EC2 m5.2xlarge instances (8 vCPUs, 32GB RAM) running Ubuntu 22.04. Both frameworks connected to th