Let's be fair. The title of this post is confusing at first, but once you read it in full, I hope you...
The service lets you share an entire folder - not just a single file - with anyone on the Internet in a single click. Under the hood, GET responses are hydrated with file fragments streamed over a duplex WebSocket connection. Close the browser tab, and the server disappears. Files can also be password-protected. I built it because I needed a way to share a static website with a client without first uploading the work to a cloud service.
GitOps policy drift is what happens when a control plane keeps a policy perfectly reconciled long after the reason for that policy has stopped being true. Every commit is applied. Every pull request is merged cleanly. Every dashboard reads green. And the rule being enforced no longer reflects anything anyone would choose to enforce today — it just hasn't been told to stop. That gap is the subject of this post. Not configuration drift — the thing GitOps was built to kill — but a second, quieter failure mode that lives one layer above it: the policy is right by every technical measure and wrong by every practical one, and nothing in the reconciliation loop is capable of telling the difference. The Promise GitOps Actually Kept GitOps earned its place in the infrastructure as code architecture stack by solving a real and expensive problem: state drift. Before declarative reconciliation, infrastructure diverged from its source of truth constantly — a console change here, an emergency hotfix there, a manual override nobody logged. The git repository said one thing. Production said another. Reconciling the two was a forensic exercise. GitOps closed that gap with a simple, durable mechanism: a controller that continuously compares declared state to actual state and corrects the difference without waiting for a human to notice. That's not a small win. It's the reason platform teams can run infrastructure at a scale that would have been operationally unmanageable a decade ago, and it's why GitOps controllers sit at the center of nearly every modern infrastructure as code architecture built since. This post isn't an argument against that mechanism. It's an argument that the mechanism's success created a blind spot nobody designed for. What GitOps Never Promised to Solve Here's the boundary GitOps was never built to cross: reconciliation proves that declared state and actual state match. It says nothing about whether the declared state should still exist in its current form. A
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Inside the world’s deepest and longest subsea road tunnel —Niall Firth I’m currently around 1,000 feet beneath the North Sea, in a dark, dank cave. It smells weird. And I’m increasingly…
Getty Images will allow OpenAI to use its content library in AI search and ChatGPT.
Octopus and CATL are pledging to roll out a network of battery swap stations for heavy trucks across Europe.
https://archive.ph/tSlDZ https://www.cnbc.com/2026/06/22/alan-greenspan-former-chairm...
submitted by /u/alexeyr [link] [留言]
I haven’t thought about the privacy issues surrounding professional athletes and wearables. Wearables present serious privacy issues for “Average Joe” consumers, who are entrusting tech companies to safely store and protect their biometric data. Imagine the stakes for a professional athlete, whose entire livelihood could be affected by a single biometric data point. To give one of many realistic hypotheticals: a basketball player has a terrible game, and the coach wonders if they showed up to the gym hungover. The coach has access to the player’s wearable data, and checks to see when they went to sleep, as well as what their heart rate looked like during the night. Should the player have been out partying before a game? No. Should the coach be able to surveil them? Definitely not...
Bob Starr was delighted with his vibe-coded website. "Boomberg" showed how much US tax money is going to tech companies, and Starr launched it online immediately after making it. It wasn't until months after the site went live that he realized there was a problem: a hidden SQL injection risk. It could've left the site […]
In this article, the author explores data poisoning as a threat to machine learning systems, covering techniques such as label flipping, backdoors, clean-label poisoning, and gradient manipulation. The article reviews real-world incidents, discusses the challenges of detecting poisoned data, and presents practical defenses, tools, and operational practices for securing ML training pipelines. By Igor Maljkovic
Dan Fineran explores how eBPF has evolved far beyond its roots in packet filtering into a robust, safe way to extend the Linux kernel. He explains how the eBPF "verifier", the security guardrail, enables implementation of deep observability and networking without the risks of traditional kernel modules or the slow upstreaming process. By Dan Fineran
I got tired of MacOS failing to index applications (it consistently seems to prefer apps installed on my phone instead of the computer) so I've bound them to keys and have started building muscle memory for opening and switching apps. Reduces mental fatigue from constantly cmd + tabbing between apps all day