heipei

That's just Germany for ya. Source: Am German

So what is the alternative? It took me a while to get around the data schema / modelling that a database like Cassandra imposed, but when it finally clicked it really clicked for me, so much so that I wish I could have the same performance footprint of consistent hashing / sharding with other databases.

We are using ScyllaDB, but since they discontinued their Open Source version we're stuck on the last supported version, and reading about the operational headaches of Cassandra does not inspire confidence to give it a go.

Legitimate file hosting services present the biggest total volume of newly discovered phishing pages / unique hostnames. Another (similar) angle is using unrelated legitimate domains which are compromised (think insecure Wordpress) to host phishing sites in subdirectories. A lot of traditional ML scoring and blocking approaches fall flat if the hosting domain is on a very legitimate and hard-to-block domain, such as a government website.

Can we please stop posting here every time Claude or OpenAI are down? These are not critical services like AWS / S3 where downtime means that your application is offline. Nothing is easier than switching to another provider, mid-session even.

Cloudflare is really good at launching features that facility low-friction deployment of malicious content (such as phishing) on the Internet, piggybacking on their hosting reputation and the fact that you can't easily block their ASN or domains.

This is gonna be amazing for phishing, like most of the features Cloudflare offers (free Turnstile for fresh accounts, CF tunnels, pages.dev, r2.dev).

It is smart enough that I use for all my coding tasks, and a lot of other mundane tasks.

It is probably not smart enough for "design this whole architecture of this complex system from scratch, make no mistakes", but that is not something I want from a coding tool anyway. I want a model that I can point to a file and tell it to make some changes to the file and related files. Or that I can ask to review a PR with regards to certain aspects.

My suggestion is to simply try it and see what it feels like.

Depends on what you mean by "local". On your Macbook, large dense models like Qwen 3.6 27B will be slow, sure. On a local workstation with a dedicated RTX card you can get > 100 tps, which is more than good enough to work with it, and faster than cloud models in many cases.

No KV cache quant, context length 50% of original, MTP absolutely. These are the relevant cmdline attributes. Getting around 100t/s with this setup, even when watt-limited to 450W.

  --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0.00 --presence-penalty 0 --metrics --jinja --chat-template-file chat_template.jinja --chat-template-kwargs '{"preserve_thinking": true}' --spec-type draft-mtp --spec-draft-n-max 2 --spec-draft-p-min 0.75 -ngl 99 -c 131072 -fa on -np 1 -hf unsloth/Qwen3.6-27B-MTP-GGUF:Q6_K

Same here, I use Qwen 3.6 27b (Q6 quant) with llama.cpp on an RTX 5090 using the pi agent exclusively now. The fact that it's local means that I never have to think about token pricing, quotas, time of day, or data sensitivity. I have limited the GPU from 600W to 450W which means the system stays whisper quiet during inference.

I have become so "lazy" (in a good way), so far that I've started using the model for lots of daily mundane things on top of just coding:

  * "commit this on a branch, push, create a PR and assign $nickname for review"
  * "Use the Stripe CLI to download all open and overdue invoices and reconcile them with this CSV export from our bank account."
  * "Use these Elasticsearch credentials to summarise what kind of operations are causing load at the moment."
  * "Tell me if our codebase already supports X and where it's  implemented."

$5B valuation on a $30B run rate for Anthropic?

Local AI models are already more than capable enough writing code that surpasses the ability of any bad or even mediocre engineer. That is not something we need to worry about.

In a way, this is less of a cost issue than the fact that some/many engineers do not seem to be willing or able to host things themselves anymore and will happily outsource every part of their stack to managed services, be it CDN, hosting, databases, etc. I don't know why that's not more alarming than the LLMs.

Serious question: Who actually builds stuff on Cloudflare workers? I mean large software projects / services, and not just side projects where the ability to scale-to-zero is perhaps more important than the scale-to-infinity direction. I feel like Cloudflare keeps pushing workers with its full force yet I fail to see the appeal.

I just saw the headline fly by yesterday and thought that this was just another dumb bug in what is the slow decline of GitHub. To find out today that this was very much intentional is even worse.

This is amazing, thank you for launching it. I know this webapp itself will make me more likely to look at raw photos on my Fuji once again.

Like the native Fujifilm software, this does not do raw conversion itself. It uses the processor in the camera to do the conversion.

Fair enough, I just loaded some pages and some of them are even bigger than 2MB. But then again those static resources would be cached client-side. So unless you have 450 million unique visitors who only ever go to one URL on your site, you are looking at significantly less per pageview. I reloaded the frontpage with caching enabled and it was ~ 30kB of data transfer.

Yes, and I didn't mean to imply that a single VPS is all you needed. But I wanted to put things into perspective for the other posters who claimed that you couldn't possibly serve a site like this from a single machine, purely in terms of performance.

The post said 450 million pageviews, likely since November. If we make very generous assumptions and assume that each pageview is a megabyte (very generous based on my own experience scanning billions of websites), then that's 450TB total in traffic. If you really did 450TB per month in traffic, you would need slightly more than one gigabit line (and hence VPS), but not more than two. With Hetzner the traffic would cost you €450 or $535.

Did I get something wrong?

Yes, the wildcard cert, but not the actual hostname under that wildcard.

Thank you for sharing, this looks really cool. The simplicity of setting this up and operating it reminds me a lot of nsq which received a lot less publicity than it should have.

I still don't get how folks can hype Postgres with every second post on HN, yet there is no simple batteries-included way to run a HA Postgres cluster with automatic failover like you can do with MongoDB. I'm genuinely curious how people deal with this in production when they're self-hosting.

The client is supposed to monitor availability themselves, that is how these contracts work.

I'd rather he'd still be working on Nomad to be honest, but Ghostty is a good consolation prize ;)

Obligatory reminder that "GPU utilisation" as a percentage is meaningless metric and does not tell you how well your GPU is utilised.

Does not change the usefulness of this dashboard, just wanted to point it out.

Yeah, that was the first thing I checked as well. Being suited for small / tiny files is a great property of the SeaweedFS system.

Sounds complicated. I just use autossh from the CLI and it reconnects if my laptop (or the remote machine) wakes up again.

If you want to see what the phishing site (npmjs[.]help) looks like: https://urlscan.io/result/01992a3e-4f8c-72bb-90a9-c13826f2d8... - Was still up and running 2 hours ago.

I agree, and I don't get where the claims that ES is hard to operate originate from. Yeah, if you allow arbitrary aggregations that exceed the heap space, or if you allow expensive queries that effectively iterate over everything you're gonna have a bad time. But apart from those, as long as you understand your data model, your searches and how data is indexed, ES is absolutely rock-solid, scales and performs like a beast. We run a 35-node cluster with ~ 240TB of disk, 4.5TB of RAM, and about 100TB of documents and are able to serve hundreds of queries. The whole thing does not require any maintenance apart from replacing nodes that failed from unrelated causes (hardware, hosting). Version upgrades are smooth as well.

The only bigger issue we had was when we initially added 10 nodes to double the initial capacity of the cluster. Performance tanked as a result, and it took us about half a day until we finally figured out that the new nodes were using dmraid (Linux RAID0) and as a result the block devices had a really high default read-ahead value (8192) compared to the existing nodes, which resulted in heavy read amplification. The ES manual specifically documents this, but since we hadn't run into this issue ourselves it took us a while to realise what was at fault.

ScyllaDB discontinued it's free and open source version, so I personally wouldn't build anything new on it.