If it was more static content it'd be easier, it's really the db being a bottle neck in a dynamic site.

Yes, the software could be better optimized but then I'd have to own the development of it. There is no reason a niche website should be getting millions of requests per day.

I adopted Cloudflare because it was getting DDoSed by the AI crawlers. I'm pretty sure all of them are vibe coding their crawlers and don't bother adding rate limiting as a requirement.

Most legit search engines are going to honor robots.txt and you can disallow access.

Next level would be using something like rate limiting controls and/or Cloudflare's bot fight mode to start blocking the bad bots. You start to annoy some people here.

Next would be putting the content behind some form of auth.

I understand the issue about using Layout and MemorySegment being verbose but the reason I'm using those things it to develop high performance software that uses off-help memory and bypasses object allocation.

What does "map Java record types onto native memory" actually mean? Did you somehow turn a Java record into a flyweight or is `Point point = points.get(0);` just instantiating a record instance using data read from off-help memory? If it's a dynamic mapping library using reflection, that's cool but doesn't it kill the performance goals for most Java off heap usage?

Is this more of a off-heap to heap bridge for pulling data into the normal Java space when performance isn't critical?

The only way I can do serious development with Gemini models is with other tooling (Cline, etc) that requires API based access which isn't available as part of the subscription.

I probably wouldn't believe him either. Google should have an option to revert to the last trusted config after some verification method. Google support is bad, I'll give him that.

All this to avoid roaming charges? And then refusing to share a personal email in this scenario and missing meetings because of that.

I'd argue that changing the MX to fastmail or Microsoft would be much faster than a postfix+dovecot solution on a VPS but I think he's just refusing any solution based on his principals.

But Gemini's API based usage also has a free tier and if that doesn't work for you (they train on your data) and you've never signed up before you get several hundred dollars in free credits that expire after 90 days. 3 months of free access is a pretty good deal.

Does the study normalize velocity between the groups by adjusting the timeframes so that we could tell if complexity and warnings increased at a greater rate per line of code added in the AI group?

I suspect it would, since I've had to simplify AI generated code on several occasions but right now the study just seems to say that the larger a code base grows the more complex it gets which is obvious.

Strangely this is one of the areas where I want to use project panama so I might re-implement some of the ring buffers constructs.

You allocate off heap memory and dump data into it. With modern Java classes like Arena, MemoryLayout, and VarHandle it's honestly a lot like C structs.

I answered "why" in another post in this thread.

I don't work for a firm so don't get to play with FPGAs. I'm also not co-located in an exchange and using microwave towers for networking. I might never even have access to kernel networking bypass hardware (still hopeful about this one). Hardware optimization in my case will likely top out at CPU isolation for the hot path thread and a hosting provider in close proximity to the exchanges.

The real goal is a combination of eliminating as much slippage as possible, making some lower timeframe strategies possible and also having best class back testing performance for parameter grid searching and strategy discovery. I expect to sit between industry leading firms and typical retail systematic traders.

It wasn't a matter of choosing Java for HFT, it was a matter of selecting a project that was a good fit for Java and my personal knowledge. I was a Java instructor for Sun for over a decade, I authored a chunk of their Java curriculum. I wrote many of the concurrency questions in the certification exams. It's in my wheelhouse :)

My C and assembly is rusty at this point so I believe I can hit my performance goals with Java sooner than if I developed in more bare metal languages.

You have to optimize your memory usage patterns to fit in CPU cache as much as possible which is something typical Java develops don't consider. I have a background in assembly and C.

I'd say it's slightly harder since there is a little bit of abstraction but most of the time the JIT will produce code as good as C compilers. It's also an niche that often considers any application running on a general purpose CPU to be slow. If you want industry leading speed you start building custom FPGAs.

Examples: AI really wants to use Project Panama (FFM) and while that can be significantly faster than traditional OO approaches it is almost never the best. And I'm not taking about using deprecated Unsafe calls, I'm talking about using primative arrays being better for Vector/SIMD operations on large sets of data. NIO being better than FFM + mmap for file reading.

You can use AI to build something that is sometimes better than what someone without domain specific knowledge would develop but the gap between that and the industry expected solution is much more than 100 hours.