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So what's your excuse for why New York has equally bad internet?


City or state?

City: just take a walk through manhattan and in a block or two look at the giant open-pit excavation with a 200-year-old morass of undocumented infrastructure under the street. This is before you even try to run fiber up to units in buildings which were built before electricity was standard. I am hardly saying it can't be done, simply that it is not as easy as density makes it seem.

State: the exact opposite problem -- just drive two hours north of NYC and (if you're not still in manhattan) you'll be in some fantastic areas of the state, but, the exact opposite problem exists.

Of note, I do think both of these problems are solvable and we should fundamentally solve them. Just anybody who thinks it's easy or cheap to do so is being myopic. If spent wisely, could be a very useful investment of our money, however.


Do you think the wilds two hours north of NYC are more or less difficult for laying fibre lines than between homes literally in the alps? 60% of switzerland is alps. Not exactly a cake walk for infrastructure development.

And why would they need open pit excavation for FTTH in NYC? Are there not existing trenches and under-street ducting for cables already in most of the city? Surely there are going to be some tricky areas but how to the other utilities like phones and electric work on their cabling?


The idea was to transition from coal to natural gas while using solar and wind to reduce fuel consumption, thereby significantly reducing CO2 emissions. Any claims of hydrogen being burned were either lies to the public to get the gas plants built despite the non-green optics or lies to investors as part of a fraud scheme.


Hydrogen burning could have a place in an all-renewable grid: it could be much more economical for very long duration storage than using batteries. The last 5-10% of the grid becomes much cheaper to do with renewables if something like hydrogen (or other e-fuels) is available.

A competitor that might be even better is very long duration high temperature thermal storage, if capex minimization is the priority.


> it could be much more economical for very long duration storage than using batteries

Yes, but that's not the only option you have. With the absolutely awful efficiency of burning hydrogen you'd need to be building a massive amount of additional wind and solar - which in turn means you'll also have additional capacity available during cloudy wind-calm days, which means you'll need to burn substantially less hydrogen to generate power.

This leads to the irony that building the power-generation infrastructure for generating enough hydrogen means you won't even need to bother with the hydrogen part: you're basically just building enough solar that their overcast supply is enough to meet the average demand. As a bonus, you've now got a massive oversupply during sunny winter days and even more during summer days, so most of the year electricity will essentially be free.


Efficiency is not very important for very long duration storage. What's important is minimizing cost, which is dominated by capex, not by the cost of the energy used to charge the storage system. Paying more to charge it can make sense if that greatly reduces capex.

So, yes, more input energy is needed. So what?


More efficient to spend the same amount of money on shoreside panels with lower installation costs.


Servers with ECC generally report zero recoverable memory errors until the chip starts failing, at which point there are increasingly many. Therefore the average server experiences zero cosmic ray related memory errors during its lifetime, despite having many times more memory than 256MB.


So how are the special interest groups keeping their enemies out?


Same as it is everywhere else, collusion and nepotism.

Wikipedia editors are a special clique.


The government will keep changing the rules until VW wins. Using tariffs, price floors, subsidies, whatever it takes.


European and national politics have been anything but kind to European automakers for quite some time.


This only applies to steam keys sold off site, which is why the original comment specified non-steam keys.


Interesting to see the definition of moat change from keeping other companies out to keeping your customers in.


I don't hate journald because it's not plaintext, I hate it because it's worse than plaintext. Somehow journald manages to provide a database which is 40x slower to query than running grep on a compressed text file. I'm all in favour of storing logs in an indexed structured format but journald ain't it.


Even doing zcat | grep is faster than journald.

I now turn off journald and use rotated pain text log files. It's more efficient in all metrics.


Journald is an odd one. I don't think it being a binary log/database makes sense. If you have a tiny operation, with a single server, then the binary database doesn't really make sense, having plain text is just easier and faster. If you're a bigger operation, you'll have a central logging solution, in which case you need journald to store the longs as plain text as well, before you can do log shipping.

The only use case where the binary format might make sense is if you ship journald logs to another central journald instance. That's just very much an edge case.


afaik journald can just forward logs via rsyslog directly to a remote server

Why would it need to store plaintext locally?


Doesn't that still involve a conversion? I believe that rsyslog can read the journald database, but you're typically not querying syslog data directly, so there's a conversion between rsyslog and logstash, Splunk, Datalog, whatever.


Some folks like having some local storage to act as a buffer in case the remote syslog server is down. Not sure if journald can do that on its own.


sqlite resolves lock contention between processes with exponential backoff. When the WAL reaches 4MB it stops all writes while it gets compacted into the database. Once the compaction is over all the waiting processes probably have retry intervals in the hundred millisecond range, and as they exit they are immediately replaced with new processes with shorter initial retry intervals. I don't know enough queuing theory to state this nicely or prove it, but I imagine the tail latency for the existing processes goes up quickly as the throughput of new processes approaches the limit of the database.


That is interesting, I’ll have to look into that further. I would expect Go to have similar issues because the RPS isn’t that much less. But maybe there is some knife edge here.


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