Nice web design, google!
Looks like Google's CDN works so well that creating resized versions to save bandwidth is not worth it. :)
Worth it to them, maybe; what about the poor reader?
The page loads 41 requests and 12.88 MB of data, with the page taking 2+ seconds to properly load the content (1.09s according to Chrome dev tools, but this is just the initial DOM load).
For a simple webpage with white background and dark text.
But hey, AMP is because Google care deeply about quick web-pages. No alternate agenda here, no siree.
I think they just get too caught up in their tooling and silly over-engineering and never actually think about the end product.
Although Kubernetes requires 3 to start, but still, this greatly reduces the need to have a lot of separate machines.
256 threads per machine this year. 512 threads per machine 2 years from now? And then hopefully 1024 threads per machine 4-5 years from now? That would be really fun.
(I will take a laptop in 4 years with just a lowly 64 cores please, leaving the heavy iron for the cloud machines.)
I want Moore's law back but in parallel form. The years since 2004 with x85 machines have been quite boring from a CPU performance increase perspective.
Why would you want to? Your whole environment will be down when the machine, or some component thereof, fails or is rotated out for maintenance
I think this is more of a benefit for cloud providers in that they can pack more disparate customer workloads on to a single machine.
The advantage of such a machine is that if it starts to die, you fail over everything atomically and then repair/replace the backup. You don't need to think about what happens if one component is on a dead machine and the others aren't (does your load balancer handle that well, given machines often "die" in ways that just make them slow rather than totally failed?)
The big win though is if you get rid of the microservices and run the whole thing in one big process. No complex RPC failures, obscure HTTP/REST attacks like https://portswigger.net/blog/http-desync-attacks-request-smu... and so on.
That might sound mad but modern JVMs can run lots of languages fast, and have ultra-low-pause GCs that can use terabytes of heap. Like less than one msec low. Many, many businesses fit into these really high end machines with a giant JVM.
I've written about the possibility of a swing back to big iron design here:
https://blog.plan99.net/vertical-architecture-734495f129c4
And a look at modern Java GCs - GC being historically the bottleneck to really large single processes:
https://blog.plan99.net/modern-garbage-collection-part-2-1c8...
It doesn't actually, and if you're running on GKE then the master is a managed service - you can have a single-node cluster (I do this occasionally for testing).
Said startup might want to consider going with smaller machines in separate availability zones, though ;-)
(Disclaimer: I work in Google Cloud)
3 is more realistic though. If you run at 66% utilization, can deal with a single node down.
Just buy more cheap 4-8c servers.
I know plenty of people who know the Intel name and would consider AMD to be some kind of cheap knock-off (non-techs, obviously). And obviously desktop/laptop manufacturers are going to have some sweetheart deals with intel.
As far as I understand it, AMD doesn't natively support thunderbolt and that's an emerging standard that people really like.
Don't underestimate a King like Intel that's backed into a corner. Lots of dirty tricks to play and lots of time to come back.
A proper solution of course would be to have the CPU intensive algorithms run on different nodes, but it's an integrated solution we pay for so we don't control that.
Is the problem that the CPU max scales with the number of GPUs, so you can't get 1 GPU with 96 vCPUs?
And how did that work out? Upfront costs but should be significant savings overall right?
The big question for us is if we're going to be able to afford to do it locally, there's both the upfront cost and the cost of system administration. These 3 I could still do with my dev team amateur style, but when that becomes 30, we'll probably need some technician that has experience managing compute clusters.
Also how many machines will they have? Will it be a token amount in a single data center or will there be a good chunk of these around in multiple data centers?
>Intel can cut its prices, to be sure. Beyond that, it has limited maneuverability. Ice Lake servers will not arrive for another year. Pricing on these cores is simply amazing, with a top-end Epyc 7742 selling for just $6950, or roughly $108 per core. An Intel Xeon Platinum 8280 has a list price of over $10,000 for a 28-core chip, just to put that in perspective. If you want a 32-core part, the Epyc 7502 packs 32 cores, 64 threads, higher IPC, and an additional 300MHz of frequency (2.5GHz base, versus 2.2GHz) for $2600 as opposed to the old price of $4200 for the 7601. AMD doesn’t segment its products the way Intel does, which means you get the full benefits of buying an Epyc part in terms of PCIe lanes and additional features. AMD also supports up to 4TB of RAM per socket. Intel tops out at 2TB per socket, and slaps a price premium on that level of RAM support.
If anything, they should cut prices across the board. AMD just cut the price of an x86 core in half.
I'm glad AMD is making such progress that these companies can't ignore them anymore. Having one CPU maker would be horrible.
Another case of scalability: we have also tested ClickHouse on an Aarch64 server (Cavium ThunderX2) with 224 logical cores and despite the fact that each core is 3..7 times slower than Intel E5-2650 and the code is not optimized as much as for x86_64, it was on-par in throughput of heavy queries.
There are also tests of ClickHouse on Power9 if you mind...
