We also have much much bigger single machines available for reasonable money. So a lot of reasonable workloads can fit in one machine now that used to require a small cluster
Think about it: That 20 core CPU (eg: i7 14700K) you can buy for just a couple hundred dollars today would have been supercomputer hardware costing tens or hundreds of thousands of dollars just a decade ago.
For a desktop, yeah, you’re generally better off buying newer from a performance/$ standpoint. For servers, the calculus can shift a bit depending on your company’s size and workloads. Most smaller companies (small is relative, but let’s go with “monthly cloud bill is < $1MM”) could run on surprisingly old hardware and not care.
I have three Dell R620s, which are over a decade old. They have distributed storage via Ceph on NVMe over Mellanox ConnectX3-PRO. I’ve run DB benchmarks (with realistic schema and queries, not synthetic), and they nearly always outclass similarly-sized RDS and Aurora instances, despite the latter having multiple generations of hardware advancements. Local NVMe over Infiniband means near-zero latency.
Similarly, between the three of them, I have 384 GiB of RAM, and 36C/72T. Both of those could go significantly higher.
Those three, plus various networking gear, plus two Supermicro servers stuffed with spinning disks pulls down around 700W on average under mild load. Even if I loaded the compute up, I sincerely doubt I’d hit 1 kW. Even then, it doesn’t really matter for a business, because you’re going to colo them, and you’re generally granted a flat power budget per U.
The downside of course is that you need someone[s] on staff that knows how to provision and maintain servers, but it’s honestly not that hard to learn.
[0]: https://www.guru3d.com/review/core-i7-4790k-processor-review...
[1]: https://www.tomshardware.com/news/intel-core-i9-14900k-cpu-r...
So maybe I was a bit too high on the pricing earlier, but my point still stands that the computing horsepower we have such easy access to today was literal big time magic just a decade ago.
[1]: https://ark.intel.com/content/www/us/en/ark/products/84685/i...
[1] Intel Xeon w3-2423 Processor 15M Cache, 2.10 GHz:
https://www.intel.com/content/www/us/en/products/sku/233484/...
[2] Intel Launches Xeon W-3400 and W-2400 Processors For Workstations: Up to 56 Cores and 112 PCIe 5.0 Lanes:
https://www.anandtech.com/show/18741/intel-launches-xeon-w-3...
The big question is: Does a 'reasonable' workloads today fit on a single machine better than a 'reasonable' workload did 20 years ago?
I proposed dumping them all for a smaller set of x86 hosts running linux, it took 2-3 years before the old admins believed in the performance and cost savings. They refused to believe it would even work.
Those days, you had to carefully architect your infrastructure and design your workload to deal with it, and every hardware improvement required you to reevaluate what you were doing. Hence novel architectural choices.
Everything is way easier for normal sized organizations now, and that level of optimization is just no longer required outside of companies doing huge scale.
To this day I still argue with ex Solaris sysadmins.
It was never about the actual workloads, much more about growth projections. And a whole lot of cargo cult behavior.
You could just distribute your workloads using...a queue, and not have this problem, or have to pay for and pay to maintain backup equipment etc.
The point here is that 99% of companies are not in that scenario, so they should not emulate the very expensive distributed architectures used by Google and a few other companies that ARE in that scenario.
For almost all companies on the smaller side, the correct move is to take the occasional downtime, because the tiny revenue loss will be much smaller than the large and ongoing costs of building and maintaining a complex distributed system.
I‘d argue that is wrong for any decently sized ecommerce platform or production facility. Maybe not millions per hour, but enough to warrant redundancy. There’s many revnue and also redundancy levels between Google and your mom and pop restaurant menu.
From the post directly above: “Most businesses…”
The thread above is specifically discussing business which won’t lose a significant amount of money if they go down for a few minutes. They also postulate that most businesses fall into this category, which I’m inclined to agree with.
In your typical seed, series A, or series B SaaS startup, this is most often not the case. At the same time, these are the companies that fueled the proliferation of microservice-based architectures, often with a single-point of failure in the message queue or in the cluster orchestration. They shifted easy-to-fix problems into hard-to-fix problems.
Loads of software issues, of course.
I know this is just an anecdote, but I'm pretty certain reliability has increased by one or two orders of magnitude since the 90s.
When I worked with small firms who used kubernetes, we had more kubernetes code issues that machines failing. The solution to the theoretical problem was the cause of real issues. It was expensive to keep fixing this.