Tired of relying on Big Tech to enable collaboration, peer-to-peer enthusiasts are creating a new model that cuts out the middleman. (That’s you, Google.)
I work in a company that runs an own cloud for most of it’s business operations and for customers. I know where the data center is and when I go there I SEE the computers running the cloud.
It’s physical hardware running virtual machines and storage servers, and network switches with absurdly and unnecessary complex configuration, all owned by, well, someone else (the company).
So yes, the features of “the cloud” are distinct from your everyday stuff done on the computer sitting under your desk, but it really is just someone else’s computer running “the cloud”.
That’s true in the same way as you are nothing else but molecules and some biochemical reactions.
It’s reductionist, and otherwise not a useful description of a human, tells nothing about interaction possibilities, lifestyle or lifespan for example.
It’s also not an accurate description, because “molecules and biochemical reactions” describes very very many life forms, just as “a computer” could be your smartphone. But aside from both being a computer, a smartphone is quite distinct from a cloud.
Isn’t part of “the cloud” being able to scale? That only works if there is a large® shared infrastructure layer. Of course I can have my own datacenter where I host my clustered services. But if I decide I need 20% more resources, I need to order and setup 20% more machines. On the other hand, if I just keep 20% machines idling around for the chance that I might need to scale up, I waste a lot of money.
I’d say it’s more about elasticity. Scaling is just very narrow aspect of elasticity.
To give you some specific example, there’s a company (that I won’t name) that by law has to have all data on premises. They have local cloud in their own datacentre. Part of that cloud is a set of powerful servers with ton of GPUs. Daytime they spin up VMs that employees can log into and have remote desktop for graphically intensive tasks.
Now you might be thinking “wait a second, they can’t easily add GPUs in the morning as employees log in, there is no scaling and thus no cloud!” And by that definition you’d be right. But what they do with their cloud is that as the demand for VDI drops in the evening, they will start allocating the GPU and CPU resources to completely different kind of VMs that do overnight data crunching. (think geospatial data) It’s completely different OS, the servers are in server subnet, not VDI network, etc… So they are using the elasticity, but it’s not just scaling.
Another counterexample is pretty frequent issue on AWS, where they momentarily run out of specific instance type in specific region. AWS support “will do their best” but you’re often looking at hours of wait time before you get your instance. Now depending where you live you could go buy a server and deploy it in your own DC faster than that. Has AWS stopped being cloud provider? No, you can use the elasticity and either spawn different instance type (if your workload allows that) or in different region/AZ. You might have been just trying to replace one instance with another, not even trying to scale up, it’s just the capacity for replacement wasn’t there.
An ant hill isn’t an ant. Your consciousness isn’t a neuron. The cloud is an abstraction on top of all that hardware. Each individual machine is simple and volatile, but a network of machines around the world offering reliability and resiliency create a new thing entirely that we call “the cloud”.
I work in a company that runs an own cloud for most of it’s business operations and for customers. I know where the data center is and when I go there I SEE the computers running the cloud.
It’s physical hardware running virtual machines and storage servers, and network switches with absurdly and unnecessary complex configuration, all owned by, well, someone else (the company).
So yes, the features of “the cloud” are distinct from your everyday stuff done on the computer sitting under your desk, but it really is just someone else’s computer running “the cloud”.
That’s true in the same way as you are nothing else but molecules and some biochemical reactions.
It’s reductionist, and otherwise not a useful description of a human, tells nothing about interaction possibilities, lifestyle or lifespan for example.
It’s also not an accurate description, because “molecules and biochemical reactions” describes very very many life forms, just as “a computer” could be your smartphone. But aside from both being a computer, a smartphone is quite distinct from a cloud.
Isn’t part of “the cloud” being able to scale? That only works if there is a large® shared infrastructure layer. Of course I can have my own datacenter where I host my clustered services. But if I decide I need 20% more resources, I need to order and setup 20% more machines. On the other hand, if I just keep 20% machines idling around for the chance that I might need to scale up, I waste a lot of money.
I’d say it’s more about elasticity. Scaling is just very narrow aspect of elasticity.
To give you some specific example, there’s a company (that I won’t name) that by law has to have all data on premises. They have local cloud in their own datacentre. Part of that cloud is a set of powerful servers with ton of GPUs. Daytime they spin up VMs that employees can log into and have remote desktop for graphically intensive tasks.
Now you might be thinking “wait a second, they can’t easily add GPUs in the morning as employees log in, there is no scaling and thus no cloud!” And by that definition you’d be right. But what they do with their cloud is that as the demand for VDI drops in the evening, they will start allocating the GPU and CPU resources to completely different kind of VMs that do overnight data crunching. (think geospatial data) It’s completely different OS, the servers are in server subnet, not VDI network, etc… So they are using the elasticity, but it’s not just scaling.
Another counterexample is pretty frequent issue on AWS, where they momentarily run out of specific instance type in specific region. AWS support “will do their best” but you’re often looking at hours of wait time before you get your instance. Now depending where you live you could go buy a server and deploy it in your own DC faster than that. Has AWS stopped being cloud provider? No, you can use the elasticity and either spawn different instance type (if your workload allows that) or in different region/AZ. You might have been just trying to replace one instance with another, not even trying to scale up, it’s just the capacity for replacement wasn’t there.
Nobody is saying it’s not a computer, but the tooling, reliability and services make it more than just a computer.
An ant hill isn’t an ant. Your consciousness isn’t a neuron. The cloud is an abstraction on top of all that hardware. Each individual machine is simple and volatile, but a network of machines around the world offering reliability and resiliency create a new thing entirely that we call “the cloud”.