Horizontally Scalable Computing System
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A Horizontally Scalable Computing System is a computing that can be scaled by adding [[computing resources to (or removing resources from) a single node.
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- Counter-Example(s):
- See: Network Function Virtualization, Amdahl's Law.
References
2019
- (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Scalability#Vertical Retrieved:2019-4-21.
- Scaling vertically (up/down) means adding resources to (or removing resources from) a single node, typically involving the addition of CPUs, memory or storage to a single computer.
Larger numbers of elements increases management complexity, more sophisticated programming to allocate tasks among resources and handle issues such as throughput and latency across nodes, while some applications do not scale horizontally.
Note that network function virtualization defines these terms differently: scaling out/in is the ability to scale by add/remove resource instances (e.g. virtual machine), whereas scaling up/down is the ability to scale by changing allocated resources (e.g. memory/CPU/storage capacity)
- Scaling vertically (up/down) means adding resources to (or removing resources from) a single node, typically involving the addition of CPUs, memory or storage to a single computer.