Introduction: Nowadays, the amount of data is getting larger and larger, and the demand for data centers will become higher and higher, when the data center needs to expand, then the question is, we need scalable data center resources, so the data center should be scaled up well? Or is it better to scale out? How to take into account cost, efficiency, performance and other factors? In this article, we try to answer these questions, including what is vertical expansion, what is horizontal expansion, vertical expansion scenarios and advantages and disadvantages, horizontal expansion scenarios and advantages and disadvantages, etc.
Scalability is the ability of a system to quickly scale up or down compute, storage, and network infrastructure. As application needs and resource requirements evolve, scaling storage infrastructure provides organizations with a means to adapt to resource demands, optimize costs, and improve operational team efficiency.
Scale up vs scale out
Scale up and scale out are key methods organizations use to increase infrastructure capacity. To the end user, both concepts seem to have the same function. However, they each meet the specific needs of data center infrastructure and solve specific capacity issues in different ways.
Scaling up is adding more resources, such as hard drives and memory, to increase the computing power of a physical server. Whereas scale-out is adding more servers to an organization's architecture to spread the workload across more servers.
Scale up
Scale-up storage infrastructure is designed to add resources to support applications to improve or maintain adequate performance, and both virtual and hardware resources can scale up. In terms of hardware, it may be as simple as using a larger capacity hard drive to significantly increase storage capacity. However, it's important to note that scaling up doesn't necessarily require changes to the system architecture.
Scaling up the infrastructure is feasible until individual components can no longer scale, but this is a fairly short-term solution.
(1) When is it necessary to scale up the infrastructure?
When performance is impacted: When an organization's workloads begin to reach performance limits, such as increased latency and performance bottlenecks due to I/O and CPU capacity, this indicates the need to scale up.
When storage optimization doesn't work: Whenever an optimized solution becomes less effective in terms of performance and capacity, it may be time to scale up.
(2) The advantages of vertical expansion
Increased speed: Scaling up resources, such as replacing a single processor with a dual processor, means that the throughput of the CPU is doubled. The same can be done for resources such as dynamic random access memory (DRAM) to improve memory performance.
Simpler: Increasing the size of existing systems means network connectivity and software configurations don't change. As a result, the time and effort saved compared to scale-out architectures ensures a simpler scale-up process.
Cost-effectiveness: The scale-up approach is less expensive compared to scale-out because network hardware and licensing costs are much lower. In addition, the use of an extended architecture can reduce the operating costs of facilities such as cooling.
Lower Energy Consumption: Scaling up requires fewer physical devices compared to scale-up, resulting in significantly lower overall energy consumption associated with scale-up.
(3) Disadvantages of vertical expansion
Increased latency: Introducing higher capacity machines may not guarantee faster workloads. For use cases like video processing, latency can be increased in scale-up architectures, which in turn can lead to performance degradation.
Labor and risk: Upgrading systems can be cumbersome, such as having to copy data to a new server. Switching to a new server can lead to downtime and risk data loss in the process.
Aging Hardware: The limitations of device aging lead to reduced effectiveness and efficiency over time. For example, backup and recovery times are examples of performance and capacity degradation that negatively impact functionality.
Scale out
Scale-out infrastructure replaces adding hardware to expand functionality, performance, and capacity. Scale-out addresses some of the limitations of scaling up infrastructure because it is generally more efficient and effective. Additionally, scaling out with cloud computing services ensures that organizations do not need to purchase new hardware when upgrading their systems.
While scale-out allows organizations to replicate resources or services, one of the key differences is streaming data resource scaling. This allows organizations to respond quickly and efficiently to diverse needs.
(1) When is it necessary to scale out infrastructure?
When an organization needs a long-term scaling strategy: The incremental nature of scaling allows organizations to scale their infrastructure to achieve the expected long-term data growth, and they can also add or remove components based on goals.
When upgrades need to be flexible: Scale-out avoids the limitations of technology depreciation and vendor lock-in for specific hardware technologies.
When storage workloads need to be distributed: Scale-out is ideal for use cases where workloads need to be distributed across multiple storage nodes.
(2) The advantages of horizontal expansion
Adopt newer server technologies: Because the architecture is not limited by older hardware, scale-out infrastructure is not affected by capacity and performance issues as scale-up infrastructure.
Adaptability to changing requirements: Scaling out architectures make it easier to adapt to changes in demand, as services and hardware can be removed or added to meet demand demands. This also makes it easy to scale your resources.
Cost Management: Scale-out follows an incremental model, which makes costs more predictable. Moreover, such a model allows organizations to pay for the resources they need as needed.
(3) Disadvantages of horizontal expansion
Limited Rack Space: Scale-out infrastructure carries the risk of running out of rack space. Theoretically, rack space may reach a point where it cannot support growing demand, suggesting that scale-out is not always the ideal approach to meet larger demand.
Increased Operational Costs: Introducing more server resources comes with additional costs, such as cooling and power.
Higher upfront costs: Setting up a scale-out system requires a significant investment, as organizations don't just upgrade their existing infrastructure.
Choose to scale up or scale?
In conclusion, scale-up and scale-out approaches serve different purposes in data center infrastructure. However, the right approach for your organization's business depends on factors such as current performance, cost-effectiveness, and challenges, goals, and use cases.
