Change is one of the critical aspects that decide an enterprise’s future. While change fosters growth, enterprises either have to expend many resources or shed some non-essential systems. In traditional business houses, coping with change is a big deal as one would have to make the changes quickly, which is not something that everyone can perform deftly.
To boil it down, the organizations would have to add or shed some of their servers to handle the change in demand. While this is a complex task for the traditional legacy business houses, enterprises that have integrated with cloud technology experience seamless scaling technologies.
But why is this scalability so strongly associated with cloud computing? Regardless of whichever sector you are in when dealing with the cloud, scalability is one of the aspects you keep encountering. And while scalability makes the cloud outclass the traditional setups, certain intricacies are involved.
In this blog, we shall explore scalability, what these vertical and horizontal scalabilities are, and which one to choose.
Scalability
Whenever there is a peak stage, one needs more resources to capitalize on the time. Once the demand peaks, the user is left with unwanted resources, which metaphorically collect dust. In day-to-day life, it is like having an unmown lawn. To maintain it, you get a lawnmower and restore the lawn to its beauty. But once the job is done, you have to tuck away the lawnmower until the next mowing session.
Instead, you don’t have the lawnmower in the cloud and don’t wish to have it around unless you need it. You can borrow tools from your neighbors to do the job. Once the job’s done, you can return it, and with that approach, you don’t have to own a resource you only need during certain times.
The same is true with the cloud; you need to rope in extra resources only when needed and pay up only for what you use. These resources can range from extra storage to additional RAM power. Effectively, scalability takes on resources when required and during lean periods, shedding unwanted resources to save monetary resources.
What makes cloud scalability lucrative for businesses is instant availability. While there are predictive spikes, there is always a sudden surprise spike in traffic, and it demands stunted latency without downtimes. Thankfully, cloud providers make the required resources available within no time.
Now that scalability has been delved into, let’s look at vertical and horizontal scaling.
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Vertical Scaling
Vertical scaling refers to the up-scaling process where your infrastructure’s computational capacity is boosted to mitigate the new requirements. This process, also called scale-up, allows you to retain the resources in the existing logical unit. As a result, the infrastructure’s network capacity, storage power, and processing ability will be expanded.
Horizontal Scaling
In horizontal scaling, computational power and devices are pulled into the picture. Here, you add more devices and distribute the existing computational capacity over the existing and additional devices. So, while there won’t be a spike in computational power, the devices across your infrastructure would increase. This distribution is what separates horizontal scaling from vertical scaling. It is also called scaling out.
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Vertical Scaling vs. Horizontal Scaling
Although scalability is mainly associated with computational power, hardware is the key aspect that sets horizontal scaling apart from vertical scaling. In vertical scaling, the hardware configuration is enhanced without disturbing or modifying the logical unit. In horizontal scaling, the hardware specifications remain the same while the number of instances spikes up. In other words, the hardware infrastructure is increased by adding more devices with the same specifications.
The other aspect they differ upon is that a sequential piece of logic is broken into smaller units and implemented on multiple devices in horizontal scaling. The breakup of the code allows programmers to execute multiple tasks parallelly over different devices. Vertical scaling is not the case, as the logic code remains unchanged. The unchanged code is run across the boosted infrastructure. With the differences out of the way, let’s look at the advantages of both scaling methods.
Pros and cons of Vertical Scaling and Horizontal Scaling
As with everything, both scaling methods have advantages and disadvantages. Both approaches differ, particularly in code and hardware. Vertical scaling does not involve a code change and is much easier to execute than horizontal scaling. The operations are easier to manage, and the data centers on one node.
This centralized node allows you to run operations across multiple devices. In addition, vertical scaling reduces expenses as your infrastructure footprint doesn’t increase. This boils down to the company not dedicating extra monetary resources to power consumption and cooling units. Additionally, managing the network from the nodal device is more straightforward and better from the control point.
The disadvantage of vertical scaling is that your hardware can only expand up to a specific limit. Though one can always boost the hardware on certain aspects, the scope to expand it holistically narrows down significantly. Also, one would have to shut down the required devices whenever they are scaling up, resulting in downtime. Additionally, the nodal device has to be taken care of, as unexpected downtimes from that device would stunt productivity.
Horizontal scaling scores well on these aspects. One just adds additional devices to consume the existing power. There is no downtime involved, and you can choose how many devices you choose. Additionally, the nodal control mechanism doesn’t exist in this scaling approach, which betters resilience. However, it runs aground on the data aspect. The data must be partitioned into multiple units due to multiple devices. This partition also complicates data sharing and processing.
Deciding Factors
With both approaches scoring over each other, it boils down to a few crucial aspects that help you decide which one to take.
Costs Involved
Vertical scaling requires you to spend at the onset of the adoption itself. You will pay for the higher power, and effectively, it fares well in the initial stages. In horizontal scaling, you wouldn’t have to pay up much at the onset of the scaling process. You would be required to pay up for the devices when you opt for them, but later on, your cost overheads would crop up in the form of cooling systems and space requirements.
Clientele
Horizontal scaling allows you to circumvent latencies and outages. You don’t have to shut down the servers to implement the scaling process. However, if the customer base is localized and if the burgeoning requirements demand higher processing power, it would be better to adopt a vertical scaling process. As the latencies and outages are involved, your clientele should be okay with such aspects.
Performance
Vertical scaling reduces your flexibility to a certain extent, as today’s technology limits you. In this approach, you wouldn’t be free to choose whatever you wish. In horizontal scaling, you can choose the required configuration and optimize operational costs.
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Trouble Deciding?
While the choice seems easy, scaling is decided by your infrastructure’s architecture and other factors. Also, you should realize that vertical and horizontal scaling is not a choice one should always make. One can implement both the scaling processes and reap its benefits.
While it sounds easy, improper scaling would stunt your production process and demand higher monetary resources. To avoid this, Fortune 500 companies and emerging companies have hired Veritis to improve their production processes.
So, reach out to us and scale your infrastructure as best as possible.
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Additional Resources:
- EKS Vs. AKS Vs. GKE: Which is the right Kubernetes platform for you?
- A Guide to DevOps Implementation on Google Cloud
- Serverless Vs Containers: Comparison Between Top Two Cloud Services
- AWS vs Azure vs GCP: Cloud Cost Comparison
- Top 10 DevOps Tools to Pick for Your Business
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