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Vertical Scaling vs. Horizontal Scaling

What is Vertical Scaling vs. Horizontal Scaling?

When deciding between horizontal and vertical scaling, it is crucial to consider what qualities of the service you value most, your budget constraints, and your feelings towards additional maintenance. Both methods have their own advantages and drawbacks, so it's important to weigh these factors carefully before making a decision. By evaluating these aspects thoroughly, you can ensure that your scaling strategy aligns with your organization's needs and resources, leading to a more effective and efficient infrastructure setup.

Scalability and Increasing Demand

Scalability is defined as how flexible a system established in the cloud is. Typically, this is applied in situations when describing if an application can accept higher traffic or lower traffic without suffering too much strain. This will severely impact how a website, web service, or application is, especially if it frequently sees user traffic that fluctuates. The more flexible a service is, the less likely it is to crash or cause widespread issues in the user experience.  The two main methods of scaling are horizontal scaling and vertical scaling.

Horizontal Scaling

Horizontal scaling provides additional nodes or computing assets to your system to better tolerate traffic. This approach is designed to add more units to process a workload and is limited by the physical capacity of servers hosted on the service. The purpose is to provide more nodes closer to some areas of the network or to offer more nodes in a particular region for users to access, or to have if any node experiences outages. In simpler terms, consider horizontal scaling as akin to increasing the number of call center employees to handle more calls simultaneously, rather than expecting a single employee to handle all the increased load.

Horizontal Scaling

Advantages

  • Generally speaking, horizontal scaling is fundamentally straightforward when adding hardware. It simply involves integrating more machines into your existing system, sidestepping the need to analyze and upgrade system specifications. This makes scaling an easier and more flexible process.
  • It usually results in fewer interruptions. By adding or removing machines, operations on existing machines remain unaffected, essential for maintaining continuous service availability and minimizing client impact.
  • This approach also enhances fault tolerance significantly. With data and operations distributed across multiple nodes rather than concentrated in a single location, the risk of total system failure and data loss is substantially reduced. This distributed model protects your operations by preserving functionality even if one part of the system goes down.
  • Having additional machines means improved handling of network traffic. This setup creates more endpoints, allowing for better distribution of load across the system, which can reduce bottlenecks and enhance overall efficiency.

Disadvantages

  • Managing a horizontally scaled system comes with its own set of challenges. More machines mean more elements to manage and maintain. The necessity for load balancing and virtualization software becomes more pronounced as these tools are crucial for evenly distributing workloads and managing multiple instances effectively. This complexity can lead to issues with synchronization and internal communication, which are vital for seamless operations.
  • The financial aspect cannot be ignored. Expanding your hardware infrastructure by adding more machines generally incurs higher upfront costs compared to simply upgrading existing servers. This initial investment can be a significant consideration for any business.
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Use Cases

Whether it is once per year or a constant problem bombarding business operations, horizontal scaling should be considered. Despite its shortcomings, horizontal scaling is optimal for providing good performance for services that are dependent on a stable connection to the end user. Depending on how much traffic the service usually gets, this can result in very efficient price performance. Using proper microservices, performance can remain stable across all instances with careful planning.

More machines are also suitable for avoiding outages and how catastrophic they can be. If servers are more evenly distributed across global regions, end-users will receive both better performance and a reduced likelihood of one damaged node preventing access to the service entirely. With other instances capable of alleviating the burden of traffic, updates and upgrades can come more readily.

In scenarios where high performance is crucial to maintaining high-quality service, horizontal scaling is an invaluable strategy. It is particularly beneficial when running your application or services across different geographical locations to ensure low latency. The flexibility to configure machines in various ways also allows for optimal efficiency, specifically improving the price-performance ratio.

Horizontal scaling can be helpful when regular updates, upgrades, and optimizations are needed — all while aiming to minimize downtime. This approach is especially important for businesses experiencing consistently high usage, user growth, or traffic spikes expected to grow exponentially.

For those utilizing a micro-services architecture or containerized applications, horizontal scaling performs better on a distributed system. It also provides the necessary backup machines to reduce single points of failure, enhancing the overall resilience and reliability of the infrastructure.

Vertical Scaling

Vertical scaling refers to adding more power to your existing machines. This could involve upgrading the CPUs, expanding the memory, enhancing storage, or increasing network speeds. Essentially, vertical scaling is about enhancing the capabilities of your current infrastructure to meet demand, similar to giving that single call center employee a faster computer and better tools to manage more calls effectively.

Vertical Scaling

Advantages

  • Vertical scaling is reasonably cost-effective in the long term. The cost is comparatively low since the service providers merely upgrade existing nodes instead of buying new units. Once the unit is back online with the replaced components, maintenance will remain the same. With no new units brought online, there’s no need to make backups or implement virtualization software.
  • Upgrading a pre-existing server costs less than purchasing a new one and simplifies maintenance. You are less likely to require additional backup and virtualization software, potentially stabilizing maintenance costs. Furthermore, when a single node handles all the layers of your services, it eliminates the need for complex synchronization and communication with other machines, leading to faster response times and less complicated maintenance.
  • Offers a simpler management scenario by upgrading existing hardware’s capabilities. While avoiding the complexities associated with networked instances, it is essential to consider the limitations inherent in this approach. Fewer nodes mean fewer instances requiring management and synchronization, simplifying the overall process. Similarly, software upgrades are less likely to happen, reducing the need for frequent software changes.
  • Unless several nodes are being upgraded, there is typically less need to synchronize communication between nodes, and software upgrades are less likely to happen as a result.
  • Maintenance costs would be cheaper than horizontal scaling because there are fewer nodes to upkeep. This streamlined approach not only makes vertical scaling a cost-effective option, but it also reduces the complexity involved in managing multiple machines and software environments.

Disadvantages

  • The risks imposed by downtime are significantly higher in vertical scaling. With fewer nodes at play, having one or two units down for maintenance could spell disaster since fewer nodes could work as backups. This aspect becomes crucial unless you have a backup server ready to handle operations, necessitating considerable downtime for upgrades.
  • Similarly, having fewer nodes risks losing all your data. If all your important data is being kept on a single server, losing that server could cost all the information kept on it. This creates a single point of failure, dramatically increasing the risk of catastrophic data loss should any hardware or software failure occur.
  • You can only upgrade the hardware so much. There are physical limitations to what CPU is implemented or how much RAM, storage, and processing power is on a single node. If you focus exclusively on upgrading vertically, expanding horizontally will eventually become the only option. Each machine has its threshold for enhancements, and once these limits are reached, no further upgrades can be made without transitioning to new or additional hardware.

Use Cases

This topic must be discussed with the group’s engineers and stakeholders. All parties need to plan what CPUs and memory would be beneficial and how it would be possible to deliver on the price performance for such an upgrade. Regardless of the risks, vertical scaling tolerates much more sporadic traffic and is worth considering if the users are relatively new to the cloud. If redundancy is not a concern, additional upgrades are far and few between, and vertical scaling will be sufficient. Though it is recommended against legacy apps that don’t require distribution or scalability, they will benefit from vertical scaling.

Vertical scaling excels in managing sporadic traffic patterns and can be a valuable choice, especially for users who are new to cloud environments. It is particularly beneficial when redundancy is not a primary concern and upgrades are infrequent. However, it is essential to note that vertical scaling is not always the ideal solution for legacy applications that do not require distribution or scalability. These applications, which may not parallelize well or have architectural constraints limiting their efficiency across multiple machines, can significantly benefit from vertical scaling. By considering the computational power requirements and scalability limitations of the workload, organizations can make an informed decision on whether vertical scaling is the most suitable approach for their specific needs.

Determining the Best Path

Cost can often play a crucial role in deciding between different scaling options. While you may have specific goals or requirements for your organization, ultimately, the cost associated with each option may heavily influence your decision-making process.

For example, while horizontal scaling may seem like the ideal solution from a functional perspective, the financial resources required for implementation could be a determining factor. Your current budget may not allow such a scaling strategy, leading you to explore other alternatives. In such situations, it’s essential to consider all available options beyond just on-premise vertical and horizontal scaling. Migrating your infrastructure to a cloud service provider, for instance, could provide a cost-effective solution that also simplifies the scaling process.

To accurately assess the cost implications of different scaling options, you might consider utilizing a cloud cost management platform. This tool can help you evaluate and compare the expenses associated with on-premise scaling versus cloud solutions, allowing you to make an informed decision based on both current and future expenditure projections. By thoroughly analyzing the financial aspects of each option, you can determine which approach aligns best with your budget constraints and long-term financial objectives.

Using either method of scaling needs to be carefully evaluated before dedicating. Especially if the application is experiencing moments of high traffic and is subsequently suffering from it, either action should be considered for the health and wellbeing of the service. That is not to say either should be considered exclusively and that it isn’t possible to accomplish a mix of both.

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Dolan Cleary

Dolan Cleary

I am a recent graduate from the University of Wisconsin - Stout and am now working with AllCode as a web technician. Currently working within the marketing department.

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