Horizontal scaling vs vertical scaling: Choosing your strategy

The narrative is shifting from “Should we embrace the cloud?” to “How can we thrive in the cloud-centric future?” As Gartner predicts, global spending on public cloud services will hit $679 billion by 2024. As investments in cloud services soar, the ability to effectively manage cloud scalability is key for businesses aiming to succeed.

When it comes to cloud scalability, there are two main strategies: horizontal scaling vs vertical scaling. Choosing the right scaling method requires evaluating factors like application architecture, traffic patterns, resource utilization needs, and budget constraints. This article explains horizontal and vertical scaling in-depth, including real-world examples, so you can determine the best fit for your business needs as you scale your operations in the cloud.

Summary

• Cloud scalability is critical for businesses to be able to adjust computing capacity based on fluctuating and peak demand. The two main types are horizontal scaling (adding more servers) and vertical scaling (upgrading capabilities of existing servers).

• Key factors to determine the best scaling approach include traffic patterns, resource efficiency needs, costs, application architecture, downtime tolerance, future growth forecasts, integration with cloud services, operational simplicity, application performance, and workload distribution.

• DigitalOcean’s products like Droplets and DOKS are designed for simplicity and flexibility to scale up or down. Droplets allow for vertical scaling by letting users upgrade CPU, RAM, and other resources without disruption.

What is horizontal scaling?

Horizontal scaling is the process of adding more machines or nodes to a resource pool in a system to distribute the workload. This approach is synonymous with scalability through replication. In simpler terms, if your organization scales horizontally, it means adding more servers to your existing infrastructure to handle an increased load.

Horizontal scaling is like adding more lanes to a highway to accommodate more traffic. Each lane represents a server and the overall capacity increases as more lanes are added.

What is vertical scaling?

Vertical scaling is the process of increasing the power of individual machines in the system. Instead of adding more servers, organizations employing vertical scaling improve the capabilities of existing servers. Vertical scaling upgrades involve upgrading hardware components, such as CPU, RAM, and network speed, adding more resources or storage, to handle larger workloads.

Vertical scaling is akin to expanding the capacity of a single bridge to accommodate more traffic. By making the bridge stronger and wider, it can handle increased load without the need for additional lanes.

Horizontal scaling vs vertical scaling

Horizontal scaling and vertical scaling are key strategies for improving system capacity and performance. Here’s how these approaches align and differ in how they manage increases in workload and resources:

Benefits of horizontal scaling

• Enhanced load distribution: Horizontal scaling distributes workload across multiple servers or nodes, reducing the burden on individual machines. This ensures efficient utilization of resources and prevents bottlenecks, leading to improved system performance and reliability.

• On-demand scalability: Horizontal scaling allows businesses to easily accommodate increasing workload demands by adding more servers to their resource pool. This scalability on-demand ensures flexibility and agility in scaling infrastructure to meet changing business needs without significant upfront investment.

• Fault tolerance: By distributing workload across multiple servers, horizontal scaling improves fault tolerance and system resilience. In the case of hardware failures or server downtime, redundant servers can seamlessly take over, ensuring uninterrupted service availability and minimal impact on operations.

Challenges of horizontal scaling

• Complexity of load balancing: Horizontal scaling introduces the complexity of load balancing, as it requires efficient distribution of incoming traffic across multiple servers. Implementing and managing effective load balancing mechanisms, such as elastic load balancers, adds overhead and complexity to the infrastructure.

• Data consistency concerns: Maintaining data consistency and synchronization across distributed servers can be challenging in a horizontally scaled environment. As data is spread across multiple nodes, ensuring consistency and coherence becomes crucial, requiring robust data replication and synchronization strategies.

• Scalability limits: Despite its scalability benefits, horizontal scaling has inherent scalability limits determined by factors such as network bandwidth, communication overhead, and synchronization latency. Scaling beyond these limits may lead to diminishing returns or performance degradation, necessitating careful cloud capacity planning and optimization.

Horizontal scaling examples

• Load balancers: Load Balancers scale horizontally by distributing incoming application traffic across multiple instances. As demand increases, new instances can be added to the pool, and the load balancer distributes the load and processing power among several servers in a system. This ensures a balanced distribution of traffic to multiple machines.

• Kubernetes: Kubernetes is a container orchestration platform that facilitates horizontal scaling. It can dynamically adjust the number of running instances based on resource utilization and demand, ensuring optimal performance.

Benefits of vertical scaling

• Increased processing power: Vertical scaling improves the processing power and computing capacity of individual servers by upgrading hardware components such as CPU, memory, and storage. This enables servers to handle larger workloads and resource-intensive applications more efficiently.

• Simplified resource management: Vertical scaling simplifies resource management by consolidating workload on a single, powerful server. This leads to less complexity in infrastructure management and eliminates the need for load balancing and distributed data management, streamlining operational processes.

• Cost-efficient for specific workloads: Vertical scaling can be cost-effective for specific workloads or applications that require high-performance computing or specialized hardware configurations. By investing in vertical scalability, businesses can optimize resource utilization and achieve better cost-efficiency for targeted use cases.

Challenges of vertical scaling

• Limited scalability: Vertical scaling has inherent scalability limits determined by the maximum capacity of individual servers. Scaling beyond these limits may require costly hardware upgrades or replacement, leading to potential downtime and operational disruptions.

• Single point of failure: Vertical scaling increases the risk of a single point of failure, as all workload is concentrated on a single server. Hardware failures or system crashes can have a significant impact on service availability and may result in downtime until the issue is resolved.

• Complexity of upgrades: Upgrading hardware components in vertically scaled environments can be costly and complex, requiring downtime for server maintenance and upgrades. Managing hardware compatibility and ensuring seamless migration of workloads during upgrades adds to the operational overhead and complexity of vertical scaling.

Vertical scaling examples

• Virtual Machines (VMs): VMs scale vertically by allowing users to resize the virtual machine to a higher or lower unit. This involves changing the size of the VM to accommodate varying performance and resource requirements such as storage capacity, networking options, etc.,

• Compute services: Cloud computing services across various providers enable vertical scaling by allowing users to resize instances with different configurations and performance levels. This includes adding more CPU cores, memory, or storage capacity to accommodate increased workload requirements. Users can vertically scale their compute resources as needed to maintain performance levels and meet business demands.

10 factors for choosing between horizontal vs vertical scaling

Horizontal scaling is particularly effective for applications that can be easily distributed across multiple servers, such as web applications, content delivery networks (CDNs), and databases. On the other hand, the vertical scaling approach is suitable for applications that may not easily lend themselves to distribution across multiple servers, but require more processing power, such as certain legacy systems or resource-intensive databases.

You can also combine both of the strategies if that suits your business. We have distilled down a few parameters below, which will help you easily decide which scaling strategy suits your business the best.

1. Traffic patterns

Observe how demand fluctuates. Based on how the demand fluctuates in your business, there can be unpredictable spikes or dips in activity. In such a case, you may favor horizontal scaling. It adds or removes computing resources, adapting to varying traffic.

2. Resource efficiency

Assess resource optimization needs. Horizontal scaling keeps the existing pool of computing resources online and adds more to what is already present. For consistent, high-resource demand, vertical scaling may be efficient. It boosts existing capabilities without the need for added infrastructure.

3. Cost considerations

Evaluate budget flexibility. Considering the cost perspective, vertical scaling may offer budget stability but can be pricier for frequent adjustments. Horizontal scaling might offer a high-cost set-up environment but might be cost-effective in the long run.

4. Application architecture

Examine system design and dependencies. If your applications are designed to run on multiple servers, lean towards horizontal scaling. For applications reliant on a single robust server, vertical scaling may be more suitable.

5. Downtime tolerance

Determine tolerance for system interruptions. Horizontal scaling often facilitates less downtime, making it suitable for businesses requiring high availability. Vertical scaling may involve brief downtimes during upgrades.

6. Future growth forecast

Anticipate long-term scalability needs. If your business expects consistent and substantial growth, a combination of horizontal and vertical scaling (hybrid approach) may provide the necessary flexibility.

7. Cloud service integration

Consider third-party cloud services. Horizontal scaling aligns well, utilizing the distributed nature of cloud infrastructure. Vertical scaling can simplify operations when using a single robust cloud server.

8. Operational simplicity

Assess ease of management. Horizontal scaling is often simpler to manage, especially for distributed systems. Vertical scaling may involve more complex adjustments to a single server.

9. Application performance

Prioritize consistent performance. For applications where consistent performance is critical, vertical scaling ensures dedicated resources, improving overall system performance.

10. Workload distribution

Examine the nature of workloads. Horizontal scaling excels in distributing workloads across multiple nodes. Vertical scaling suits scenarios where a single machine can handle the entire workload efficiently.

Scale confidently with DigitalOcean

DigitalOcean offers a suite of cloud infrastructure products designed to simplify cloud scaling, empowering developers and businesses to grow without complexity. The platform makes both horizontal and vertical scaling achievable through offerings tailored to accommodate fluctuating workloads.

Here’s how you can harness DigitalOcean’s products to achieve cloud scalability:

• Droplets: You can seamlessly implement vertical scaling through Droplets. They are DigitalOcean’s Linux-based virtual machines that run on top of virtualized hardware. They can be effortlessly customized to meet evolving requirements. With diverse performance types, including Standard, General Purpose, CPU-Optimized, or Memory-Optimized Droplets, you can align your computing resources precisely with your application’s demands.

• Kubernetes: For the best horizontal scaling, we have DigitalOcean Kubernetes (DOKS). It streamlines container orchestration with a managed service that simplifies deployment, management, and scaling of containerized applications using the open-source Kubernetes platform, devoid of Kubernetes management complexities.

• Spaces: Catering to vast amounts of unstructured data such as videos, images, and backups, Spaces offer scalable storage sans the intricacies of traditional storage system management, ensuring seamless scalability.

• Volumes: DigitalOcean’s block storage solution, Volumes, empowers you to scale your storage effortlessly by attaching additional storage to Droplets, with the flexibility to resize as necessary, ensuring storage scales alongside your application.

• App Platform: As a scalable platform-as-a-service (PaaS) solution, App Platform automates infrastructure management tasks like updates, scaling, and security, supporting multiple programming languages and frameworks for quick app deployment and scaling.

• Load Balancers: DigitalOcean’s fully managed Load Balancers efficiently distribute traffic across your infrastructure, adeptly handling traffic spikes, and optimizing performance and computing power to uphold application availability and performance amid increasing demand.

Each of these products seamlessly integrates within DigitalOcean’s ecosystem, delivering a unified experience that simplifies the scalability journey. With transparent pricing models and robust community support, DigitalOcean fosters an environment conducive to growth-focused businesses.

Seeking stress-free cloud scalability? DigitalOcean has your back—experience effortless scaling today and establish a robust cloud infrastructure that supports the ascent of your business.