Most entrepreneurs don’t start a business with the goal of staying small forever. And the volatility of the market for any industry makes it impossible to accurately predict changes in demand. For those two reasons, scalability is an incredibly important concept to consider. In this article, we will explore what cloud scalability is, why it’s so important to enterprises, the benefits of cloud scalability opposed to on-premise architecture, the different types of cloud scalability, and software that can help make cloud scalability even easier. Let’s begin.
Cloud Scalability
Cloud scalability is the ability to increase or decrease IT resources — such as processing power, networking ability, and data storage capacity — with minimal to no disruption to operations. One of the major benefits of choosing the cloud over on-premise architecture is the ability to scale quickly and easily. On-premise solutions require weeks or months to overhaul infrastructure. With cloud, third-party providers (like AWS) already have infrastructure in place and can add IT resources to achieve desired goals. Then, once the need for additional resources is gone, organizations can revert back to their original configurations with ease.
When referencing scalability, it’s important to introduce cloud elasticity into the conversation. Similar in concept to scalability, it’s the system’s ability to expand and contract based on workload demands. Time is the key difference between scalability and elasticity. Cloud scalability is for long-term, strategically planned growth while elasticity is required for short-term bursts.
3 Types of Cloud Scalability
Scalability is not a one-size-fits-all. Scaling is dependent on the requirements of data and compute power. To meet needs, businesses can choose the type of scalable cloud architecture that will best suit their environment. The types of cloud scalability include:
Vertical scaling involves moving up or down. To scale vertically means to change the existing infrastructure, either increasing or decreasing its power. For this type of scaling, no code alterations are needed. Rather, changes involve specs—like CPU and RAM on machines and I/O resources—to a present server. Capacity limits and server size can curtail growth, which may affect performance.
Horizontal scaling is also known as scaling in or out. As organizations grow and requirements include greater capacity, storage, memory, etc., additional servers can be used, working as a singles system. Because additional servers are involved, horizontal scaling is viewed as more complex and labor-intensive than vertical scaling.
A combination of vertical and horizontal scaling, organizations can grow vertically until reaching limitations, then choose to scale out horizontally with additional resources. Organizations experiencing unpredictable surges can benefit from this type of scaling, allowing for agility and giving flexibility to scale in accordance with business demands.
Running Software in the Cloud
Organizations use cloud scalability to meet changing needs during periods of growth or slow/downtime. Achieving scalability is dependent on the cloud model used. Public or private, abundant resources are available for organizations to meet business demand. Scaled solutions can be a request made to a vendor or implemented directly by the organization. Further, some solutions can be auto-scaled as scaling is based on previously set conditions. Kubernetes is one such cloud solution offering this capability.
Kubernetes is software that automatically manages, scales, and maintains multi-container workloads in desired states. It turns a collection of physical or virtual hosts (servers) into a platform with the ability to host containerized applications, keeping them healthy and available while adapting to change.
Features of Kubernetes on AWS:
- Running applications at scale
- Moving applications
- Running anywhere
- Adding new functionality
- Ability to access more plugins and extensions; improving management and security
- Increasing the portability of your applications using a combination of cloud-based and on-premises systems
Best Practices of Running Applications in Cloud
It is important to have a firm understanding of the benefits the best cloud practices can bring to your organization. Understanding helps you in knowing why it is a good fit for your company before you start using it. Given below are some of the best practices for running applications in cloud.
- Take your time with the design pattern
There are numerous design patterns that can be used simultaneously; they are not exclusive. Your choice of design pattern(s) should be in line with the objectives and business priorities of the app. A gatekeeper design pattern might be effective if security is of the utmost importance because it lessens the application’s accessibility to the internet.
- Don’t compromise in terms of security
Organizations need regulations to ensure secure development in the best practice. Developers ought to make plans to increase the security of application data. This applies to information kept both internally by the application and externally, such as in an object storage service. Enable access control and data encryption in all storage location across your cloud infrastructure.
- Be strategic while using serverless
Platforms enabling serverless computing—at least natively—only support programs written in particular languages or frameworks. Developers occasionally utilize wrappers to conduct serverless functions that a particular platform doesn’t natively support. But doing so involves extra work and could harm performance.
Database Scalability Example: AWS RDS
In terms of scaling, Amazon RDS allows for both vertical and horizontal scaling to ensure application demands are being met. Vertical scaling involves adding more database capacity, chiefly to storage and compute of relational database, while horizontal scaling relates directly to increasing performance, extending database operations.
Amazon RDS Proxy is an additional way of scaling your database. This database proxy for RDS enhances the scalability, resilience, and security of applications. Database memory and compute resources can be exhausted as database connections open and close at a high rate. Having a large number of open connections to the database server, many applications, including ones built on modern serverless architectures can cause this issue. However, database efficiency and application scalability can be improved as Amazon RDS Proxy permits applications to pool and share connections established with the database.
Cloud Scalability for Agile Growth
In the ongoing debate between cloud computing and on-premise architecture, scalability is a major talking point. The ability to increase workload size within an existing structure is important for a growing organization. Cloud scalability offers key advantages over on-premise infrastructure including reduced costs, ease of IT management and faster deployment. And no matter if an enterprise is scaling vertically, horizontally, or diagonally, running software like Kubernetes on AWS makes cloud scalability even easier by automating software deployment, scaling, and management.
The total amount of data stored in the cloud by 2025 is expected to reach 100 zettabytes. A staggering number that will account for 50% of the world’s data at that time. The $180-billion cloud market is currently led by Amazon Web Services (AWS). With so many companies adopting the cloud, scalability is a critical issue that should be at the forefront for business.
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This article was cowritten with Dhaval Soni
Also read: Cloud Computing trends that will rule in 2024
