Empowering Growth: The Importance of Performant Scalable Architecture
Empowering Growth: The Importance of Performant Scalable Architecture
Key Principles and Best Practices for Scalable Architecture and Future-Proofed Growth
Scalable architecture is foundational for business growth. It's not merely a technical decision but rather a strategic imperative essential for supporting growth and gaining a competitive edge.
In the previous article, we delved into scalability from a functional standpoint, examining the system’s flexibility to evolve in terms of functionality without the need for significant reengineering.
This article shifts the focus to scalability from a performance perspective, often referred to as Performance Scalability, or simply Scalability.
What is Performance Scalability
Performance Scalability refers to the ability of a system to handle increasing traffic (Load Scalability) and data volumes (Data Scalability) without compromising its responsiveness or speed. In this context, Scalability ensures that the system can maintain its speed and responsiveness as demand grows over time.
As the business expands, the number of users placing load on the system grows as well. This creates pressure to the extent that the initially allocated resources become insufficient to handle the increased load. Consequently, the system needs to "scale," necessitating additional resources to accommodate the increased load.
Scaling can take two approaches.
Vertical scaling, also known as scaling up, involves enhancing the resources of a single server or machine to manage higher loads. This may include upgrading the CPU, memory, storage, or other components to boost performance and capacity. However, this approach has limitations in terms of scalability and cost-effectiveness.
Alternatively, horizontal scaling, also referred to as scaling out, entails expanding the system by adding more servers and distributing the workload across them.
Scalability vs Elasticity
A special type of scalability is elasticity. Although similar in concept, these terms have distinct meanings.
Scalability refers to the system's ability to manage gradual increases in traffic and data as the number of users grows. As the load gradually increases over time, the ability of the system to scale only manually is often sufficient.
However, there are instances where gradual scalability is not sufficient, and the system requires support for elasticity. Elasticity refers to the system’s capacity to handle sudden peaks in load and swiftly return to normal behavior afterward.
To achieve elasticity, the system must be capable of automatically scaling servers based on the current load. Alternatively, dedicating excessive capacity upfront is an option, but this is of course not desirable, as it leads to underutilization during periods of low demand and therefore unnecessary high costs.
A typical example illustrating elasticity is a platform for purchasing tickets to a newly released movie. When ticket sales open, there is a significant surge in traffic as everyone attempts to buy tickets before they are sold out.
An elastic system would seamlessly manage this increased traffic without any disruption. However, a system lacking scalability and elasticity will struggle to cope with the new situation. This could result in broken system performance or even make the system completely unavailable during peak periods.
Scalable Architecture is a Business Choice
Scalable architecture is often seen solely through a technical lens. Yet it's crucial to recognise that this is a strategic decision. Investing in a scalable architecture should be driven by clear business needs and aligned with broader organisational objectives.
The benefits of this architecture include:
Cost-effective growth: Cost is the primary driver for scalable architecture. While investing in expensive migration to scalable architecture might not be justified for businesses with stagnant growth, it is crucial for growing businesses anticipating an increased customer base. Scaling the architecture becomes a pivotal asset and a key enabler for growth.
Agility: Scalable architecture (both functional and performance scalability) brings a significant benefit in agility. A company supported by an agile software landscape has the advantage of swiftly adapting to evolving business needs, whether it involves entering new markets, introducing new products or services, or adjusting to changing customer preferences.
Resilience: Businesses supported by a scalable foundational architecture can maintain uninterrupted operations even amidst unforeseen challenges such as sudden spikes in traffic, hardware failures, or cyber threats. This not only reduces operational costs and headaches but also enhances the user experience.
Competitive advantage: Scalable architecture provide a significant competitive advantage. By fostering agility and adaptability to new market conditions and enhancing user experience, companies supported by scalable foundations can outpace competitors.
How to Achieve Scalable Architecture
There is no simple blueprint for building a scalable architecture. It demands expertise, a scalability mindset, and an understanding of the business. Let's review the key principles to consider when aiming for scalable architecture.
Understand your scalability needs
Designing an architecture involves striking a careful balance of trade-offs and considering various "what if" scenarios. Understanding the business goals is essential for this task.
Questions such as who the end customers are, their expectations, the projected number of users, and potential growth are crucial. Additionally, identifying peak periods of activity, assessing the business impact of system failures, and determining the need for handling confidential data are key considerations.
The defined business goals drive the architecture principles and guidelines for implementation. These aspects should not only exist on paper but should be deeply integrated into the product organization. Designing a system that requires 99.999% uptime differs significantly from one where occasional downtime may be tolerated without significant impact.
Embrace decoupling from the start: transition to services when ready
Large monolithic applications are difficult and expensive to scale due to their single deployable unit nature. Scaling such applications requires scaling the entire system's functionality, resulting in rapidly escalating costs.
A fundamental principle for achieving scalability is to break down a large codebase into services. These smaller deployable units can be maintained, deployed, or scaled independently. This approach is known as service-oriented architecture (SOA) or micro-services architecture when the services are more granular and there is also separation of data.
To promote high scalability of a larger system, this pattern is inevitable. However, moving to micro-services architecture must be approached carefully, as it has its own downsides.
The shift from in-memory to network-based communication between services introduces latency and performance concerns. Imagine substituting an existing call to a component in a loop with a network call; this could cause substantial performance degradation and potentially lead to system failure.
Micro-services often depend on each other; a failure in one service can trigger cascading failures. System success depends on how well the system is designed for resilience and the failover mechanisms implemented.
Security poses a greater challenge with micro-services as they expose individual APIs. Establishing security measures in the distributed environments becomes critically important.
Maintaining and managing micro-services is inherently more complex compared to monolithic applications, yet when executed effectively, it offers significant advantages.
Transitioning directly to micro-services is not recommended. Instead, it is advisable to begin with a modular architecture and decoupled components. This approach ensures that as the codebase expands, transitioning to separate services becomes much more manageable.
Coding best practices can make a significant difference
Ensure that best practices are applied during coding to optimize application performance before considering scaling. This involves implementing efficient algorithms and adhering to coding guidelines. For instance, minimizing the use of complex nested loops, leveraging caching mechanisms to reduce traffic between components, and optimizing communication between distributed components can significantly enhance application efficiency.
Developing with a performance-oriented mindset can yield substantial improvements in application performance. While these optimizations have their limitations and scaling at a later stage would still be necessary, they can mitigate the need for unnecessary early scaling, ultimately resulting in cost savings for the business.
Stateless services
A fundamental principle of scalable architecture is the use of stateless services, essential for enabling horizontal scaling. The concept revolves around ensuring that each request to a service is self-contained and independent of past interactions (state). This approach simplifies the distribution of incoming traffic across multiple service instances.
Asynchronous communication
Another crucial principle is minimizing synchronous communication between services. Asynchronous communication decouples system components, enabling independent operation without reliance on one another to complete tasks. Implementing asynchronous communication patterns enhances overall system performance, system responsiveness, and resource utilization.
Utilize cloud services
Cloud platforms provide elastic resources, auto-scaling capabilities, and managed services, simplifying scalability. This can yield significant benefits, positively impacting costs and scalability.
However, migrating to the cloud doesn't automatically resolve all issues. Many organizations are embracing this trend, only to realize that simply lifting their applications to the cloud without proper preparation does not yield the expected benefits. While the cloud offers great potential, applications need to be cloud-native and need to follow the practices mentioned above to fully leverage its advantages.
Monitor, analyze and optimize
Monitoring is essential for achieving optimal system performance. Utilizing monitoring and analytics tools can provide valuable insights into system performance, scalability, and resource utilization. This becomes particularly important in a micro-services setup, where identifying and resolving slowdowns within the network of services is essential for maintaining overall system efficiency.
Building a Scalable Architecture in an Agile World
Making the right architecture choices is crucial for creating a future-proof system that can adapt and grow alongside your business needs. However, this can be challenging in today's agile environment where the future is unpredictable.
According to Gartner's report on "From Fragile to Agile Software Architecture" (2019), traditional architectural practices often clash with modern agile software development methodologies, leaving teams without clear guidance on how to architect their systems effectively.
It's important to recognize that building great architectures is a gradual process that requires continuous iteration, feedback, and adjustment. Take, for example, companies like Uber or Spotify, known for their flexible microservices architecture. These architectures evolved over time through iterative development and refinement.
As Adam Gluck from Uber Engineering puts it,
"Evolving a microservice architecture is more like 'trimming a hedge'—a dynamic and progressive process—rather than a one-time, top-down effort."
This blog is part of the series on Scalable Software Architecture. Below, you'll find an index of the articles in this series:
The Software Development Reality: The Need for Scalable Architecture
Empowering Growth: The Importance of Performant Scalable Architecture
How to Establish Architecture Principles for Successful Scaling
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