Scalable Architecture
A horizontally scalable technology architecture controls costs and ensures your systems keep pace with your growth.
Scalable architecture isn’t just tech jargon — it’s the difference between capitalizing on growth and scrambling under pressure. Scalable architectures flex with demand, reduce recurring costs, and keep customers happy.
These systems are built to grow without breaking the bank or damaging your brand. They handle more users, orders, and data, while keeping performance steady. Scalable architectures create the opportunity for profitable growth, allowing you to outpace rivals saddled with rigid systems.
How It Works
There are two models for scaling that your team can leverage:
- Add Power (Vertical): Scale up the entire system at once
- Add Workers (Horizontal): Scale up discrete parts of the system as needed to meet demand
Scalable architectures aren’t optional—they’re table stakes in a world where growth punishes the unprepared. They control costs, protect revenue, and allow you to take advantage of opportunities to grow your business.
Aligning Architectural Choices with Evolving Business Needs
Architecture is a living entity, growing and evolving with your business to accommodate expanding customer bases, increasing revenue, and adapting to fluctuating business needs. The architecture you choose significantly influences your system’s capacity to efficiently scale and adapt to transformational requirements, directly affecting performance, efficiency, and cost.
Selecting the right software architecture patterns is an important part of your scaling strategy. Patterns such as microservices, event-driven, service-oriented architecture (SOA), and even monolithic all offer unique advantages, but also come with unique limitations.
Our Insights: Gotta Keep ‘Em Separated: Building Scalable Architecture →
A Ten Mile Square expert can work with you to determine the best plan for your unique enterprise.
How to Create a Scalable Software Architecture
Business and product leaders consider several factors when planning for a scalable architecture. It usually starts with an eye toward horizontal scalability and scaling discreet aspects of the system independently. Design decisions need to factor in deployment costs, data architecture, security, potential system/process bottlenecks, currency (real-time / batch), expected data growth, and the desired user experience.
1. Truly Scalable Architecture Requires a Horizontal Scaling Model
Horizontal Scaling
Horizontal scaling allows you to scale up discrete parts of a system, rather than the entire system, to meet demand. Scaling horizontally not only is significantly more cost-effective, but also enables effective auto-scaling, gives you more control, and reduces the time it takes to evolve your system.
Vertical Scaling
By contrast, vertical scaling requires you to scale up the entire system at once. Classic relational databases are a prime example of this. Need more compute? Redploy the whole thing on a bigger server and migrate the data into it. While modern cloud architecture has made it easier to architect and deploy horizontally scaling systems, vertically scaling monoliths are often used for prototyping and validating product market fit as they can be faster to iterate during early days before scale is an issue.
Microservices
Microservices architecture breaks down software programs into smaller components. Each microservice has one function, so it can be scaled to the exact level you need, making them independently deployable or upgradable. Microservices help you scale efficiently in the cloud using horizontal scaling and workload partitioning – resulting in faster deployments, cost efficiencies, and granular performance tracking. Many recognize Netflix’s pioneering move to replace its monolithic software design with smaller components decoupled into 1,000 microservices for discrete functions, such as login, search, stream a movie or update your profile.
2. Design for Scalability to Control Your Operational Costs
Architecture design decisions will affect operational costs.
Our Insights: Who’s Really in Control of Total Cost of Ownership (TCO) →
Before making any decisions, ask:
- Do your architectural decisions consider impact on deployment costs? Many developers write code to optimize the solution to the problem they are handed, but not necessarily the efficiency of the cost model for running the solution.
- Do you know, or can you predict, where load stressors and bottlenecks on the system are?
- Do you have a model that predicts user load/usage scenarios?
- Do you have a scaling model that predicts the amount of compute (cpu, mem, i/o, etc) resources that will be required under predicted load/usage scenarios?
Flexible, Scalable Architecture for Media Platform
- Scaled our platform to accommodate 7x the number of customers
- Lowered company’s cost by reusing current data systems
- Leveraged our AWS partnership to quickly solve a new customer need
- Built rights management system to serve a $100B+ media customer
3. Database Scalability Is a Common Scaling Bottleneck
Most relational databases were designed using older technologies that supported vertical scaling. As a result, databases are a common cause of scaling issues. There are a number of ways to solve database scalability including:
- Managed databases: A managed relational database service (RDS), like Amazon Aurora, allows you to move your database to an open-source, cloud database. This lightens the load of moving to a horizontally scalable database, but it may require some changes first.
- Clustering: Clustering technology may be an option that can move your database architecture closer to horizontal scaling.
- Sharding: A replica database and sharding is another option (think of it as “horizontal partitioning” to spread the load). For instance, if you have an enterprise relational database that you plan to stay on, you may find it easiest to use master replication and sharding to make it more scalable.
- Non-relational and NoSQL databases: Consider cloud-native databases that are built to avoid relational database scaling challenges. Options include CloudSpanner, BigQuery, Redis, MongoDB, and Neo4J.
Increased Database Scalability by Migrating to Aurora
- Looking at how the database was being used compared to its business goals
- Analyzing its existing architecture and alternative database architectures
- Conducting a cost comparison, which found migrating to Amazon Aurora would best meet their seamless scalability needs
4. Load Balancing Is Key to Scalable Architecture
Your entire system can be bound by single choke points. In order to increase responsiveness, load balancers can spread traffic across horizontally scaled services. Load balancers can improve availability by routing traffic to different proxy servers to prevent overloading.
Consider, where are your scaling problems occurring? If your API gateway is the bottleneck, a load balancer will help you scale up to avoid crashing under demand, timeouts, or slow performance. Similarly, if your application is experiencing a surge in customers, an application load balancer will resolve the issue. Elastic load balancing can also help with application scalability by distributing traffic across multiple targets and virtual applications in one or more availability zones. You may need to address your database scalability – redesigning your storage architecture or moving to a horizontally scaling database.
MEDIA SCALABILITY
“Ten Mile Square knows how to scale digital asset management systems for media companies. After asking the right questions to understand our business, they quickly figured out and solved our scalability issues. Leveraging their AWS expertise, they scaled our platform to serve 7x as many customers. They’re invested in our product and our success. I haven’t found anything they don’t do well.”
– IAN CHESTNUTT, HEAD OF DEVELOPMENT, TENOVOS
Planning and Building Scalable, High-Performing Architecture
With careful planning, you can readily address web application scalability challenges. It starts with understanding your business goals, use cases, and metrics, followed by an analysis comparing architectural design alternatives, such as running one’s own infrastructure instance versus a managed service or cloud hosted offering. Ten Mile Square’s expert team frequently consults on decisions integral to addressing scalability in these key areas:
Fueling Growth and Efficiency with Cloud Architecture
As an AWS partner, we are practitioners of the AWS Well-Architected Framework, which helps cloud architects build secure, high-performing, resilient, and efficient infrastructure. By following its six pillars – operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability – our customers see significant cost savings, improved application performance, and reduced security risks.
Architecting or refining a cloud-based environment for your enterprise? Leverage our expert-led technology assessment where we help you navigate the complex aspects of your cloud architecture strategy. It includes meticulously defining each layer (IaaS, PaaS, SaaS) to build a robust, secure, and scalable framework. You’ll gain a plan that seamlessly integrates your cloud strategy with your business goals, ensuring resilience and growth readiness.
Prioritizing MLOps for AI and Machine Learning
In this era of digital transformation, AI and Machine Learning (ML) have become crucial by allowing systems to learn from data, improve performance, and adapt to evolving business needs autonomously. The integration of AI and ML into your architecture demands a focus on MLOps — a practice for collaboration and communication between data scientists, developers, and operations professionals. MLOps helps you turn your ML models into scalable products that deliver tangible business value.
Successfully integrating AI and ML into scalable architectures requires addressing unique data management needs, sourcing the right talent, and discerning the business value of different models. Homegrown ML often underestimates these demands. Furthermore, high costs and scarce resources, like GPUs for transformers and neural architectures, complicate scaling. A strategic approach to AI/ML, inclusive of efficient MLOps, is crucial to ensure your architecture is scalable, intelligent, and adaptive – making your business dynamic and competitive.
Our Insights: AWS Solutions Architect Associate (SAA-C03), Machine Learning Overview →
Harnessing Auto-Scaling and Elasticity for Optimal Performance
Auto-scaling and elasticity are essential aspects of high-performing cloud infrastructure. Key to their success is ensuring your architecture has horizontally scalable components and understanding how these individual pieces interact and scale.
Pitfalls like overprovisioning, often due to scaling mismatches between components or a lack of elastic scaling capabilities, can inflate costs and hinder flexibility. Proactive monitoring can minimize these unforced errors and downtime issues, preventing the need for customer support and technology operations responses. Infrastructure planning should align with well-architected frameworks and business needs, including data sensitivities, SLAs, and compliance. From a cost standpoint, emphasis is placed on the efficacy of the elastic scaling scheme, along with right-sizing the underlying compute resources. Effective management of auto-scaling and elasticity can significantly enhance operational performance as well as system reliability and customer experience.
Our Insights: Are Your Cloud Costs Too High? 5 Steps to Lower Your AWS Costs →
Unlocking Growth with Scalable Databases
Envision a database that mirrors your business’ growth trajectory, an infrastructure that thrives amidst increasing workloads, ensuring unrivaled performance and efficiency. It is the promise of a scalable database — a robust platform capable of adapting and growing seamlessly with your enterprise.
The journey to achieving optimal database scalability starts by choosing a database type and tech stack that matches your data type and use cases. Employing advanced techniques, like replication, clustering, and sharding, further enhances your potential. Our technology experts lead you through critical strategic decisions to minimize barriers and ensure uninterrupted growth in a business environment riddled with high licensing costs and performance bottlenecks.
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Symptoms of architecturally bound scaling
- Are your AWS bills too expensive relative to revenue/value created?
- Does your system or product “break” when you try to expand your customer base or add new features?
- Does the whole system need to be redeployed, usually with a service outage, when it needs to be scaled up, or even just for a version update?
- Do even minor updates to the system pose a risk of bringing everything down for an unplanned outage?
- Do what should be simple changes to the system take orders of magnitude longer than expected due to interdependencies and baked in fragilities?
- Is monitoring and reacting to system load, health, and capacity non-existent, impossible, lacking, or eyes-on-screens manual?