Autoscaling eCommerce: Seamlessly Managing Website Traffic

DynamicWeb

What is Autoscaling?

Autoscaling is a cloud computing capability that automatically adjusts the number 
and size of computing resources according to the demand.

Unlike traditional fixed infrastructure approaches where you provision resources based on peak capacity needs, autoscaling dynamically adjusts resources based on actual demand. Fixed approaches require significant upfront capital investment and result in idle capacity much of the time, while autoscaling allows for more efficient resource utilization and typically follows a pay-for-what-you-use model.

Autoscaling is a fundamental feature of cloud computing that embodies its core principles:

• Elasticity: The ability to scale resources up or down on demand
• Resource pooling: Drawing from shared computing resources to meet individual application needs
• Measured service: Paying only for resources consumed
• On-demand self-service: Automatically provisioning resources without human intervention
• Broad network access: Making scaled resources available across the network

There are several different types of autoscaling:

Horizontal vs. Vertical

• Horizontal scaling (scaling out/in): Adds or removes instances of resources (e.g., servers, containers) to handle load. This is more common in cloud environments as it offers better fault tolerance and can scale to larger capacities.
• Vertical scaling (scaling up/down): Increases or decreases the capacity of existing resources by adding more CPU, memory, or storage. This approach is typically limited by the maximum capacity of a single instance and may require downtime during scaling operations.

Reactive vs. Predictive

• Reactive autoscaling: Responds to current metrics (CPU utilization, request count, memory usage) that have crossed predefined thresholds. While simpler to implement, it can lead to temporary performance issues during the scaling delay.
• Predictive autoscaling: Uses historical data, machine learning, and pattern recognition to anticipate load changes before they occur. This provides a better user experience by having resources ready before they're needed, but it requires more sophisticated implementation.

Scheduled vs. Spontaneous

• Scheduled autoscaling: Adjusts capacity according to a predefined schedule based on known traffic patterns (e.g., business hours, marketing campaigns, seasonal variations).
• Spontaneous autoscaling: Reacts to real-time metrics and unexpected demand fluctuations without any predefined time pattern, providing maximum adaptability to unforeseen changes in workload.

5 Benefits of Autoscaling Your eCommerce Platform

1. Better Customer Experiences During Traffic Spikes 

When websites crash or slow to a crawl during peak periods, customers face frustrating experiences like timeout errors during critical transactions or inability to access services when they need them most—as seen during Black Friday sales crashes or ticket release events where customers lose reservations mid-checkout.

Autoscaling automatically provisions additional resources as traffic increases, maintaining consistent performance and response times even during unexpected spikes. Thus, customers experience the same level of service quality regardless of how many other users are simultaneously accessing the application.

2. Significant Cost Optimization

Autoscaling implements a true pay-for-use model where companies only incur costs for the exact computing resources they consume. Traditional infrastructure requires substantial capital investment sized for peak capacity that sits idle most of the time, while autoscaling dramatically reduces costs by eliminating this waste—saving massively on infrastructure expenses compared to static provisioning approaches.

3. Improved Reliability and Availability

Autoscaling creates inherent redundancy by distributing workloads across multiple instances, eliminating single points of failure, and ensuring that the failure of any individual component doesn't impact overall system availability.
When instances or services fail, autoscaling automatically replaces them with healthy resources, often detecting and initiating recovery processes before monitoring systems even alert human operators to the problem.

4. Lower Management Overhead

IT teams no longer need to manually provision or de-provision servers based on anticipated demand, removing time-consuming activities like capacity planning meetings, hardware procurement cycles, and manual configuration processes. Midnight calls and emergency response situations due to unexpected traffic spikes become far less common.

5. Great Agility and Scalability 

Companies can capitalize on unexpected opportunities without infrastructure concerns, whether from viral content, sudden market changes, or rapid business growth.

Businesses with predictable seasonal fluctuations—like retail during holidays, tax preparation services, or travel booking sites—can handle peak periods without maintaining expensive year-round capacity for short-term needs.

7 Autoscaling Best Practices

1. Set Appropriate Scaling Metrics and Thresholds

Choose metrics that directly correlate with your application's performance bottlenecks, such as CPU utilization for compute-intensive workloads or request count for web applications, while setting thresholds with sufficient buffer to prevent oscillation between scaling states.

Implement cooldown periods of 3-5 minutes between scaling actions to prevent "flapping" and regularly test threshold settings under varied load conditions to find the optimal balance.

2. Implement Proper Application Design for Scalability

Design applications with stateless architecture where possible, using external session stores and implementing connection pooling to prevent database bottlenecks during scaling events. Incorporate distributed caching strategies that maintain performance during instance changes and ensure all application components can handle adding or removing resources without disruption.

3. Balance Responsiveness with Stability

Configure appropriate cooldown periods between scaling actions and set reasonable minimum and maximum instance limits to prevent both excessive scaling and resource exhaustion. Create graduated scaling policies that add fewer instances initially and more as thresholds continue to be exceeded, testing thoroughly to ensure scaling actions are completed quickly enough to address demand changes.

4. Plan for Regional and Zone Distribution

Distribute your autoscaling groups across multiple availability zones or regions to maximize resilience against localized failures and provide lower-latency experiences to geographically dispersed users. Implement global load balancing that can route traffic based on both instance health and regional capacity availability so resources are optimally allocated across your entire infrastructure.

5. Monitor and Continuously Optimize

Track key metrics, including scaling frequency, instance utilization before and after scaling events, response times, and cost per transaction to identify optimization opportunities. Regularly review scaling patterns to refine policies based on actual usage trends.

6. Combine Reactive and Predictive Scaling

Supplement reactive scaling with predictive measures based on historical data analysis. Pre-warm resources before anticipated traffic spikes using scheduled scaling policies while maintaining reactive capabilities to handle unexpected variations beyond predicted patterns.

7. Test Thoroughly Before Critical Periods

Conduct comprehensive load testing that simulates real-world traffic patterns and sudden spikes before relying on autoscaling for critical business periods. Test failure scenarios including zone outages and instance terminations to verify recovery capabilities, implementing changes gradually in production environments to validate scaling behavior under actual conditions.

DynamicWeb's eCommerce Suite

DynamicWeb offers a comprehensive Composable eCommerce Suite that simplifies online commerce for B2B and B2C businesses. Built from the ground up on .NET 7 with a composable MACH (Microservices, API-first, Cloud, Headless) architecture, DynamicWeb 10 provides the flexibility modern businesses need while future-proofing your strategy for innovations to come. The platform can be deployed either as a complete all-in-one solution—integrating CMS, eCommerce, PIM, and marketing in a single interface—or as individual API-based best-of-breed applications that fit seamlessly into your existing technology stack.

DynamicWeb 10 leverages cloud technology for powerful autoscaling capabilities that adapt to your business needs in real-time. The cloud-based approach is complemented by DynamicWeb's versionless upgrade system, which keeps your eCommerce environment on the newest versions without requiring disruptive upgrade projects. Your business benefits from both the latest features and optimal performance, while your IT team is freed from constant infrastructure management and upgrade planning.

Curious to see how DynamicWeb's autoscaling capabilities can transform your eCommerce operations? Contact DynamicWeb today for a personalized demonstration tailored to your specific business requirements.