A practical guide to building scalable coupon platforms, reducing database pressure, and collecting useful customer activity data with .NET technologies.
Black Friday changes the way people shop online. Visitors who normally browse a few products may suddenly spend hours comparing prices, searching for discount codes, and checking different offers before making a purchase.
For coupon platforms, this creates a challenging situation. A popular deal can attract thousands of visitors within a short period. If the application is not prepared, the increased demand can lead to slow pages, overloaded databases, failed requests, and a poor user experience.
This is where software architecture becomes important.
Developers working with ASP.NET Core have several technologies available to prepare applications for these traffic spikes. Redis, Content Delivery Networks (CDNs), distributed caching, background processing, and SQL Server can work together to improve performance and make a coupon platform more reliable.
Let's explore how these technologies fit together.
1. Understanding the Black Friday Traffic Challenge
Consider a coupon platform such as RabattDigga. During a major shopping event, visitors may repeatedly search for popular brands, open coupon pages, copy discount codes, and follow links to online retailers.
Each action can generate multiple application requests.
For example, opening a coupon page might require:
- Retrieving brand information.
- Loading available coupon codes.
- Checking coupon expiration dates.
- Loading images and promotional banners.
- Recording page views and user interactions.
When thousands of visitors perform these actions simultaneously, the application server and database can experience considerable pressure.
The solution is not simply adding more servers. Developers need to identify which operations require database access, which information can be cached, and which tasks can run asynchronously.
2. Using Redis to Reduce Database Pressure
Redis is an in-memory data store that can act as a distributed cache.
Imagine that thousands of visitors open the same popular brand page. Without caching, the application might execute similar SQL Server queries repeatedly to retrieve identical brand and coupon information.
Instead, developers can store frequently requested information in Redis.
The application checks Redis first. If the requested information exists, it returns the cached result. Otherwise, it retrieves the information from SQL Server and stores it in Redis for subsequent requests.
This approach is commonly known as cache-aside.
In ASP.NET Core, developers can implement distributed caching through the IDistributedCache interface and the Redis provider.
For example:
builder.Services.AddStackExchangeRedisCache(options =>
{
options.Configuration =
builder.Configuration.GetConnectionString("Redis");
});
A cache entry can then be retrieved asynchronously:
var cachedData = await cache.GetStringAsync("brand_coupons");
if (cachedData == null)
{
// Retrieve coupon information from SQL Server
// Serialize and store the result in Redis
}
The actual implementation should also include cache expiration, serialization, and cache invalidation when coupon information changes.
The benefit is straightforward: frequently requested information does not need to be retrieved from SQL Server on every visit.
3. Using a CDN to Deliver Static Content Faster
A coupon platform may contain hundreds of brand logos, promotional banners, product images, and other static resources.
Serving all these resources directly from the application server can increase its workload.
A CDN distributes static content across geographically distributed servers. Visitors can retrieve images and other eligible resources from a nearby CDN location instead of repeatedly requesting them from the application's origin server.
For a platform receiving visitors from different countries, this can improve content delivery and reduce unnecessary origin requests.
Developers should configure appropriate cache headers and ensure that updated promotional images are not hidden behind outdated CDN copies.
4. Combining Different Caching Strategies
Redis is useful, but it should not be the only caching mechanism.
ASP.NET Core supports several caching approaches, including:
- In-memory caching for frequently accessed information within an application instance.
- Distributed caching for information shared across multiple application instances.
- Output caching for eligible HTTP responses.
- CDN caching for static resources.
Consider a popular coupon category page.
The CDN can deliver its images, output caching can reuse eligible server-generated responses, and Redis can store frequently requested coupon and brand data.
This layered approach reduces repeated processing at different points in the application.
However, developers must be careful with personalized responses, expired coupons, and frequently updated information. Not every response should be cached in the same way.
5. Using Background Processing for User Activity Tracking
Performance is not only about displaying pages quickly. Coupon platforms also generate valuable activity data.
For example, they may need to record:
- Coupon page views.
- Search queries.
- Coupon copy events.
- Retailer link clicks.
- Popular brands and categories.
- Returning visitor activity.
One mistake developers can make is performing every tracking operation directly within the visitor's HTTP request.
If thousands of visitors generate tracking events simultaneously, synchronous database writes can add unnecessary delays.
A better approach is asynchronous background processing.
The application can place tracking events into a message queue. A background worker then processes these events and stores them in SQL Server.
ASP.NET Core provides BackgroundService and IHostedService for implementing hosted background tasks.
This allows the main application to respond to visitors without waiting for every analytics operation to finish.
For more demanding applications, developers can also consider message brokers such as RabbitMQ or Azure Service Bus.
Reliable event processing should include retry handling, monitoring, and appropriate queue management.
6. Storing and Analysing Coupon Activity with SQL Server
Once background workers process the events, SQL Server can store structured information for reporting.
A simple event table might include:
| Column | Description |
|---|
| EventId | Unique event identifier |
| UserId | User reference, if available |
| EventType | View, search, copy or click |
| BrandId | Related brand |
| EventDate | Activity timestamp |
Developers can use SQL queries to identify which brands receive the most attention, which coupons are copied frequently, and when visitor activity reaches its highest point.
For example, the business team might discover that electronics coupons receive more attention during the evening, while fashion offers attract more visitors earlier in the day.
These insights can help improve future campaigns and platform planning.
There is an important privacy consideration here: platforms should avoid collecting unnecessary personal information. Anonymous identifiers, appropriate consent mechanisms, retention policies, and transparent privacy notices should be considered when designing analytics systems.
7. Load Balancing and Autoscaling
Even with caching and optimized database operations, application servers can become overloaded during exceptional traffic spikes.
Load balancing helps distribute incoming requests across multiple healthy application instances.
Autoscaling can increase the number of instances when demand rises and reduce capacity when traffic returns to normal.
For an ASP.NET Core application, this can be implemented using suitable cloud hosting infrastructure or container orchestration.
Developers should also ensure that application instances do not depend on local in-memory session data when requests may move between servers.
8. Test the Application Before Black Friday
Infrastructure improvements should be tested before the actual shopping event.
Load testing helps developers understand how the application behaves under different levels of concurrent traffic.
Important areas to test include:
- Homepage and category page loading.
- Coupon search functionality.
- Brand detail pages.
- Coupon copy and click tracking.
- SQL Server query performance.
- Redis response times.
- Background queue processing.
- API response times and error rates.
Monitoring CPU usage, memory consumption, database connections, cache hit rates, and request latency can help identify bottlenecks before they affect visitors.
Final Thoughts
A successful Black Friday experience depends on more than attractive discounts and a well-designed website. The technology behind the platform must also be ready for sudden changes in demand.
ASP.NET Core provides a flexible foundation for building scalable applications. Redis can reduce repeated database queries, CDNs can improve static content delivery, caching can reduce unnecessary processing, and background services can handle analytics without slowing down the visitor experience.
SQL Server then provides a structured way to retain and analyse useful activity data.
When these technologies are designed to work together, developers can build coupon platforms that are better prepared for heavy traffic while gaining insights that help improve future shopping experiences.
Arun PottiPosted Nov 11, 2026, 5:12 AM
Great Article.