Handle Over Million Requests – Factors a Database should have

1. Business Design Statements (BD)

When planning to handle over a million requests, we should clear the Business Design first. Technical leaders think about how every element of the business model affects the consumer and client experience, then outline business needs and how our database should support them.

For example, a student management system should focus on optimizing the relationship between models, since the banking system should focus on optimizing the server when the number of users keeps increasing over time.

So doing this in the earlier time of the project helps us have a well-defined BD, making the right decision for technical strategies

2. Why did our server keep crashing?

A common issue businesses face is server crashes when handling high traffic. Often, it’s due to:
♦ Bad resource allocation
♦ Poor database design
♦ No or lack of scaling mechanisms

Indeed, many products fail because of the lack of scaling mechanisms, and they only start the optimization progress when the high traffic is happening. One of the quick solutions is Hardware Scaling, but it is a bad idea.

3. Hardware vs Software improving

When improving database performance, you can enhance either hardware or software.

Upgrading hardware, which is adding more RAM, and CPU, or using faster SSDs, can provide immediate performance boosts and might be the quickest way to achieve good performance. However, the cost will be increased, and the true thing is that even powerful hardware would not adapt the bad designs.

But if we do that on the software side, optimizing your database queries, indexing, and using efficient algorithms can significantly reduce load times and improve the handling of large volumes of requests on our server, which is a more stable solution.

4. The problem isn’t database, but development!

• ✅ Providing good architecture is crucial for database performance, the team lead, designer, or solution architect in the project should look at many factors:
  ♦ What does the system do overall (Website, Banking, Realtime, Storage,…)
  ♦ Which logic seems to be processing the most (CRUD, services layer, security layer, socket,..)
  ♦ How often does the system communicate with the Database?
  ♦ A relational database, NoSQL, or a hybrid approach?
  ♦ Which is the largest number of users that can be adapted in that scenario?
• ⛔ Not this:
  ♦ How much RAM should be used
  ♦ How much CPU should be used

5. Optimize for the Super Speed!

Whether we choose any architecture, optimization is key to handling millions of requests. Some techniques such as:
♦ Caching frequently accessed data
♦ Load balancing
♦ Connection pooling improves your database’s response time.
♦ Microservice could help separate the heavy load of one instance into smaller instances, using CQRS and SAGA patterns to ensure data consistency.

Stress Testing is the final step

Before going live, we should perform stress testing on our database. Stress testing simulates high-traffic conditions to identify potential bottlenecks so that we know the areas for improvement.

After all, by following and focusing on the critical factors of database performance, you can ensure your system is well-equipped to handle over a million requests efficiently and reliably, providing a smooth user experience even under heavy traffic.