In this article , we provide a practical, step-by-step guide to making software systems scalable , from a single-server setup to a fully distributed architecture.

It begins with the fundamentals of I/O performance, explaining how hardware limitations such as disk speed and network latency affect system throughput. Then it explores progressive scaling strategies, including vertical and horizontal scaling, caching, asynchronous processing, and load balancing.

Finally, it addresses the deeper challenges of distributed systems . data consistency, CAP theorem, replication, sharding, and event-driven communication .

offering clear, real-world approaches for designing resilient, high-performance application

CAP is a .NET library that helps implement the Outbox Pattern and distributed event publishing reliably.

It supports multiple databases (SQL Server, MySQL, PostgreSQL, etc.) and message brokers (RabbitMQ, Kafka, Azure Service Bus).

It automatically stores events in an outbox table within your database transaction and publishes them asynchronously.

It handles retries, failure scenarios, and event deduplication.

CAP is a great fit if you want out-of-the-box support for transactional outbox + message broker integration.

It abstracts away a lot of complexity.

Widely used in .NET microservice and event-driven architectures.

• Transactional consistency: Your business data and events are saved atomically.
• Reliable event publishing: Events are published asynchronously with retries.
• Supports multiple brokers and databases.
• Minimal setup: Integrates easily with EF Core and other ORMs.
• Automatic cleanup and monitoring.
• Helps you avoid reinventing the wheel.