Networking and Data Flow

3. Networking Basics for System Design

How Data Travels Across Systems

Explanation
Networking is the foundation that enables distributed systems to function. Every request in a modern application travels through multiple network layers, including the client network, public internet, load balancers, internal service networks, and data stores. Understanding how data moves across these layers helps system designers reason about latency, reliability, and failure modes.

In system design, networking is not about low-level packet details but about designing safe, efficient paths for data flow. Concepts such as DNS resolution, TCP connections, TLS encryption, and routing directly affect performance and security. In 2026, global systems must also account for geographically distributed users, requiring careful placement of services and data to minimize latency and comply with regional regulations.

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Example
When a user opens a web application, the browser first resolves the domain name using DNS. The request is then routed through a CDN, which may serve cached content or forward the request to a load balancer. The load balancer selects an available server instance, which processes the request and communicates with internal services over a private network. Each step adds latency and introduces potential failure points, making network-aware design essential.

Use Cases

Designing low-latency global applications

Planning secure internal service communication

Improving availability through redundancy

Diagnosing network-related performance issues 

APIs and Communication Protocols

REST, gRPC, and Event-Based Communication

Explanation
APIs define how different components of a system communicate. The choice of communication protocol impacts performance, scalability, and development velocity. REST remains widely used for client-facing APIs due to its simplicity and compatibility, while gRPC is popular for internal service-to-service communication because of its efficiency and strong typing.

Event-based communication enables loosely coupled systems by allowing components to publish and consume events asynchronously. This model improves resilience and scalability by decoupling producers from consumers. In 2026, many large-scale systems combine synchronous APIs for immediate interactions with event-driven architectures for background processing and data propagation.

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Example
A ride-sharing application uses REST APIs for booking rides and retrieving trip details. Internally, services communicate using gRPC to handle high request volumes efficiently. Events are published when a ride is completed, triggering downstream processes such as billing, notifications, and analytics without blocking the main user flow. This hybrid communication strategy balances responsiveness and scalability.

Use Cases

Designing public and internal APIs

Building real-time and asynchronous systems

Improving system resilience through decoupling

Supporting evolving business workflows