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Understanding Event-Driven Systems

Quite a lot of the tasks modern-day systems are required to do are in response to changes in state.

Adding an item to a shopping cart, liking a post, and paying a bill are all state changes that trigger a set of tasks in their respective systems.

This requirement has paved the way for a popular approach to system architecture known as event-driven architecture (EDA).

There are four main components in an event-driven architecture — events, producers, consumers, and event brokers.

In a nutshell, events are updates to the system’s state which are generated by producers. When an event occurs, it is sent to consumers via event brokers, which distribute the event for processing.

In more detail.

Events represent changes or updates to the system's state. These can range from a user action, like clicking a button, to a system-generated alert, such as a threshold being reached.

Producers generate events whenever a state change occurs. These can be applications, services, sensors, or user interfaces.

Consumers are the recipients of the events. They listen for events they are interested in and, upon receiving such an event, perform a corresponding action or process. This decoupled nature allows consumers to operate independently from the producers, enhancing the system's modularity and flexibility.

Event brokers (eg; Kafka, RabbitMQ, AWS EventBridge) manage event distribution between producers and consumers, providing event persistence, message queues, and routing via topics or channels. Some ensure reliability with at-least-once delivery, while others use at-most-once delivery, risking data loss.

Synchronous vs Asynchronous Event Handling

Events can be handled synchronously or asynchronously.

When using a synchronous approach, the producer would need to wait for the consumer to process the event before moving on to the next task.

For example, when booking a hotel online your web browser would wait for the system to complete your request and return a result before it can proceed.

Synchronous processing provides a predictable execution path for every given event, which makes it far simpler to understand and debug.

It is necessary in scenarios where an immediate response is critical, such as processing financial transactions.

However, its rigid nature makes it incompatible with components that generate high amounts of events or carry out time-consuming processing operations.

Synchronous processing limits the system's scalability and fault tolerance which is why it should only be reserved for when it is absolutely necessary.

On the other hand, asynchronous processing doesn't wait for a response. Producers queue up events for consumers to process and then move on to the next task.

For example, posting a status update on social media does not need immediate action. Instead, your followers can be notified asynchronously.

Asynchronous processing is more commonly used in event-driven architecture because it promotes scalability, loose coupling, resilience, and flexibility better than a synchronous approach.

It is ideal in scenarios where events are generated frequently and in large portions, which is generally the case for most systems built with an event-driven design.

EDA is primarily asynchronous because synchronous event handling can create performance bottlenecks.

The Upside of Event-Driven Architecture

EDA stands out for its scalability, efficiency, and flexibility.

By decoupling services, it seamlessly handles fluctuating demands, fostering system growth with minimal overhaul.

EDA's event-centric approach ensures resources are used only when necessary, enhancing efficiency. Its loosely coupled design allows components to evolve independently, simplifying updates and maintenance while boosting system resilience and adaptability.

This combination of features positions EDA as a popular architecture for developing robust and efficient modern systems.

Challenges of Event-Driven Systems

While event-driven architecture offers scalability and flexibility, it introduces significant complexity in managing distributed environments.

As systems scale, monitoring event flows, debugging failures, and diagnosing errors become more difficult without specialized tools like distributed tracing, log correlation, and dead-letter queues.

EDA’s decentralized nature complicates data consistency.

Since events are processed asynchronously, systems often rely on eventual consistency rather than strict ACID transactions. Event ordering is not always guaranteed, especially in event-streaming systems like Kafka that use partitioned logs.

Other key challenges include:

Duplicate event processing → consumers must handle idempotency to avoid unintended side effects.

Error handling and retries → failures in event delivery require dead-letter queues, backoff strategies, and compensating transactions.

Event delivery guarantees → systems must choose between at-most-once (potential data loss), at-least-once (potential duplicates), or exactly-once (more expensive to implement).

These challenges require careful design, monitoring, and error-handling strategies to fully leverage EDA’s benefits.

Where Event-Driven Architecture Shines

EDA shines in scenarios that require real-time responsiveness and scalability across distributed systems. As well as scenarios where events are generated frequently and in large amounts—as the name implies.

Its applicability spans various domains, from IoT, which relies on immediate reaction to sensor data, to real-time data processing systems that must process and analyze data streams with minimal latency.

Microservices also greatly benefit from EDA, as it allows for decoupled services that can independently respond to state changes.

These use cases underscore event-driven architecture’s versatility and ability to enhance system responsiveness and scalability.

Wrapping Up

Event-driven architecture is a scalable and efficient solution for systems that consist of many nodes or services and process large volumes of events. It promotes loose coupling and helps keep the system flexible and simpler to maintain.

What Does an API Gateway Do? (Recap)

An API Gateway is a centralized entry point for client interactions with microservices, simplifying communication, enhancing security, and optimizing performance.

It handles request routing, validation, authentication, rate limiting, and protocol translation.

Additionally, it aggregates responses, monitors performance metrics, and provides logging, caching, and fault handling.

This makes it essential for managing complex microservices architectures efficiently.

See here, for how an API gateway processes a request.

5 Authentication Features You Should Know (Recap)

Authentication goes beyond just logging in—it’s about security, user experience, and compliance. Here are five auth features you should consider adding to your applications to enhance security and provide a seamless user experience:

1) Login & Registration – Secure credential storage, password hashing, and smooth onboarding.

2) Single Sign-On (SSO) – Enables users to log in once and access multiple apps via OAuth 2.0, OIDC, or SAML.

3) Multi-Factor Authentication (MFA) – Adds security layers with TOTP codes, biometrics, or push notifications.

4) Passkeys (WebAuthn) – Passwordless authentication using biometrics and device security.

5) Magic Links – One-time login links via email for a frictionless experience.

Authentication is a high-risk and complex area, so using an auth provider is considered best practice.

Check out the full post here.

API Security Best Practices (Recap)

The rise in API-related security breaches highlights the necessity for robust API security.

Essential techniques and best practices to improve API security include; HTTPS, rate limiting and throttling, authentication, authorization, input validation, API gateway, regular security audits, dependency management, logging and monitoring, API versioning, data encryption at rest, and access controls.

API security isn’t a nice to have; it’s a must. Following the techniques and best practices I’ve shared above will take you a long way; they are the foundations of building safe and secure APIs.

See the full post here for an explanation of key practices.

That wraps up this week’s issue of Level Up Coding’s newsletter!

Join us again next week where we’ll explore and visually distill more important engineering concepts.