Events

Event-Driven Architecture and Messaging Event-driven architecture uses events as the main way systems communicate. A component that creates something of interest—like a new order—publishes an event. Other components listen for that event and react. Because actions are driven by messages rather than direct calls, services stay decoupled and can grow independently. This design helps apps handle spikes in traffic and recover when parts fail. The core idea is simple: producers emit events, and consumers respond. A message broker or event bus stores events and routes them to interested handlers. To keep things reliable, teams often design with durable queues, idempotent observers, and explicit contracts for event data. ...

Serverless Computing: Pros, Cons and Use Cases Serverless computing changes how software runs. You write small pieces of code, called functions, and the cloud executes them on demand. You never manage servers or capacity. This model can speed up development and handle sudden traffic spikes, but it also brings new limits and trade-offs. With clear design, it helps teams ship features faster and keep operations simple. What it means for developers In a serverless setup, developers focus on business logic. Functions are stateless and run in response to events or HTTP requests. The platform scales automatically and retries tasks when needed. This reduces setup time and outages tied to traffic surges. Still, you must plan for observability, error handling, and data consistency across many tiny parts. ...

Middleware Architecture: Integration Without Pain Integration often feels like a puzzle with many moving parts. A good middleware layer reduces friction between services, teams, and data. The goal is to connect systems in a reliable, scalable way while keeping changes safe and visible. Key aims for middleware include decoupling, reliability, and observability. Decoupling lets teams move faster without breaking others. Reliability means predictable messages and retries, not mysterious failures. Observability helps you understand flows, diagnose problems, and prove compliance. ...

Serverless Computing: When to Run Functions Serverless computing lets developers write small, event-driven functions that run in the cloud. The platform provisions resources, scales automatically, and charges only for execution time. Because server management is hidden, teams ship features faster and reduce operational tasks. Yet this model also invites new questions about design, reliability, and cost. When should you run functions? Focus on events and boundaries that fit short, stateless work. Consider these common scenarios: ...

Serverless computing and event-driven architectures Serverless computing lets developers run code without managing servers. In practice, you write small units of logic—functions or event-driven services—while a cloud provider handles deployment, scaling, and fault tolerance. You pay only for the compute time you use, which can reduce costs for workloads with irregular activity. This model fits well with event-driven architectures, where changes in data or user actions emit events that trigger downstream processing. ...

Serverless and Event-Driven Architectures Serverless and event-driven architectures are two modern patterns that often work together. Serverless means you run code without managing servers; you pay only for compute time and resources used. Event-driven design focuses on events and asynchronous flows, where components react to changes and emit new messages. This combination lets systems respond quickly to real work while staying flexible. Typical setups connect event sources such as API gateways, file storage, data streams, or scheduled timers to an event bus. Each service subscribes to the events it can handle, processes the data, and sends new events downstream. This keeps services small and focused, easy to replace or scale. With clear boundaries, teams can evolve parts of the system without risking the whole app. ...

Serverless Computing From Abstraction to Real World Serverless computing shifts the burden of running servers away from developers to a cloud provider. You still write code, but you don’t manage machines, OS updates, or capacity planning. This speeds delivery and lets teams focus on user value. Under the hood, serverless is an abstraction layer that lets you run small, stateless functions that respond to events: HTTP calls, file uploads, or messages from a queue. When traffic rises, the platform scales automatically; when it falls, resources shrink to zero. Real world use means designing around latency, reliability, and security. Expect cold starts, where a function starts up from idle state. You can reduce impact with memory tuning, shorter tasks, or architectural choices that keep work quick. ...