Does everything need to be real-time?

No. Real-time adds complexity and cost. Use when: customer-facing, time-sensitive decisions, competitive advantage from speed. Batch is fine for many back-office processes.

What is the difference between real-time and streaming?

Streaming processes continuous data flows. Real-time focuses on low latency. Often combined: streaming enables real-time processing of continuous data. Batch is the opposite of both.

How do I handle failures in real-time?

Design for resilience: message queues for buffering, retry mechanisms, graceful degradation, dead-letter queues. Real-time failures are visible, so handling is critical.

What latency is considered real-time?

Depends on context. User interactions: sub-second. Business events: seconds. Analytics: seconds to minutes. Define "real-time" for your use case and measure against it.

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Real-Time Processing

Processing data or transactions immediately as they occur, enabling instant responses and up-to-date information.

In-Depth Explanation

Real-time processing handles data or transactions immediately as they occur, without deliberate delay. It enables instant responses, live dashboards, and up-to-date business operations.

Real-time characteristics:

Immediate: Processed as received
Event-driven: Triggered by events
Low latency: Minimal delay
Continuous: Always processing

Types of "real-time":

Hard real-time: Strict timing guarantees
Soft real-time: Best effort, low latency
Near real-time: Seconds to minutes delay

Real-time applications:

Customer-facing transactions
Live dashboards
Fraud detection
Inventory updates
Chat and notifications
IoT data processing

Technologies:

Message queues (Kafka, RabbitMQ)
Stream processing (Spark Streaming, Flink)
Event-driven architecture

Business Context

Real-time processing enables responsive customer experiences, timely decisions, and operational agility in fast-moving business environments.

How Clever Ops Uses This

We implement real-time processing for Australian businesses where immediacy matters, from customer transactions to operational dashboards.

Example Use Case

"Real-time inventory updates: when a customer purchases online, inventory is immediately decremented, available-to-promise updated, and low-stock alerts triggered."