AiVibeEvent Streaming
Event streaming is the continuous capture of events, such as transactions or sensor readings, into durable ordered logs that many applications can consume and replay in real time, decoupling data producers from consumers.
Event streaming is the practice of capturing events, such as transactions, sensor readings, clicks or status changes, as continuous streams and making them available to many consumers in real time. Events are appended to durable, ordered logs, often divided into partitions for parallelism, and retained for a configurable period so that consumers can read at their own pace and replay history. Producers and consumers are decoupled: neither needs to know about the other.
Event streaming supports real-time analytics, monitoring and alerting, data integration between microservices and change data capture from databases into lakes and warehouses. In industry it carries machine and sensor data from edge gateways to cloud analytics, often bridged from MQTT. Platforms include Apache Kafka, Amazon Kinesis Data Streams, Azure Event Hubs, Google Cloud Pub/Sub and Apache Pulsar, with stream processors such as Apache Flink computing results continuously.
Design decisions include partitioning keys that preserve ordering where needed, retention periods, schema management through a schema registry and delivery guarantees such as at-least-once or exactly-once processing. Consumers must handle duplicates and late or out-of-order events. Monitoring consumer lag, the gap between the newest event and the last one processed, is a key operational measure.
Key points
- Events are appended to durable, partitioned logs that consumers can replay
- Decouples producers and consumers for real-time integration and analytics
- Platforms include Apache Kafka, Amazon Kinesis, Azure Event Hubs and Apache Pulsar
- Consumer lag is a key measure of whether processing keeps up
Where AiVibe comes in
AiVibe Software Services delivers cloud solutions on AWS, Microsoft Azure, Google Cloud or on-premise, together with cloud security, legacy modernisation, data analytics and AI and machine learning services.
Related terms
- Apache KafkaCloud & AI Infrastructure
- Message QueueCloud & AI Infrastructure
- Microservices ArchitectureCloud & AI Infrastructure
- MQTTIndustrial IoT & Edge
- Extract, Transform, Load (ETL)Cloud & AI Infrastructure
- Serverless ComputingCloud & AI Infrastructure