For example, you could aggregate readings from an embedded device over a time window, and generate a notification if the moving average crosses a certain threshold.Įvent stream processing.
Python event driven framework series#
A consumer processes a series of events, looking for patterns in the event data, using a technology such as Azure Stream Analytics or Apache Storm. For example, you could use Azure Functions with a Service Bus trigger, so that a function executes whenever a message is published to a Service Bus topic.Ĭomplex event processing. An event immediately triggers an action in the consumer. On the consumer side, there are some common variations: That means a client can join at any time, and can replay events. The client is responsible for advancing its position in the stream. Clients don't subscribe to the stream, instead a client can read from any part of the stream. Events are strictly ordered (within a partition) and durable. After an event is received, it cannot be replayed, and new subscribers do not see the event.Įvent streaming: Events are written to a log. When an event is published, it sends the event to each subscriber. Pub/sub: The messaging infrastructure keeps track of subscriptions. In some systems, such as IoT, events must be ingested at very high volumes.Īn event driven architecture can use a pub/sub model or an event stream model. This differs from a Competing Consumers pattern, where consumers pull messages from a queue and a message is processed just once (assuming no errors). Consumers are also decoupled from each other, and every consumer sees all of the events. Producers are decoupled from consumers - a producer doesn't know which consumers are listening. An event-driven architecture consists of event producers that generate a stream of events, and event consumers that listen for the events.Įvents are delivered in near real time, so consumers can respond immediately to events as they occur.
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