Event driven thinking is now at the heart of modern cloud design. Systems react to facts as they happen, which improves scalability, resilience, and speed to value. In this guide, we cover the Top 10 Event-Driven Architectures in the Cloud and show where each pattern fits. You will learn the core idea, the common building blocks, and the trade offs to watch. The focus is clear and practical, so teams from startups to large enterprises can apply it. Use these patterns to reduce coupling, cut fragile dependencies, and support rapid change. Each section names a proven architecture, explains how it works, and lists design tips.
#1 Serverless event bus core
A serverless event bus places a managed router at the center, with producers publishing events and consumers subscribing by rule. Cloud services such as event bridge, event grid, and pub sub topics handle filtering, retries, and delivery at scale. This pattern reduces point to point coupling and lets teams add new consumers without touching producers. Use schema registries to keep contracts clear. Apply idempotency keys to make handlers safe on retries. Separate high value events from noisy telemetry with different buses. Start with coarse events, then evolve payloads with versioned fields.
#2 Topic based pub or sub fan out
A topic based model lets one event reach many services through independent subscriptions. Producers publish to a topic, and each subscriber processes a copy at its own pace. This enables analytics, indexing, caching, and notifications to evolve in parallel. Choose push or pull delivery per workload to control back pressure. Use dead letter queues for poison messages. Keep topics focused on a business noun, not a database table. Avoid sharing read specific fields in the canonical event. If a shape is too large, publish a light event with a durable link to the full record.
#3 Event sourcing with CQRS
Event sourcing records facts as an append only log, then builds read models from those facts. Commands validate intent and emit events. The read side uses materialized views to serve queries with low latency. This pattern gives perfect audit and time travel. It also enables replay into new projections without touching the write path. Keep aggregates small and transactional to avoid contention. Store events with type, id, timestamp, and version. Version event schemas with additive rules. Provide snapshots for long lived streams to speed recovery. Monitor stream gaps to catch stalled consumers early.
#4 Saga choreography for long transactions
When a business action spans several services, a saga coordinates the steps using events. Each service performs its local work and publishes an outcome event that triggers the next step. Compensation events undo prior work if a later step fails. Choreography keeps the flow flexible and avoids a single controller. Use clear event names like order reserved and payment captured. Keep compensations simple and bounded. Prefer small steps that complete quickly to reduce lock time. Trace each saga with a correlation id so you can debug and measure end to end latency.
#5 Workflow orchestration on events
Some processes need strong control, branching, and timeouts. A workflow engine started by an event can call activities, wait on signals, and manage retries with backoff. This gives clarity for regulated flows and when human approval or timers are required. Use state machines for high volume short tasks, and full workflows for complex lifecycles. Put only coordination in the workflow. Keep business logic in stateless activities. Set retention and history limits to control cost. Export workflow metrics and traces so operations can see blocking states, timer queues, and success rates per step.
#6 Stream processing pipeline
Continuous streams carry click data, sensor readings, and payments. A stream processing pipeline ingests, partitions, and processes events with low latency using tools like Kafka, Kinesis, or Pulsar with Flink or Spark. Stateless transforms handle filtering and mapping. Stateful transforms support joins, windows, and alerts. Choose keys that balance partitions and keep related events together. Persist state with checkpoints and externalized state stores. Design exactly once semantics with idempotent writes and transactional sinks where possible. Expose a compacted topic for latest state and a long retention topic for full history to enable both serving and analytics.
#7 Change data capture to events
Legacy systems hold critical data, yet they were not built for events. Change data capture turns database updates into ordered events without touching application code. Use log based capture to avoid triggers and to preserve commit order. Publish domain events that map changes to business meaning, not raw row diffs. Apply exactly once handling at consumers by using primary keys and upserts. Protect privacy by filtering sensitive columns early. Throttle per table to avoid load bursts on the source. Use schema evolution and data quality checks to keep downstream views stable during migrations.
#8 IoT edge to cloud event ingestion
Devices and gateways send bursts of small messages that must be secured and buffered. Use device identity, mutual TLS, and per topic access to isolate tenants. Gateways batch events, apply simple rules, and drop duplicates before forwarding. In the cloud, land events into a durable stream, then fan out to time series storage, monitoring, and control services. Handle offline devices with backoff and store and forward queues. Keep payloads compact with binary codecs where needed. Model device twins as events to keep digital state in sync and to support safe update workflows.
#9 Event mesh across regions and clouds
An event mesh links brokers in several regions so events can flow with low latency and local autonomy. Producers publish locally and policies route events where they are needed. This reduces cross region chatty calls and improves fault isolation. Use subjects or topics with geography prefixes to keep routing clear. Enable message replay at the edge for quick recovery. Encrypt in transit and enforce tenant isolation. Test regional failover with realistic traffic. Replicate only durable business events, not high volume noise, to control cost and to protect interconnect bandwidth.
#10 Notifications and webhooks gateway
External systems often need to react to your events in real time. A notifications and webhooks gateway transforms internal events into outbound calls while handling retries, signing, and backoff. Use a subscription model where partners select event types and delivery targets. Sign payloads and record delivery logs for audit. Provide a replay API so consumers can recover from outages. Throttle per target and isolate failures with circuit breakers and queues. Expose a developer portal with examples and schema definitions to speed onboarding and to reduce integration errors. Offer templates to adapt payloads to partner formats without code in producers.