无服务器事件处理架构

Architecture

无服务器事件处理架构图，S3、DynamoDB Streams、API Gateway 和 CloudWatch 触发器调用 Lambda 函数，由 Step Functions 编排，通过 SQS 扇出并使用死信队列进行错误处理。该模板展示如何完全从托管无服务器组件构建复杂的事件处理管道，无需配置或管理任何服务器。适合需要弹性扩展和内置容错能力的数据处理工作流。

下载 .fz 文件

完整 FlowZap 代码

EventSources { # Event Sources
n1: rectangle label:"S3 Bucket Upload"
n2: rectangle label:"DynamoDB Stream"
n3: rectangle label:"API Gateway Webhook"
n4: rectangle label:"CloudWatch Scheduled Rule"
n1.handle(bottom) -> Triggers.n5.handle(top) [label="ObjectCreated"]
n2.handle(bottom) -> Triggers.n6.handle(top) [label="StreamRecord"]
n3.handle(bottom) -> Triggers.n7.handle(top) [label="POST Event"]
n4.handle(bottom) -> Triggers.n8.handle(top) [label="Cron"]
}
Triggers { # Lambda Triggers
n5: rectangle label:"Image Processing Lambda"
n6: rectangle label:"Data Sync Lambda"
n7: rectangle label:"Webhook Handler Lambda"
n8: rectangle label:"Batch Job Lambda"
n5.handle(bottom) -> Processing.n9.handle(top) [label="Process Image"]
n6.handle(bottom) -> Processing.n11.handle(top) [label="Sync Data"]
n7.handle(bottom) -> Processing.n9.handle(top) [label="Handle Event"]
n8.handle(bottom) -> Processing.n12.handle(top) [label="Run Batch"]
}
Processing { # Processing Pipeline
n9: rectangle label:"Step Functions Orchestrator"
n10: diamond label:"Processing Complete?"
n11: rectangle label:"Transform and Load"
n12: rectangle label:"Fan-Out with SQS"
n13: rectangle label:"Error Handler Lambda"
n9.handle(right) -> n10.handle(left)
n10.handle(right) -> n11.handle(left) [label="Success"]
n10.handle(bottom) -> n13.handle(top) [label="Failure"]
n12.handle(right) -> n11.handle(left) [label="Parallel"]
n13.handle(bottom) -> Storage.n17.handle(top) [label="DLQ"]
n11.handle(bottom) -> Storage.n14.handle(top) [label="Store"]
}
Storage { # Managed Storage
n14: rectangle label:"DynamoDB Table"
n15: rectangle label:"S3 Results Bucket"
n16: rectangle label:"SNS Notification Topic"
n17: rectangle label:"SQS Dead Letter Queue"
n14.handle(right) -> n15.handle(left) [label="Archive"]
n15.handle(right) -> n16.handle(left) [label="Notify"]
}

为什么需要这个工作流？

Building event processing pipelines on traditional servers requires provisioning for peak load, managing scaling policies, and handling server failures. Serverless event processing automatically scales per-event, handles failures with built-in DLQ support, and costs nothing when idle—perfect for bursty, unpredictable workloads.

工作原理

Step 1: Events from S3 uploads, DynamoDB streams, API webhooks, and scheduled rules trigger Lambda functions.
Step 2: Each trigger type invokes a specialized Lambda function for its processing logic.
Step 3: Step Functions orchestrate multi-step processing with branching and parallel execution.
Step 4: SQS provides fan-out for parallel processing of independent work items.
Step 5: Failed events are captured in a dead letter queue for investigation.
Step 6: Processed results are stored in DynamoDB and S3, with SNS notifications for downstream consumers.

替代方案

Container-based event processors (ECS) offer more control over runtime but require capacity management. Managed services like AWS EventBridge simplify routing. This template shows the fully serverless event processing pipeline.

Key Facts

Template Name	无服务器事件处理架构
Category	Architecture
Steps	6 workflow steps
Format	FlowZap Code (.fz file)