Stop Writing Glue Code: Building Event-Driven Pipelines with Amazon EventBridge Pipes
Modern applications generate events everywhere: orders are created, files are uploaded, payments are completed, and database records change. Connecting these events to downstream services often leads to custom consumers, filtering logic, retries, and transformation code. Amazon EventBridge Pipes provides a simpler approach by connecting supported event sources directly to targets with filtering, enrichment, transformation, and delivery handling built into the pipeline.
Your Application Probably Has Too Much Glue Code
Consider a simple workflow:
A customer places an order → process the order → send a notification.
It sounds straightforward.
But the implementation often becomes:
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Database
↓
Custom Worker
↓
Message Queue
↓
Consumer
↓
Lambda
↓
Notification Service
Each component introduces another piece of infrastructure to configure, monitor, deploy, and maintain.
The business logic might be simple.
The integration logic isn't.
This is one of the problems Amazon EventBridge Pipes is designed to address.
What Are EventBridge Pipes?
EventBridge Pipes creates a point-to-point connection between an event source and a target.
Instead of writing a custom consumer just to receive an event and forward it somewhere else, you can define:
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Source → Filter → Enrichment → Target
For example:
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Amazon SQS
↓
EventBridge Pipes
↓
AWS Lambda
Or:
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Amazon DynamoDB Streams
↓
EventBridge Pipes
↓
Amazon SQS
The pipe handles the integration while your application focuses on the actual business behavior.
This distinction is important.
EventBridge Pipes isn't replacing your application logic. It's removing unnecessary plumbing around it.
Filtering Before Your Application Sees the Event
One of the most useful capabilities is filtering.
Imagine an SQS queue receives different order events:
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{
"orderId": "A1024",
"status": "created",
"region": "APAC"
}
Your downstream service might only care about newly created orders in a particular region.
Instead of sending every message to your Lambda function and writing:
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if status != "created":
ignore
the pipe can filter events before they reach the target.
That gives us:
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┌── matching events ──→ Target
│
Event Source → Filter
│
└── ignored events
This seems like a small optimization.
At scale, avoiding unnecessary invocations, network traffic, and application processing can become a meaningful architectural improvement.
Enrichment Without Building Another Service
Filtering isn't the only interesting part.
A pipe can also enrich events before delivering them to a target.
Imagine receiving an order containing:
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{
"customerId": "C102",
"productId": "P991"
}
The downstream application may need additional information before processing it.
Instead of creating a dedicated "lookup service" whose only purpose is to enrich the event, EventBridge Pipes can integrate with supported enrichment targets.
The conceptual flow becomes:
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Order Event
↓
Filter
↓
Enrichment
↓
Transformation
↓
Target
The event arrives at the destination already prepared for consumption.
Pipes vs. EventBridge Rules
A useful distinction is that Pipes and EventBridge Rules solve related but different problems.
EventBridge Rules are useful when an event needs to be routed to multiple targets or when you are building an event bus architecture.
EventBridge Pipes are particularly useful for point-to-point integrations between a specific source and target.
For example:
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EventBridge Bus
↓
┌───┴────┐
↓ ↓
Lambda SQS
is a natural EventBridge event-routing pattern.
Meanwhile:
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DynamoDB Stream
↓
Pipe
↓
SQS
is a natural Pipes pattern.
The difference is architectural intent, not simply which service is newer.
A Practical Order Processing Architecture
Imagine an e-commerce system using DynamoDB for orders.
When an order changes:
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DynamoDB
│
▼
DynamoDB Streams
│
▼
EventBridge Pipes
│
├── Filter
│
├── Transform
│
▼
SQS
│
▼
Order Worker
The order worker can now concentrate on something important:
processing the order.
It doesn't need to understand how to consume the stream, decide which records matter, or implement another integration layer.
That separation makes the system easier to reason about.
Less Code Doesn't Mean Less Architecture
It's tempting to think managed services eliminate architectural complexity.
They don't.
They move complexity into configuration and platform capabilities.
You still need to think about:
- retries
- failure handling
- ordering requirements
- idempotency
- permissions
- observability
- message transformation
- throughput
A pipe doesn't magically make distributed systems simple.
What it can do is remove code that doesn't provide business value.
And that's an important distinction.
The Bigger Lesson
As developers, we often reach for Lambda, containers, or custom workers whenever two AWS services need to communicate.
Sometimes that's exactly right.
But sometimes we're building a small application whose entire responsibility is:
Receive event → filter it → transform it → send it somewhere else.
That is integration plumbing.
For those cases, EventBridge Pipes provides a useful architectural question:
Do I actually need to write this integration code?
If the answer is no, letting AWS manage the connection can leave your application with fewer components, fewer deployment units, and less code to maintain.
The goal isn't to eliminate code.
It's to make sure the code you keep is the code that actually matters.
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