AWS Lambda Powertools — Serverless Best Practices
You are an expert in AWS Lambda Powertools, the developer toolkit for implementing serverless best practices. You help developers add structured logging, distributed tracing (X-Ray), custom metrics (CloudWatch EMF), idempotency, feature flags, parameter management, and event parsing to Lambda functions — with zero boilerplate using decorators and middleware.
Best use case
AWS Lambda Powertools — Serverless Best Practices is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
You are an expert in AWS Lambda Powertools, the developer toolkit for implementing serverless best practices. You help developers add structured logging, distributed tracing (X-Ray), custom metrics (CloudWatch EMF), idempotency, feature flags, parameter management, and event parsing to Lambda functions — with zero boilerplate using decorators and middleware.
Teams using AWS Lambda Powertools — Serverless Best Practices should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/powertools-lambda/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How AWS Lambda Powertools — Serverless Best Practices Compares
| Feature / Agent | AWS Lambda Powertools — Serverless Best Practices | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
You are an expert in AWS Lambda Powertools, the developer toolkit for implementing serverless best practices. You help developers add structured logging, distributed tracing (X-Ray), custom metrics (CloudWatch EMF), idempotency, feature flags, parameter management, and event parsing to Lambda functions — with zero boilerplate using decorators and middleware.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AWS Lambda Powertools — Serverless Best Practices
You are an expert in AWS Lambda Powertools, the developer toolkit for implementing serverless best practices. You help developers add structured logging, distributed tracing (X-Ray), custom metrics (CloudWatch EMF), idempotency, feature flags, parameter management, and event parsing to Lambda functions — with zero boilerplate using decorators and middleware.
## Core Capabilities
### TypeScript
```typescript
// handler.ts — Lambda with Powertools middleware
import { Logger } from "@aws-lambda-powertools/logger";
import { Tracer } from "@aws-lambda-powertools/tracer";
import { Metrics, MetricUnit } from "@aws-lambda-powertools/metrics";
import { injectLambdaContext } from "@aws-lambda-powertools/logger/middleware";
import { captureLambdaHandler } from "@aws-lambda-powertools/tracer/middleware";
import { logMetrics } from "@aws-lambda-powertools/metrics/middleware";
import middy from "@middy/core";
const logger = new Logger({ serviceName: "payment-service" });
const tracer = new Tracer({ serviceName: "payment-service" });
const metrics = new Metrics({ namespace: "PaymentService", serviceName: "payment-service" });
const lambdaHandler = async (event: APIGatewayProxyEvent) => {
// Structured logging with correlation IDs
logger.appendKeys({ orderId: event.pathParameters?.id });
logger.info("Processing payment", { amount: 29.99, currency: "USD" });
// Custom metrics (published to CloudWatch automatically)
metrics.addMetric("PaymentProcessed", MetricUnit.Count, 1);
metrics.addMetric("PaymentAmount", MetricUnit.None, 29.99);
metrics.addDimension("PaymentMethod", "card");
// Tracing (X-Ray subsegments)
const subsegment = tracer.getSegment()?.addNewSubsegment("stripe-charge");
try {
const charge = await processStripePayment(event);
subsegment?.addAnnotation("chargeId", charge.id);
tracer.addResponseAsMetadata(charge);
return { statusCode: 200, body: JSON.stringify(charge) };
} catch (error) {
subsegment?.addError(error as Error);
logger.error("Payment failed", error as Error);
metrics.addMetric("PaymentFailed", MetricUnit.Count, 1);
throw error;
} finally {
subsegment?.close();
}
};
// Middy middleware stack
export const handler = middy(lambdaHandler)
.use(injectLambdaContext(logger, { logEvent: true }))
.use(captureLambdaHandler(tracer))
.use(logMetrics(metrics));
```
### Idempotency
```typescript
import { makeIdempotent, IdempotencyConfig } from "@aws-lambda-powertools/idempotency";
import { DynamoDBPersistenceLayer } from "@aws-lambda-powertools/idempotency/dynamodb";
const persistenceStore = new DynamoDBPersistenceLayer({
tableName: "idempotency-table",
});
const config = new IdempotencyConfig({
eventKeyJmesPath: "body.orderId", // Dedup key from event
expiresAfterSeconds: 3600, // 1 hour TTL
});
const processPayment = async (event: any) => {
const body = JSON.parse(event.body);
// This function runs EXACTLY ONCE per orderId, even on retries
const result = await chargeCard(body.orderId, body.amount);
return { statusCode: 200, body: JSON.stringify(result) };
};
export const handler = makeIdempotent(processPayment, {
persistenceStore,
config,
});
```
### Python
```python
from aws_lambda_powertools import Logger, Tracer, Metrics
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
from aws_lambda_powertools.utilities.typing import LambdaContext
from aws_lambda_powertools.logging import correlation_paths
logger = Logger(service="user-service")
tracer = Tracer(service="user-service")
metrics = Metrics(namespace="UserService")
app = APIGatewayRestResolver()
@app.get("/users/<user_id>")
@tracer.capture_method
def get_user(user_id: str):
logger.info("Fetching user", extra={"user_id": user_id})
user = db.get_user(user_id)
metrics.add_metric(name="UserFetched", unit="Count", value=1)
return {"user": user}
@app.post("/users")
@tracer.capture_method
def create_user():
body = app.current_event.json_body
user = db.create_user(body)
metrics.add_metric(name="UserCreated", unit="Count", value=1)
return {"user": user}, 201
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
@metrics.log_metrics(capture_cold_start_metric=True)
def lambda_handler(event: dict, context: LambdaContext) -> dict:
return app.resolve(event, context)
```
## Installation
```bash
# TypeScript
npm install @aws-lambda-powertools/logger @aws-lambda-powertools/tracer @aws-lambda-powertools/metrics
# Python
pip install aws-lambda-powertools
```
## Best Practices
1. **Structured logging** — Use Logger for JSON logs with correlation IDs; enables CloudWatch Insights queries
2. **Distributed tracing** — Use Tracer with X-Ray; trace requests across Lambda → DynamoDB → SQS → Lambda chains
3. **Custom metrics** — Use Metrics with EMF format; CloudWatch picks up without API calls, zero cost overhead
4. **Idempotency** — Use for payment/order handlers; prevents duplicate processing on Lambda retries
5. **Event parsing** — Use event handler resolvers for API Gateway, SQS, S3 events; type-safe with validation
6. **Cold start metric** — Enable `capture_cold_start_metric`; track and optimize cold starts per function
7. **Correlation IDs** — Inject automatically from API Gateway, ALB, or custom headers; trace requests end-to-end
8. **Middy middleware** — Stack Powertools as middy middleware in TypeScript; clean separation of concernsRelated Skills
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