Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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Build and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless applications.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Build serverless applications with AWS Lambda, covering function creation, event sources, layers, SAM templates, and cold start optimization.
lambda:*, iam:PassRole, logs:*, apigateway:*, s3:*# Create a deployment package
cd my-function
zip -r function.zip app.py
# Create the Lambda function
aws lambda create-function \
--function-name my-api-handler \
--runtime python3.12 \
--handler app.handler \
--role arn:aws:iam::123456789012:role/LambdaExecRole \
--zip-file fileb://function.zip \
--memory-size 256 \
--timeout 30 \
--environment 'Variables={STAGE=production,LOG_LEVEL=INFO}' \
--architectures arm64 \
--tracing-config Mode=Active \
--tags '{"Team":"backend","Environment":"production"}'
# Update function code
aws lambda update-function-code \
--function-name my-api-handler \
--zip-file fileb://function.zip
# Update function configuration
aws lambda update-function-configuration \
--function-name my-api-handler \
--memory-size 512 \
--timeout 60 \
--environment 'Variables={STAGE=production,LOG_LEVEL=WARNING}'
# Publish a version (immutable snapshot)
aws lambda publish-version \
--function-name my-api-handler \
--description "v1.2.0 - added rate limiting"
# Create an alias pointing to the version
aws lambda create-alias \
--function-name my-api-handler \
--name live \
--function-version 3
# Weighted alias for canary deployments (90% v3, 10% v4)
aws lambda update-alias \
--function-name my-api-handler \
--name live \
--function-version 4 \
--routing-config '{"AdditionalVersionWeights":{"3":0.9}}'
# app.py - API Gateway handler with structured logging
import json
import logging
import os
logger = logging.getLogger()
logger.setLevel(os.environ.get("LOG_LEVEL", "INFO"))
def handler(event, context):
"""Handle API Gateway proxy event."""
logger.info("Request: %s %s", event["httpMethod"], event["path"])
try:
body = json.loads(event.get("body", "{}"))
result = process_request(body)
return {
"statusCode": 200,
"headers": {
"Content-Type": "application/json",
"X-Request-Id": context.aws_request_id
},
"body": json.dumps(result)
}
except ValueError as e:
logger.warning("Validation error: %s", e)
return {"statusCode": 400, "body": json.dumps({"error": str(e)})}
except Exception as e:
logger.exception("Unhandled error")
return {"statusCode": 500, "body": json.dumps({"error": "Internal server error"})}
def process_request(body):
return {"message": "OK", "data": body}
# sqs_processor.py - SQS batch processor with partial failure reporting
import json
import logging
logger = logging.getLogger()
logger.setLevel("INFO")
def handler(event, context):
"""Process SQS messages with partial batch failure reporting."""
failed_ids = []
for record in event["Records"]:
try:
body = json.loads(record["body"])
logger.info("Processing message: %s", record["messageId"])
process_message(body)
except Exception as e:
logger.error("Failed message %s: %s", record["messageId"], e)
failed_ids.append(record["messageId"])
# Return failed items so only those get retried
return {
"batchItemFailures": [
{"itemIdentifier": msg_id} for msg_id in failed_ids
]
}
def process_message(body):
pass # your logic here
# Build a layer for Python dependencies
mkdir -p layer/python
pip install requests boto3-stubs -t layer/python/
cd layer
zip -r ../my-layer.zip python/
# Publish the layer
aws lambda publish-layer-version \
--layer-name common-deps \
--description "Shared Python dependencies" \
--zip-file fileb://my-layer.zip \
--compatible-runtimes python3.11 python3.12 \
--compatible-architectures arm64 x86_64
# Attach layer to a function
aws lambda update-function-configuration \
--function-name my-api-handler \
--layers "arn:aws:lambda:us-east-1:123456789012:layer:common-deps:1"
# List available layers
aws lambda list-layers --compatible-runtime python3.12
# SQS trigger with batch processing
aws lambda create-event-source-mapping \
--function-name sqs-processor \
--event-source-arn arn:aws:sqs:us-east-1:123456789012:my-queue \
--batch-size 10 \
--maximum-batching-window-in-seconds 5 \
--function-response-types ReportBatchItemFailures
# DynamoDB Streams trigger
aws lambda create-event-source-mapping \
--function-name stream-processor \
--event-source-arn arn:aws:dynamodb:us-east-1:123456789012:table/my-table/stream/2026-01-01T00:00:00.000 \
--batch-size 100 \
--starting-position LATEST \
--maximum-retry-attempts 3 \
--bisect-batch-on-function-error \
--destination-config '{"OnFailure":{"Destination":"arn:aws:sqs:us-east-1:123456789012:dlq"}}'
# S3 event notification (via Lambda permission + S3 config)
aws lambda add-permission \
--function-name image-processor \
--statement-id s3-trigger \
--action lambda:InvokeFunction \
--principal s3.amazonaws.com \
--source-arn arn:aws:s3:::my-uploads-bucket \
--source-account 123456789012
aws s3api put-bucket-notification-configuration \
--bucket my-uploads-bucket \
--notification-configuration '{
"LambdaFunctionConfigurations": [{
"LambdaFunctionArn": "arn:aws:lambda:us-east-1:123456789012:function:image-processor",
"Events": ["s3:ObjectCreated:*"],
"Filter": {"Key": {"FilterRules": [{"Name": "suffix", "Value": ".jpg"}]}}
}]
}'
# Schedule with EventBridge (cron)
aws events put-rule \
--name daily-cleanup \
--schedule-expression "cron(0 2 * * ? *)" \
--state ENABLED
aws lambda add-permission \
--function-name daily-cleanup \
--statement-id eventbridge \
--action lambda:InvokeFunction \
--principal events.amazonaws.com \
--source-arn arn:aws:events:us-east-1:123456789012:rule/daily-cleanup
aws events put-targets \
--rule daily-cleanup \
--targets '[{"Id":"1","Arn":"arn:aws:lambda:us-east-1:123456789012:function:daily-cleanup"}]'
# Create a function URL (public HTTPS endpoint)
aws lambda create-function-url-config \
--function-name my-api-handler \
--auth-type NONE \
--cors '{
"AllowOrigins": ["https://myapp.com"],
"AllowMethods": ["GET", "POST"],
"AllowHeaders": ["Content-Type"],
"MaxAge": 86400
}'
# Grant public invoke for function URL
aws lambda add-permission \
--function-name my-api-handler \
--statement-id function-url-public \
--action lambda:InvokeFunctionUrl \
--principal "*" \
--function-url-auth-type NONE
# Enable provisioned concurrency to eliminate cold starts
aws lambda put-provisioned-concurrency-config \
--function-name my-api-handler \
--qualifier live \
--provisioned-concurrent-executions 10
# Set reserved concurrency (throttle limit)
aws lambda put-function-concurrency \
--function-name my-api-handler \
--reserved-concurrent-executions 100
# Enable SnapStart for Java functions (near-zero cold starts)
aws lambda update-function-configuration \
--function-name my-java-handler \
--snap-start '{"ApplyOn": "PublishedVersions"}'
aws lambda publish-version --function-name my-java-handler
Cold start reduction tips:
arm64 architecture (Graviton) for faster init and lower cost# template.yaml - AWS SAM application
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: My serverless API
Globals:
Function:
Runtime: python3.12
Architectures: [arm64]
MemorySize: 256
Timeout: 30
Tracing: Active
Environment:
Variables:
STAGE: !Ref Stage
LOG_LEVEL: INFO
Parameters:
Stage:
Type: String
Default: dev
AllowedValues: [dev, staging, prod]
Resources:
ApiFunction:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub "${Stage}-api-handler"
Handler: app.handler
CodeUri: src/
Layers:
- !Ref DepsLayer
Events:
GetItems:
Type: Api
Properties:
Path: /items
Method: get
PostItem:
Type: Api
Properties:
Path: /items
Method: post
Policies:
- DynamoDBCrudPolicy:
TableName: !Ref ItemsTable
QueueProcessor:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub "${Stage}-queue-processor"
Handler: sqs_processor.handler
CodeUri: src/
Events:
SQSEvent:
Type: SQS
Properties:
Queue: !GetAtt ProcessingQueue.Arn
BatchSize: 10
FunctionResponseTypes:
- ReportBatchItemFailures
DepsLayer:
Type: AWS::Serverless::LayerVersion
Properties:
LayerName: common-deps
ContentUri: layer/
CompatibleRuntimes:
- python3.12
ItemsTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: !Sub "${Stage}-items"
BillingMode: PAY_PER_REQUEST
AttributeDefinitions:
- AttributeName: id
AttributeType: S
KeySchema:
- AttributeName: id
KeyType: HASH
ProcessingQueue:
Type: AWS::SQS::Queue
Properties:
QueueName: !Sub "${Stage}-processing"
VisibilityTimeout: 360
Outputs:
ApiEndpoint:
Value: !Sub "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/Prod"
# SAM CLI commands
sam build
sam local invoke ApiFunction --event events/get-items.json
sam local start-api --port 3000
sam deploy --guided
sam logs --name ApiFunction --stack-name my-stack --tail
| Problem | Cause | Fix |
|---|---|---|
| Function times out | Timeout too low or downstream slow | Increase timeout; check VPC/NAT config |
| Out of memory | Memory limit too small | Increase --memory-size; profile with CloudWatch Insights |
| Permission denied on AWS API | Execution role missing policy | Attach required policy to the execution role |
| Cold starts > 5s | Large package or VPC overhead | Use layers, arm64, provisioned concurrency; remove VPC if not needed |
| SQS messages reprocessed | Visibility timeout < function timeout | Set queue visibility timeout to 6x function timeout |
| Event source mapping disabled | Too many consecutive errors | Fix the function error; re-enable the mapping |
| Layer not found | Wrong region or deleted version | Verify layer ARN region matches function region |
| Canary deployment not shifting | Alias routing config wrong | Verify version numbers in routing config |
| Cannot invoke function URL | Missing resource-based policy | Add lambda:InvokeFunctionUrl permission |
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
中文简介正在准备中。当前显示原文说明。
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
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Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
中文简介正在准备中。当前显示原文说明。
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
中文简介正在准备中。当前显示原文说明。
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
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Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
中文简介正在准备中。当前显示原文说明。