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lambda

AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

personAuthor: jakexiaohubgithub
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AWS Lambda

AWS Lambda runs code without provisioning servers. You pay only for compute time consumed. Lambda automatically scales from a few requests per day to thousands per second.

Table of Contents

Core Concepts

Function

Your code packaged with configuration. Includes runtime, handler, memory, timeout, and IAM role.

Invocation Types

| Type | Description | Use Case | |------|-------------|----------| | Synchronous | Caller waits for response | API Gateway, direct invoke | | Asynchronous | Fire and forget | S3, SNS, EventBridge | | Poll-based | Lambda polls source | SQS, Kinesis, DynamoDB Streams |

Execution Environment

Lambda creates execution environments to run your function. Components:

  • Cold start: New environment initialization
  • Warm start: Reusing existing environment
  • Handler: Entry point function
  • Context: Runtime information

Layers

Reusable packages of libraries, dependencies, or custom runtimes (up to 5 per function).

Common Patterns

Create a Python Function

AWS CLI:

# Create deployment package
zip function.zip lambda_function.py

# Create function
aws lambda create-function \
  --function-name MyFunction \
  --runtime python3.12 \
  --role arn:aws:iam::123456789012:role/lambda-role \
  --handler lambda_function.handler \
  --zip-file fileb://function.zip \
  --timeout 30 \
  --memory-size 256

# Update function code
aws lambda update-function-code \
  --function-name MyFunction \
  --zip-file fileb://function.zip

boto3:

import boto3
import zipfile
import io

lambda_client = boto3.client('lambda')

# Create zip in memory
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, 'w') as zf:
    zf.writestr('lambda_function.py', '''
def handler(event, context):
    return {"statusCode": 200, "body": "Hello"}
''')
zip_buffer.seek(0)

# Create function
lambda_client.create_function(
    FunctionName='MyFunction',
    Runtime='python3.12',
    Role='arn:aws:iam::123456789012:role/lambda-role',
    Handler='lambda_function.handler',
    Code={'ZipFile': zip_buffer.read()},
    Timeout=30,
    MemorySize=256
)

Add S3 Trigger

# Add permission for S3 to invoke Lambda
aws lambda add-permission \
  --function-name MyFunction \
  --statement-id s3-trigger \
  --action lambda:InvokeFunction \
  --principal s3.amazonaws.com \
  --source-arn arn:aws:s3:::my-bucket \
  --source-account 123456789012

# Configure S3 notification (see S3 skill)

Add SQS Event Source

aws lambda create-event-source-mapping \
  --function-name MyFunction \
  --event-source-arn arn:aws:sqs:us-east-1:123456789012:my-queue \
  --batch-size 10 \
  --maximum-batching-window-in-seconds 5

Environment Variables

aws lambda update-function-configuration \
  --function-name MyFunction \
  --environment "Variables={DB_HOST=mydb.cluster-xyz.us-east-1.rds.amazonaws.com,LOG_LEVEL=INFO}"

Create and Attach Layer

# Create layer
zip -r layer.zip python/

aws lambda publish-layer-version \
  --layer-name my-dependencies \
  --compatible-runtimes python3.12 \
  --zip-file fileb://layer.zip

# Attach to function
aws lambda update-function-configuration \
  --function-name MyFunction \
  --layers arn:aws:lambda:us-east-1:123456789012:layer:my-dependencies:1

Invoke Function

# Synchronous invoke
aws lambda invoke \
  --function-name MyFunction \
  --payload '{"key": "value"}' \
  response.json

# Asynchronous invoke
aws lambda invoke \
  --function-name MyFunction \
  --invocation-type Event \
  --payload '{"key": "value"}' \
  response.json

CLI Reference

Function Management

| Command | Description | |---------|-------------| | aws lambda create-function | Create new function | | aws lambda update-function-code | Update function code | | aws lambda update-function-configuration | Update settings | | aws lambda delete-function | Delete function | | aws lambda list-functions | List all functions | | aws lambda get-function | Get function details |

Invocation

| Command | Description | |---------|-------------| | aws lambda invoke | Invoke function | | aws lambda invoke-async | Async invoke (deprecated) |

Event Sources

| Command | Description | |---------|-------------| | aws lambda create-event-source-mapping | Add event source | | aws lambda list-event-source-mappings | List mappings | | aws lambda update-event-source-mapping | Update mapping | | aws lambda delete-event-source-mapping | Remove mapping |

Permissions

| Command | Description | |---------|-------------| | aws lambda add-permission | Add resource-based policy | | aws lambda remove-permission | Remove permission | | aws lambda get-policy | View resource policy |

Best Practices

Performance

  • Right-size memory: More memory = more CPU = faster execution
  • Minimize cold starts: Keep functions warm, use Provisioned Concurrency
  • Optimize package size: Smaller packages deploy faster
  • Use layers for shared dependencies
  • Initialize outside handler: Reuse connections across invocations
# GOOD: Initialize outside handler
import boto3
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('MyTable')

def handler(event, context):
    # Reuses existing connection
    return table.get_item(Key={'id': event['id']})

Security

  • Least privilege IAM roles — only grant needed permissions
  • Use Secrets Manager for sensitive data
  • Enable VPC only if needed (adds latency)
  • Encrypt environment variables with KMS

Cost Optimization

  • Set appropriate timeout — don't use max 15 minutes unnecessarily
  • Use ARM architecture (Graviton2) for 34% better price/performance
  • Batch process where possible
  • Use Reserved Concurrency to limit costs

Reliability

  • Configure DLQ for async invocations
  • Handle retries — async events retry twice
  • Make handlers idempotent
  • Use structured logging

Troubleshooting

Timeout Errors

Symptom: Task timed out after X seconds

Causes:

  • Function takes longer than timeout
  • Network call to unreachable resource
  • VPC configuration issues

Debug:

# Check function configuration
aws lambda get-function-configuration \
  --function-name MyFunction \
  --query "Timeout"

# Increase timeout
aws lambda update-function-configuration \
  --function-name MyFunction \
  --timeout 60

Out of Memory

Symptom: Function crashes with memory error

Fix:

aws lambda update-function-configuration \
  --function-name MyFunction \
  --memory-size 512

Cold Start Latency

Causes:

  • Large deployment package
  • VPC configuration
  • Many dependencies to load

Solutions:

  • Use Provisioned Concurrency
  • Reduce package size
  • Use layers for dependencies
  • Consider Graviton2 (ARM)
# Enable Provisioned Concurrency
aws lambda put-provisioned-concurrency-config \
  --function-name MyFunction \
  --qualifier LIVE \
  --provisioned-concurrent-executions 5

Permission Denied

Symptom: AccessDeniedException

Debug:

# Check execution role
aws lambda get-function-configuration \
  --function-name MyFunction \
  --query "Role"

# Check role policies
aws iam list-attached-role-policies \
  --role-name lambda-role

VPC Connectivity Issues

Symptom: Cannot reach internet or AWS services

Causes:

  • No NAT Gateway for internet access
  • Missing VPC endpoint for AWS services
  • Security group blocking outbound

Solutions:

  • Add NAT Gateway for internet
  • Add VPC endpoints for AWS services
  • Check security group rules

References