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
• Common Patterns
• CLI Reference
• Best Practices
• Troubleshooting
• References

Core Concepts

Function

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

Invocation Types

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

Invocation

Event Sources

Permissions

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

• [Lambda Developer Guide](https://docs.aws.amazon.com