Error handling and retries in DynamoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of error handling in DynamoDB operations?

Error handling helps detect and manage problems during database operations, ensuring the application can respond gracefully instead of crashing.

beginner

Why are retries important when working with DynamoDB?

Retries help recover from temporary issues like network glitches or throttling by trying the operation again after a short wait.

intermediate

What is exponential backoff in the context of retries?

Exponential backoff means waiting longer between each retry attempt, usually doubling the wait time, to reduce overload and increase chances of success.

intermediate

Name two common error types you should handle when using DynamoDB.

Common errors include ProvisionedThroughputExceededException (when request rate is too high) and ConditionalCheckFailedException (when a condition in the request is not met).

intermediate

How can you implement retries safely to avoid infinite loops?

Use a maximum retry count and exponential backoff delays. Stop retrying after the limit is reached and handle the failure appropriately.

What does a retry mechanism help with in DynamoDB operations?

A Recovering from temporary errors

B Increasing data size limits

C Changing table schemas automatically

D Encrypting data at rest

Retries help recover from temporary errors like throttling or network issues by trying the operation again.

Which error indicates that your request rate is too high for DynamoDB?

A ConditionalCheckFailedException

B ProvisionedThroughputExceededException

C ResourceNotFoundException

D ValidationException

ProvisionedThroughputExceededException means the request rate exceeded the provisioned capacity.

What is the best practice to avoid retry storms in DynamoDB?

A Use exponential backoff with jitter

B Ignore errors and continue

C Retry only once

D Retry immediately without delay

Exponential backoff with jitter spreads out retries to reduce load and avoid retry storms.

Which of these is NOT a good way to handle errors in DynamoDB?

A Stopping retries after a max count

B Retrying with exponential backoff

C Logging the error details

D Ignoring errors silently

Ignoring errors silently can hide problems and cause unexpected failures.

What should you do after reaching the maximum retry attempts?

A Keep retrying indefinitely

B Delete the DynamoDB table

C Log the failure and alert if needed

D Restart the application

After max retries, log the failure and alert to handle the issue properly.

Explain how exponential backoff helps in retrying DynamoDB operations.

Think about how waiting longer each time helps the system recover.

Describe the steps you would take to handle errors and retries when writing to a DynamoDB table.

Consider both detecting errors and managing retries safely.

Practice

1. What is the main purpose of using retries in DynamoDB error handling?

easy

A. To ignore all errors and continue processing

B. To permanently stop the operation when an error occurs

C. To automatically try the operation again after a temporary failure

D. To delete the data causing the error

Solution

1. Step 1: Understand retries in DynamoDB

   Retries are used to handle temporary errors like throttling by trying the operation again.

2. Step 2: Identify the purpose of retries

   Retries help keep the app stable by not failing immediately on temporary issues.

3. Final Answer:

   To automatically try the operation again after a temporary failure -> Option C

4. Quick Check:

   Retries = automatic retry after temporary failure [OK]

Hint: Retries mean trying again after temporary errors [OK]

Common Mistakes:

• Thinking retries stop all errors permanently
• Ignoring the need to check error types before retrying
• Assuming retries delete data

2. Which of the following is the correct way to catch a throttling exception in DynamoDB using Python?

easy

A. try:
# operation
except ThrottlingException:
# retry logic

B. try:
# operation
except Exception:
pass

C. if error == 'ThrottlingException':
retry()

D. catch ThrottlingException {
retry();
}

Solution

1. Step 1: Identify Python error handling syntax

   Python uses try-except blocks to catch exceptions, with except specifying the exception type.

2. Step 2: Match correct exception handling for throttling

   try: # operation except ThrottlingException: # retry logic correctly uses try-except with ThrottlingException to handle retries.

3. Final Answer:

   try: # operation except ThrottlingException: # retry logic -> Option A

4. Quick Check:

   Python try-except with specific exception = try: # operation except ThrottlingException: # retry logic [OK]

Hint: Python uses try-except to catch specific exceptions [OK]

Common Mistakes:

• Using incorrect syntax like catch instead of except
• Catching all exceptions without handling specific ones
• Using if statement instead of try-except for exceptions

3. Given this Python code snippet for DynamoDB, what will be the output if a throttling error occurs on the first attempt?

import boto3
from botocore.exceptions import ClientError

client = boto3.client('dynamodb')

try:
    response = client.put_item(TableName='MyTable', Item={'id': {'S': '123'}})
    print('Success')
except ClientError as e:
    if e.response['Error']['Code'] == 'ThrottlingException':
        print('Retrying...')
    else:
        print('Failed')

medium

A. Success

B. Retrying...

C. Failed

D. No output

Solution

1. Step 1: Understand the try-except block behavior

   If a ClientError occurs, the code checks the error code inside the except block.

2. Step 2: Check error code for throttling

   If the error code is 'ThrottlingException', it prints 'Retrying...'. Otherwise, it prints 'Failed'.

3. Final Answer:

   Retrying... -> Option B

4. Quick Check:

   Error code 'ThrottlingException' triggers 'Retrying...' [OK]

Hint: Check error code in except to decide output [OK]

Common Mistakes:

• Assuming success despite error
• Ignoring error code check and printing 'Failed'
• Expecting no output on error

4. Identify the error in this retry logic snippet for DynamoDB in Python:

try:
    response = client.get_item(TableName='MyTable', Key={'id': {'S': '123'}})
except ClientError as e:
    if e.response['Error']['Code'] == 'ThrottlingException':
        client.get_item(TableName='MyTable', Key={'id': {'S': '123'}})
    else:
        raise e

medium

A. No error, code retries correctly

B. Should not raise exception in else block

C. Error code check is incorrect

D. Retry call is not inside a try-except block

Solution

1. Step 1: Analyze retry call placement

   The retry call is made without a try-except block, so if it fails again, it will raise an unhandled exception.

2. Step 2: Understand proper retry handling

   Retries should be wrapped in try-except to handle repeated failures gracefully.

3. Final Answer:

   Retry call is not inside a try-except block -> Option D

4. Quick Check:

   Retry without try-except risks unhandled errors [OK]

Hint: Always wrap retries in try-except to catch repeated errors [OK]

Common Mistakes:

• Not wrapping retry calls in error handling
• Mischecking error codes
• Avoiding raising exceptions on unknown errors

5. You want to implement a retry mechanism for DynamoDB writes that retries up to 3 times with exponential backoff when a throttling error occurs. Which approach correctly combines error handling and retries?

hard

A. Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts

B. Call put_item once, then retry infinitely without delay on any error

C. Ignore errors and assume writes always succeed

D. Use try-except but do not check error codes before retrying

Solution

1. Step 1: Understand retry with exponential backoff

   Retries should be limited in number and wait time should increase to reduce load.

2. Step 2: Combine error handling and retry logic

   Use a loop with try-except to catch throttling errors, sleep with increasing delay, and stop after max retries.

3. Final Answer:

   Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts -> Option A

4. Quick Check:

   Retry loop + exponential backoff + error check = Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts [OK]

Hint: Retry with limited attempts and increasing delay on throttling [OK]

Common Mistakes:

• Retrying infinitely without delay
• Not checking error codes before retrying
• Ignoring errors completely