Idempotency for safe retries in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the key concept that ensures safe retries without side effects.

HLD

To make an operation safe for retries, it must be [1].

Drag options to blanks, or click blank then click option'

Aasynchronous

Bidempotent

Cstateful

Dblocking

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing idempotent with asynchronous or stateful operations.

An idempotent operation can be repeated multiple times without changing the result beyond the initial application. This ensures safe retries.

2fill in blank

medium

Complete the code to show how to use a unique identifier to achieve idempotency.

HLD

Store the result of a request using a unique [1] to avoid duplicate processing.

Drag options to blanks, or click blank then click option'

Atimestamp

Buser password

Csession token

Didempotency key

Attempts:

3 left

💡 Hint

Common Mistakes

Using timestamp or session token which do not guarantee uniqueness per request.

An idempotency key uniquely identifies a request so that retries with the same key do not cause duplicate effects.

3fill in blank

hard

Fix the error in the statement about idempotency in distributed systems.

HLD

In distributed systems, to ensure idempotency, the system must [1] requests with the same idempotency key.

Drag options to blanks, or click blank then click option'

Aignore duplicate

Bprocess all

Clog and discard

Dretry indefinitely

Attempts:

3 left

💡 Hint

Common Mistakes

Processing all duplicates causes repeated side effects.

The system must ignore duplicate requests with the same idempotency key to avoid repeated side effects.

4fill in blank

hard

Fill both blanks to complete the idempotency implementation snippet.

HLD

if request.[1] in cache:
    return cache[request.[2]]

Drag options to blanks, or click blank then click option'

Aidempotency_key

Brequest_id

Cuser_id

Dsession_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using different keys for check and fetch causes errors.

The idempotency_key is used to check and retrieve cached results to avoid duplicate processing.

5fill in blank

hard

Fill all three blanks to complete the idempotent request handling logic.

HLD

def handle_request(request):
    key = request.[1]
    if key in [2]:
        return [3][key]
    result = process(request)
    [2][key] = result
    return result

Drag options to blanks, or click blank then click option'

Aidempotency_key

Bcache

Ccache_store

Dsession

Attempts:

3 left

💡 Hint

Common Mistakes

Using different cache names or wrong key names causes errors.

The idempotency_key identifies the request. The cache stores results to return on retries, ensuring idempotency.

Practice

1. What is the main purpose of idempotency in system design for safe retries?

easy

A. To increase the number of retries allowed

B. To ensure repeated requests produce the same result without side effects

C. To speed up the processing of new requests

D. To encrypt data during transmission

Solution

1. Step 1: Understand idempotency concept

   Idempotency means that making the same request multiple times results in the same outcome without causing additional changes.

2. Step 2: Identify the purpose in retries

   In safe retries, idempotency prevents duplicate processing and side effects by returning the same result for repeated requests.

3. Final Answer:

   To ensure repeated requests produce the same result without side effects -> Option B

4. Quick Check:

   Idempotency = Same result, no side effects [OK]

Hint: Idempotency means retrying won't change the outcome [OK]

Common Mistakes:

• Confusing idempotency with performance optimization
• Thinking idempotency increases retry limits
• Assuming idempotency encrypts data

2. Which of the following is the correct way to implement idempotency in an API request?

easy

A. Retry the request without any tracking

B. Encrypt the request payload for security

C. Ignore request IDs and process every request as new

D. Use a unique request ID to detect duplicates and avoid reprocessing

Solution

1. Step 1: Identify idempotency implementation method

   Idempotency requires tracking requests to detect duplicates, typically using a unique request ID.

2. Step 2: Evaluate options

   Only using a unique request ID allows the system to recognize repeated requests and avoid reprocessing.

3. Final Answer:

   Use a unique request ID to detect duplicates and avoid reprocessing -> Option D

4. Quick Check:

   Unique request ID = Idempotency key [OK]

Hint: Unique request ID prevents duplicate processing [OK]

Common Mistakes:

• Retrying blindly without tracking
• Ignoring request IDs
• Confusing encryption with idempotency

3. Consider a system that stores results of processed requests keyed by a unique request ID. If a client sends the same request twice with the same ID, what will the system return on the second request?

medium

A. A new result generated by reprocessing

B. An error indicating duplicate request

C. The original result from the first request

D. A timeout response

Solution

1. Step 1: Understand stored result usage

   The system caches the result of the first request using the unique request ID.

2. Step 2: Determine response for repeated request

   When the same request ID is received again, the system returns the cached original result to maintain idempotency.

3. Final Answer:

   The original result from the first request -> Option C

4. Quick Check:

   Repeated request returns cached result [OK]

Hint: Same ID returns cached result, not reprocessed output [OK]

Common Mistakes:

• Expecting an error on duplicate requests
• Assuming reprocessing happens every time
• Confusing timeout with duplicate handling

4. A developer implemented idempotency by storing request IDs but forgot to store the response results. What problem will this cause on retries?

medium

A. The system will reprocess the request causing side effects

B. The system will return the original result correctly

C. The system will reject all requests

D. The system will crash due to missing data

Solution

1. Step 1: Analyze missing response storage impact

   Without storing the response, the system cannot return the original result on retries.

2. Step 2: Identify retry behavior

   Since the system lacks the cached result, it reprocesses the request, causing potential side effects and breaking idempotency.

3. Final Answer:

   The system will reprocess the request causing side effects -> Option A

4. Quick Check:

   Missing response storage = Reprocessing on retry [OK]

Hint: Store both request ID and response to avoid reprocessing [OK]

Common Mistakes:

• Assuming storing request ID alone is enough
• Expecting system to reject retries automatically
• Thinking system crashes without response data

5. You design a payment system that must be idempotent to handle retries safely. Which combination of techniques best ensures idempotency and prevents duplicate charges?

hard

A. Use unique request IDs, store payment results, and check before processing

B. Allow retries without tracking, rely on client to avoid duplicates

C. Encrypt payment data and retry immediately on failure

D. Process every request independently to ensure payment completion

Solution

1. Step 1: Identify idempotency requirements for payments

   Payments must not be charged multiple times on retries, so tracking requests and results is essential.

2. Step 2: Evaluate techniques for safe retries

   Using unique request IDs to detect duplicates, storing results to return on retries, and checking before processing prevents duplicate charges.

3. Final Answer:

   Use unique request IDs, store payment results, and check before processing -> Option A

4. Quick Check:

   Unique ID + stored result = Safe payment retries [OK]

Hint: Combine unique IDs and result storage for safe retries [OK]

Common Mistakes:

• Relying on client to avoid duplicates
• Ignoring result storage
• Processing every request without checks