Lambda with DynamoDB Streams in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Lambda Trigger Behavior on DynamoDB Stream Batch

You have a Lambda function triggered by a DynamoDB stream with batch size set to 5. The stream receives 7 new records at once. How many times will the Lambda function be invoked?

A The Lambda function will be invoked 2 times: once with 5 records and once with 2 records.

B The Lambda function will be invoked 1 time with 7 records in the batch.

C The Lambda function will be invoked 7 times, once per record.

D The Lambda function will not be invoked automatically.

💡 Hint

Think about how batch size controls the maximum number of records per invocation.

The batch size limits the number of records per Lambda invocation. With 7 records and batch size 5, Lambda is invoked twice: first with 5 records, then with 2.

❓ Architecture

intermediate

Ensuring Exactly-Once Processing with Lambda and DynamoDB Streams

You want to process DynamoDB stream records with a Lambda function ensuring each record is processed exactly once, even if retries happen. Which architectural choice helps achieve this?

A Use Lambda with DynamoDB Streams and implement idempotent processing in the Lambda function.

B Use Lambda with DynamoDB Streams and set batch size to 1 to avoid retries.

C Use Lambda with DynamoDB Streams and rely on Lambda's automatic retry without additional logic.

D Use Lambda with DynamoDB Streams and disable the stream to prevent duplicate processing.

💡 Hint

Consider how retries can cause duplicate processing and how to handle it.

Lambda retries can cause the same record to be processed multiple times. Implementing idempotent logic in the Lambda function ensures processing is safe and exactly-once.

❓ Configuration

advanced

Configuring Lambda Event Source Mapping for DynamoDB Streams

Given this AWS CLI command to create an event source mapping for a Lambda function triggered by a DynamoDB stream, what is the effect of the --starting-position TRIM_HORIZON parameter?

aws lambda create-event-source-mapping \
  --function-name MyLambdaFunction \
  --event-source-arn arn:aws:dynamodb:us-east-1:123456789012:table/MyTable/stream/2023-01-01T00:00:00.000 \
  --starting-position TRIM_HORIZON \
  --batch-size 10

A The Lambda function will start processing only new records added after the mapping is created.

B The Lambda function will ignore the stream and run on a schedule.

C The Lambda function will process records in reverse order, starting from the newest.

D The Lambda function will start processing from the oldest available record in the stream.

💡 Hint

Think about what 'TRIM_HORIZON' means in stream processing.

TRIM_HORIZON means the Lambda starts reading from the oldest record available in the stream, processing all existing records.

❓ security

advanced

IAM Permissions for Lambda to Read DynamoDB Streams

Which IAM permission is required for a Lambda function to read records from a DynamoDB stream?

A dynamodb:DeleteItem

B dynamodb:PutItem

C dynamodb:GetRecords

D lambda:InvokeFunction

💡 Hint

Consider what action allows reading stream records.

The permission dynamodb:GetRecords allows Lambda to read records from the DynamoDB stream.

✅ Best Practice

expert

Handling Partial Failures in Lambda Processing of DynamoDB Streams

Your Lambda function processes batches of DynamoDB stream records. If processing one record in the batch fails, what is the best practice to avoid losing other successfully processed records?

A Set batch size to 1 to avoid batch failures.

B Process records individually inside Lambda and handle failures per record, using partial batch response feature.

C Let the entire batch fail so Lambda retries all records, including successful ones.

D Disable retries in Lambda to prevent duplicate processing.

💡 Hint

Think about how to handle failures without reprocessing successful records.

Using the partial batch response feature lets Lambda acknowledge successful records and retry only failed ones, avoiding duplicate processing of successful records.