DVA-C02 Show IP Route Output Practice Questions

Explanation: Increasing the batch size causes each invocation to process more messages, but if the function's reserved concurrency is too low, many invocations may be throttled. By increasing reserved concurrency, more invocations can run concurrently, allowing the function to consume messages from the queue faster and reduce the backlog. The batch size increase alone may not help if the function cannot run enough concurrent executions. Increasing memory can improve per-message processing speed but is less effective here since the bottleneck is concurrency. Using a FIFO queue does not address standard queue throughput. Decreasing the batch size would reduce throttling but not improve throughput.

Explanation: Amazon CloudWatch Agent can be installed on EC2 instances to collect operating system-level metrics, including memory utilization, and send them to CloudWatch. This provides visibility into memory usage over time without requiring code changes. The agent can be configured via Systems Manager or manually, and the metrics can be used to set alarms or analyze trends to detect memory leaks.

Explanation: Throttles occur when more concurrent Lambda invocations are attempted than the reserved concurrency allows. Increasing the batch size allows the function to process more messages per invocation, thus reducing the number of concurrent executions required to process the same backlog. This directly reduces the likelihood of hitting the reserved concurrency limit. Increasing reserved concurrency might help but does not reduce the number of invocations; it only raises the limit. Visibility timeout and message retention do not affect throttles. Therefore, increasing the batch size is the most effective action.

Explanation: The function's timeout is 30 seconds, and synchronous HTTP calls can take variable time. By using asynchronous HTTP calls, the function can initiate multiple requests concurrently and wait for all responses, reducing the total wall clock time. This allows processing more messages within the timeout, maximizing throughput. Increasing the timeout is possible but does not address the underlying latency and may hide issues. Reducing the batch size reduces throughput. Changing the SQS visibility timeout does not affect the Lambda function's execution timeout.

Explanation: The high IteratorAge indicates the function is not keeping up with the data flowing through the Kinesis stream. Each shard can be processed by only one Lambda invocation at a time (per shard). Increasing the number of shards increases the parallelism, allowing more concurrent Lambda invocations to process records, which directly reduces backpressure. Increasing batch size or memory may help but are less effective when the function is already throttled and the parallelism is limited by shard count.