An order-processing Lambda consumes messages from an Amazon SQS queue and writes results to a DynamoDB table. The Lambda runs with reserved concurrency. Customers report the order history page is delayed in showing processing status. Which actions should a DevOps engineer take to diagnose and fix the latency? (Choose two.)

The SQS ApproximateAgeOfOldestMessage metric indicates how long messages are waiting in the queue. A high value suggests the Lambda isn't processing messages fast enough. Increasing the Lambda's concurrency limit allows it to process more messages in parallel, reducing the backlog. The DynamoDB WriteThrottleEvents metric shows if writes to the table are being throttled. If this is high, the Lambda is trying to write more data than DynamoDB can handle, causing delays. Raising the maximum write capacity units (WCUs) in the table's autoscaling policy will allow DynamoDB to scale up and handle the write load. Configuring a redrive policy for SQS is for handling failed messages, not for improving processing speed. Increasing the SQS visibility timeout would hold messages longer, potentially worsening latency. Checking NumberOfMessagesSent only shows input volume, not processing issues. Increasing the Lambda function timeout addresses long-running individual invocations, not a backlog of messages, and the Throttles metric for Lambda would indicate the Lambda itself is being throttled, not necessarily that it's the bottleneck for SQS processing.