Amazon Web Services DVA-C02 Exam With Confidence Using Practice Dumps

AWS Lambda is a service that lets developers run code without provisioning or managing servers. Lambda layers are a distribution mechanism for libraries, custom runtimes, and other dependencies. The developer can create a Lambda layer with the required Python library and use the layer in both Lambda functions. This will reduce the size of the Lambda deployment packages and avoid reaching the quota for the maximum size of zipped deployment packages. The developer can also benefit from using layers to manage dependencies separately from function code.

The correct answer is C because the requirement is for a live feed of log events in near real time , filtered to show only lines that begin with “ERROR.” The live tail feature for AWS Lambda and CloudWatch Logs is specifically intended for this kind of operational debugging. It allows developers to watch logs as they are generated and apply filtering so they can focus only on relevant messages during active troubleshooting.

This is particularly suitable because the function is already in production , and the company wants immediate visibility into timeout-related issues without waiting for a full batch of logs to accumulate. With live tail and a filter expression for ERROR , the developer can observe only the important log lines as new invocations happen, which speeds up root-cause analysis.

Option A is not the best answer because CloudWatch Logs Insights is powerful for querying logs, but it is primarily used for searching and analyzing logs after they have been collected, not as a continuous near-real-time live stream. Option B is incorrect because a subscription filter is used to forward logs to another destination such as Lambda, Kinesis, or Firehose; it is not the simplest way to give an operator a live interactive filtered view. A metric filter also creates metrics from log patterns but does not present the actual live log lines for review. Option D is incorrect because Amazon Athena is not used directly for querying CloudWatch Logs in real-time operational troubleshooting.

Therefore, the best solution is to use live tail with an ERROR filter to inspect relevant Lambda log events as they occur.

Amazon S3 automatically scales to handle high request rates, but request parallelism is optimized when objects are distributed across multiple prefixes. AWS documentation explains that S3 internally partitions data by key name, and distributing objects across multiple prefixes allows requests to be spread across multiple partitions.

When many GET requests target objects within the same prefix, they may contend for the same internal partition, limiting throughput. By designing object keys with multiple prefixes—such as including hashed or randomized components—applications can significantly increase parallel request handling.

Options A and D do not address S3 request partitioning. Global Accelerator improves network latency for supported endpoints but does not increase S3 request parallelism. Direct Connect improves network consistency but does not change how S3 scales requests internally. Option B worsens the problem by concentrating traffic into a single prefix.

Therefore, partitioning objects by prefixes is the correct and AWS-recommended solution.