Amazon Web Services SAA-C03 Exam With Confidence Using Practice Dumps

The correct answer isDbecause the application peak hours occur at thesame time each day, and the performance issue happens specifically at thestart of peak hours. This indicates that the company knows in advance when additional capacity will be needed. Ascheduled scaling policyis the most appropriate solution because it allows the Auto Scaling group to increase capacitybeforedemand rises, ensuring that instances are already launched and available when users begin accessing the application.

Dynamic scaling based on CPU or memory reacts onlyafterutilization increases. Because launching EC2 instances takes time, reactive scaling can lead to delays and degraded user experience at the beginning of peak periods. That directly matches the problem described in the question, where performance is slow at the start but normalizes later once capacity catches up. Scheduled scaling solves this by making capacity available proactively.

Option A is incorrect because an Application Load Balancer distributes traffic among existing instances but does not add capacity ahead of predictable demand. Option B is incorrect because Auto Scaling does not natively scale on memory utilization unless a custom metric is configured, and even then it would still be reactive rather than proactive. Option C is also incorrect because CPU-based dynamic scaling reacts after demand increases and therefore may not prevent the startup lag during peak traffic.

AWS design guidance recommends usingscheduled scalingwhen traffic patterns are predictable and occur at known times. This approach improves application responsiveness and user experience by making sure enough EC2 capacity is available before the workload surge begins.

Comprehensive and Detailed 250 to 300 words of Explanation (AWS documentation-based, no links):

To capture traffic metadata to and from network interfaces in a VPC, the correct telemetry source is VPC Flow Logs. Flow Logs can publish records to destinations such as CloudWatch Logs, which is a natural first landing zone for near-real-time log ingestion and centralized retention/permissions. The next requirement is to stream that data to Amazon OpenSearch Service for analysis with minimal operational overhead.

Amazon Data Firehose is purpose-built for fully managed delivery of streaming data to destinations including OpenSearch. Firehose handles buffering, batching, retry behavior, and optional transformations, and it minimizes the need to build and operate custom consumers. Therefore, sending VPC Flow Logs to CloudWatch Logs and then using Firehose to deliver to OpenSearch is an operationally efficient and scalable pattern.

Option A uses Kinesis Data Streams, which would require building/operating consumers (or additional integration components) to read from the stream and load into OpenSearch, adding operational complexity compared with Firehose’s managed delivery. Options C and D are incorrect because CloudTrail records API activity and governance events, not VPC network flow records; VPC Flow Logs do not publish to CloudTrail trails.

Thus, B best meets the requirement: Flow Logs capture the network interface traffic metadata; CloudWatch Logs provides near-real-time log collection; and Firehose provides managed streaming delivery into OpenSearch for indexing and analytics with minimal operational effort.

This solution leverages:

Amazon Redshift Spectrum to query S3 data directly from Redshift.

Amazon Athena for ad-hoc analysis of S3 data.

Amazon QuickSight for unified visualization from multiple data sources.

“Redshift Spectrum enables you to run queries against exabytes of data in Amazon S3 without having to load or transform the data.”

“QuickSight supports both Amazon Redshift and Amazon Athena as data sources.”

— Redshift Spectrum

— Amazon QuickSight Supported Data Sources

This architecture allows scalable querying and visualization with minimum ETL overhead, ideal for BI dashboards.

Incorrect Options:

A: The query editor is not a BI tool.

B, D: Grafana is better for time-series data, not structured analytics or BI reports.