Pass the Amazon Web Services AWS Certified Associate SOA-C03 Questions and answers with Dumpstech

According to the AWS Cloud Operations and Compute Optimizer documentation, Compute Optimizer provides right-sizing recommendations by analyzing Amazon CloudWatch metrics and instance configuration data. However, AWS explicitly notes that only supported instance types are included in Compute Optimizer analyses. If an EC2 instance type is newly released or not yet supported by Compute Optimizer, it will not appear in the Compute Optimizer dashboard until official support is added.

The documentation explains that “Compute Optimizer analyses only supported resource types and instance families. Instances using unsupported or newly launched instance types will not appear in the Compute Optimizer console.” This ensures the service provides accurate recommendations based on sufficient performance history and benchmark data.

While CloudWatch metrics are required for analysis, the complete absence of instances from the dashboard — rather than “insufficient metric data” notifications — indicates unsupported instance types. Compute Optimizer would normally still display those with limited metrics but would flag them as “insufficient data,” not remove them entirely.

Therefore, the most accurate cause of missing instances in this case is that Compute Optimizer does not support the newly released instance types, making option B correct.

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:

The correct answer is A because AWS KMS symmetric customer managed keys with automatic key rotation provide encryption, access control, and compliance with minimal operational effort. AWS CloudOps documentation states that Amazon EBS encryption supports AWS KMS symmetric keys only, and customer managed keys allow administrators to define custom key policies to control access.

Automatic key rotation is supported for symmetric customer managed keys and rotates the backing key material once every year, fully satisfying the company’s rotation requirement without manual intervention. This approach minimizes operational overhead while maintaining strong security controls and auditability.

Option B is incorrect because AWS owned keys do not allow custom key policies and therefore cannot meet the access control requirement. Option C is incorrect because asymmetric KMS keys are not supported for EBS encryption. Option D is incorrect because imported key material requires manual rotation and re-import, increasing operational complexity and risk.

AWS CloudOps security best practices strongly recommend customer managed symmetric keys with automatic rotation when organizations need fine-grained access control, regulatory compliance, and low maintenance overhead.

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:

The correct answers are B and D. AWS CloudOps documentation clearly states that AWS Secrets Manager is the recommended service for storing and managing database credentials securely. Secrets Manager integrates natively with Amazon RDS and supports automatic, scheduled secret rotation.

To rotate credentials weekly, Secrets Manager requires a Lambda rotation function. AWS provides managed rotation templates for Amazon RDS for MySQL that update the database password and the stored secret atomically. This combination ensures credentials are protected, rotated automatically, and audited with minimal operational effort.

Option A is incorrect because RDS Proxy does not store or rotate credentials; it only retrieves them from Secrets Manager. Option C is incorrect because Systems Manager Parameter Store does not support native automatic rotation. Option E is incorrect because Automation runbooks are not the recommended mechanism for secrets rotation and add unnecessary complexity.

AWS CloudOps best practices strongly recommend Secrets Manager with Lambda-based rotation for database credential protection and compliance.

The AWS Cloud Operations and Monitoring documentation specifies that the Amazon CloudWatch Agent is the recommended tool for collecting system and application logs from EC2 instances. The agent pushes these logs into a centralized CloudWatch Logs group, providing durable storage and real-time monitoring.

Once the logs are centralized, a CloudWatch Metric Filter can be configured to search for specific error keywords (for example, “ERROR” or “FAILURE”). This filter transforms matching log entries into custom metrics. From there, a CloudWatch Alarm can monitor the metric threshold and publish notifications to an Amazon SNS topic, which can send email or SMS alerts to subscribed recipients.

This combination provides a fully automated, managed, and serverless solution for log aggregation and error alerting. It eliminates the need for manual cron jobs (Option B), custom scripts (Option D), or Lambda-based log streaming (Option C).

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:

The correct answer is D because target tracking scaling policies are designed to automatically maintain a specific metric at a desired target value with the least administrative effort. AWS CloudOps documentation states that target tracking works like a thermostat, continuously adjusting capacity to keep the selected metric close to the defined target.

By specifying a target value of 40% average CPU utilization, the Auto Scaling group automatically scales out or in based on real-time demand without requiring manual thresholds, multiple alarms, or predefined scaling steps. This approach is fully managed by AWS and is the most operationally efficient option.

Option A is incorrect because scheduled scaling is based on predictable traffic patterns and cannot respond dynamically to real-time load changes. Option B is incorrect because simple scaling reacts only after an alarm is triggered and does not continuously maintain a target value. Option C is less efficient because step scaling requires additional configuration and tuning of scaling steps.

AWS CloudOps best practices clearly recommend target tracking scaling policies for maintaining steady performance metrics with minimal operational overhead.

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:

The requirement is preventative: stop users from launching from unapproved AMIs. The most scalable approach with 75 approved AMIs is to tag all approved AMIs (for example, ApprovedAMI=true) and enforce usage through an IAM policy condition that only allows ec2:RunInstances when the ec2:ImageId resource (the AMI) includes the required tag. This avoids maintaining long allow/deny lists of AMI IDs and supports continuous updates: as new approved AMIs are created, tagging them automatically brings them under the policy without policy rewrites.

Option B is incorrect because service-linked roles are used by AWS services, not assigned to users for interactive authorization enforcement in this way. Option C and D are detective/remedial controls that act after instances are already launched, which does not satisfy “must prevent.” They also increase operational overhead and risk disruptions.

According to the AWS Cloud Operations and Cost Management documentation, AWS Budgets is the recommended service to track and alert on cost thresholds across all AWS accounts and resources. It allows users to define cost, usage, or reservation budgets, and configure notifications to trigger when usage or cost reaches defined percentages of the budgeted value (e.g., 75%, 90%, 100%).

The AWS Budgets system integrates natively with Amazon Simple Notification Service (SNS) to deliver alerts to an email distribution list or SNS topic subscribers. AWS Budgets supports granular cost filters, including specific service categories such as data transfer, regions, or linked accounts, ensuring precise visibility into inter-Region transfer costs.

By contrast, CloudWatch billing alarms (Option B) monitor total account charges only and do not allow detailed service-level filtering, such as data transfer between Regions. Cost and Usage Reports (Option A) are for detailed cost analysis, not real-time alerting, and VPC Flow Logs (Option D) capture traffic data, not billing or cost-based metrics.

Thus, using AWS Budgets with a 75% alert threshold best satisfies the operational and notification requirements.

According to the AWS Cloud Operations and Security documentation, AWS CloudTrail is the authoritative service for recording API activity across all AWS services within an account.

When an access key is compromised, CloudTrail logs all API requests made using that key, including details such as:

The user identity (access key ID) that made the request,

The service, operation, resource, and timestamp affected, and

The source IP address and region of the request.

By searching the CloudTrail event history for the specific access key ID, the CloudOps engineer can identify every action performed by that key during the suspected breach window.

Other options are incorrect:

EventBridge (A) is event-driven, not historical.

CloudWatch Logs (B) monitors system logs, not AWS API activity.

VPC Flow Logs (D) track network-level traffic, not API calls.

Therefore, the correct solution is Option C — using AWS CloudTrail event history to audit and trace all actions executed via the compromised access key.

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:

The requirement is that traffic from a VPC-connected Lambda to Amazon S3 must not use public IP addresses. The AWS-native way to keep traffic private is to use VPC endpoints, which provide private connectivity to supported AWS services without traversing the public internet. Among the options, creating an S3 VPC endpoint is the only approach that satisfies “no public IP addresses” while allowing access to the bucket. Option D is the best match because it explicitly configures an S3 endpoint and directs the Lambda function to use the endpoint-specific DNS name for private routing.

Option C (NAT gateway) is incorrect for this requirement because NAT provides outbound internet access from private subnets and typically uses public IP addressing at the NAT gateway. That violates the intent to avoid public IP paths for S3 traffic. Option A is not applicable because S3 buckets are not placed “inside” a VPC and do not participate in VPC sharing in a way that provides private network paths. Option B (transit gateway) connects VPCs and on-prem networks, but it does not create private service connectivity to S3 by itself; you would still need the correct service endpoint solution for S3 access.

Using a VPC endpoint also aligns with CloudOps best practices: it reduces exposure, simplifies network egress controls, and supports least-privilege access via endpoint policies (where applicable) alongside IAM policies.

According to the AWS Cloud Operations, Governance, and Compliance documentation, AWS Config provides managed rules that automatically evaluate resource configurations for compliance. The “required-tags” managed rule allows CloudOps teams to specify mandatory tags (e.g., Environment, Owner, CostCenter) and automatically detect non-compliant resources such as DynamoDB tables.

Furthermore, AWS Config supports automatic remediation through AWS Systems Manager Automation runbooks, enabling correction actions (for example, adding missing tags) without manual intervention. This automation minimizes operational overhead and ensures continuous compliance across multiple accounts.

Using a custom Lambda function (Options A or B) introduces unnecessary management complexity, while EventBridge rules alone (Option D) do not provide resource compliance tracking or historical visibility.

Therefore, Option C provides the most efficient, fully managed, and compliant CloudOps solution.