SOA-C03 Exam Dumps - Amazon Web Services AWS Certified Associate Questions and Answers

High availability for an EC2-based web application behind an ALB is primarily achieved by eliminating single points of failure at the infrastructure layer. A single Availability Zone (AZ) deployment is vulnerable to AZ-level impairment (power/network issues, facility events, or service disruptions). The most direct and standard AWS approach is to distribute the Auto Scaling group across multiple AZs within the same Region.

Updating the Auto Scaling group to use subnets in at least two AZs allows instances to be launched across AZs automatically. The ALB is built to route traffic across targets in multiple AZs, and Auto Scaling can replace unhealthy instances in any enabled AZ. This provides resilience without the complexity of multi-Region architectures.

Options A and B address capacity for peak load but do not address the core availability requirement. Even with more instances, a full AZ outage would still take the entire application down if all instances are in the same AZ.

Option D (multi-Region) can improve resilience further, but it introduces significantly more operational overhead: cross-Region traffic routing, data replication, DNS failover strategy, application state handling, and potentially active-active or active-passive designs. For “make the application highly available” from a single-AZ baseline, multi-AZ in the same Region is the standard, least-overhead improvement.

The AWS Cloud Operations and Governance documentation defines that enabling Organizational View in AWS Health allows the management account in AWS Organizations to view and aggregate health events from all member accounts.

This feature provides a single-pane-of-glass view of service health issues, account-specific events, and planned maintenance across the organization — without requiring additional automation or data pipelines.

Alternative options (B, C, and D) require custom integration and ongoing maintenance. CloudTrail does not natively forward AWS Health events, and custom Lambda or DynamoDB approaches increase complexity.

Therefore, Option A — enabling the Organizational View feature in AWS Health — is the most operationally efficient and AWS-recommended solution.

The symptoms point to two common database pressure sources: inefficient queries (driving high CPU and latency) and excessive concurrent connections (driving connection management overhead, read contention, and timeouts). The most effective remediation is to address both the SQL workload and the connection surge behavior.

Amazon RDS Performance Insights (Option A) is designed to help identify which SQL statements and wait events contribute most to database load. It provides a database-centric view of performance that highlights top SQL, top waits, and the relative impact of sessions on CPU and other resources. By using Performance Insights to pinpoint the highest-impact SQL and then tuning those queries (for example, improving indexes, reducing full scans, and optimizing query patterns), the company can lower CPU utilization and reduce query latency during peak hours.

Connection surges are best addressed with a managed connection pooling layer. RDS Proxy (Option E) provides connection pooling and multiplexing between application connections and the database, which reduces the overhead of establishing and maintaining a large number of database connections. During spikes, the proxy can smooth bursty connection behavior, improve failover handling, and reduce the risk of overwhelming the database with too many concurrent connections. This directly targets the observed timeouts and read performance degradation tied to surges.

Option B is not the best fit because CloudWatch Logs Insights is a log analytics tool; it is not the primary mechanism for deep SQL performance attribution in RDS and typically requires extensive logging configurations that add overhead. Option C would reduce availability and does not improve performance. Option D would make the problem worse: disabling pooling increases connection churn and overhead, amplifying timeouts and latency during peak traffic.

Therefore, combining Performance Insights query analysis/tuning with RDS Proxy connection pooling best resolves both root causes.

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VPC Flow Logs require permissions to create log groups and log streams in Amazon CloudWatch Logs. If the IAM role associated with the flow log lacks the logs:CreateLogGroup permission, CloudWatch Logs cannot be created and no logs will appear.

Option B is unrelated because CreateExportTask is used for exporting logs, not publishing them. IPv6 configuration and VPC peering do not prevent flow logs from being delivered.

Ensuring the IAM role has the correct CloudWatch Logs permissions resolves the issue.

As documented in AWS Cloud Operations and Database Recovery, Aurora Backtrack allows you to rewind the existing database cluster to a chosen point in time without creating a new cluster. This feature supports fine-grained rollback for accidental data changes, making it ideal for scenarios like table deletions or logical corruption.

Backtracking maintains continuous transaction logs and permits rewinding within a configurable window (up to 72 hours). It does not require creating a new cluster or endpoint, and it preserves the same production environment, fulfilling the operational requirement for in-place recovery.

In contrast, Point-in-Time Recovery (Option D) always creates a new cluster, while replica promotion (Option A) and Lambda restoration (Option B) are unrelated to immediate rollback operations.

Therefore, Option C, using Aurora Backtrack, best meets the requirement for same-cluster restoration and minimal downtime.

The number of AWS Trusted Advisor checks available to an account depends on the AWS Support plan associated with the account. The Basic and Developer support plans provide access to a limited set of Trusted Advisor checks, primarily focused on security and service limits.

The Business and Enterprise support plans provide full access to all Trusted Advisor checks, including cost optimization, performance, fault tolerance, and security categories.

Running EC2 instances, SCPs, or MFA settings do not affect the availability of Trusted Advisor checks.

Therefore, the AWS Support plan determines the quantity of available Trusted Advisor checks.

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

For high availability and fast failover, ElastiCache for Redis supports replication groups with Multi-AZ and automatic failover. CloudOps guidance states that a primary node can be paired with one or more replicas across multiple Availability Zones; if the primary fails, Redis automatically promotes a replica to primary in seconds, thereby minimizing RTO. This architecture maintains in-memory data continuity without waiting for backup restore operations. Backups (Options B and D) provide durability but require restore and re-warm procedures that increase RTO and may impact application latency. Switching engines (Option A) to Memcached does not provide Redis replication/failover semantics and would not inherently improve resilience for this use case. Therefore, creating a read replica in a different AZ and enabling Multi-AZ with automatic failover is the prescribed CloudOps pattern to increase resilience and achieve the lowest practical RTO for Redis caches.

EC2 Instance Connect Endpoint (EICE) enables secure SSH access to instances in private subnets without requiring public IP addresses, bastion hosts, or inbound internet access. By deploying the endpoint in the private subnet, administrators can connect securely using IAM-based authentication.

The instance security group must allow inbound SSH (port 22) from the EICE security group. Access control is handled via IAM, which eliminates the need to distribute or manage SSH keys.

Option B incorrectly attempts to use Systems Manager for SSH, which is unnecessary when EICE is available. Option C incorrectly places the endpoint in a public subnet, which does not align with the requirement to keep access private. Option D is incorrect because Systems Manager Session Manager does not require SSH and AmazonEC2ReadOnlyAccess does not allow instance access.

EICE provides the least overhead and most secure SSH access path for private EC2 instances.

Auto Scaling groups with target tracking scaling policies automatically adjust capacity based on real-time demand. This solution is ideal for handling unpredictable and random traffic spikes.

Target tracking scaling maintains a metric, such as average CPU utilization or request count per target, at a defined target value. The Auto Scaling group automatically launches or terminates instances as traffic fluctuates.

Manual scaling, EventBridge-based scaling, or scheduled scaling do not respond dynamically to random traffic patterns.

Therefore, an Auto Scaling group with a target tracking scaling policy is the correct solution.