Free Amazon Web Services SOA-C03 Practice Exam with Questions & Answers

The AWS Cloud Operations and Compute documentation explains that placement groups control how EC2 instances are physically arranged within AWS data centers to optimize network performance.

Among the available placement strategies:

Cluster placement groups place instances physically close together within a single Availability Zone, connected through high-bandwidth, low-latency networking (ideal for tightly coupled, HPC, or distributed workloads).

Spread placement groups distribute instances across distinct racks or Availability Zones for fault tolerance, increasing latency.

Partition placement groups separate instances into partitions for isolation, not latency reduction.

Therefore, to minimize latency for workloads such as computational clusters, the CloudOps engineer should use a cluster placement group. This placement ensures single-digit microsecond latency and enhanced packet rate performance between instances.

Elastic IPs (Option B) do not influence internal networking. Jumbo frames (Option C) can marginally improve throughput but do not reduce propagation latency. Spread placement (Option D) increases distance, worsening latency.

Hence, Option A — using a cluster placement group — delivers the lowest possible network latency and is AWS’s best-practice design for HPC-style clusters.

CloudWatch Logs data protection provides native redaction/masking of sensitive data at ingestion and query. AWS documentation states it can “detect and protect sensitive data in logs” using data identifiers, and that authorized users can “use the unmask action to view the original data.” Creating a data protection policy on the log group masks PII by default for all viewers, satisfying the requirement to redact personal information. Granting only the security team permission to invoke the unmask API operation ensures that unredacted content is restricted. Option B (KMS) encrypts at rest but does not redact fields; encryption alone does not prevent plaintext visibility to authorized readers. Options A and D add complexity and latency, move data out of CloudWatch, and do not provide default inline redaction/unmask controls in CloudWatch itself. Therefore, the CloudOps-aligned, managed solution is to use CloudWatch Logs data protection with appropriate data identifiers and unmask permissions limited to the security team.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Monitoring & Logging

• Amazon CloudWatch Logs – Data Protection (masking/redaction with data identifiers)

• CloudWatch Logs – Permissions for masking and unmasking sensitive data

• AWS Well-Architected Framework – Security and Operational Excellence (sensitive data handling)

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

AWS CloudFormation supports the DeletionPolicy attribute to control what happens to a resource when a stack is deleted. For Amazon RDS DB instances, setting DeletionPolicy: Snapshot instructs CloudFormation to retain a final DB snapshot automatically at stack deletion. CloudOps best practice recommends using this native mechanism for data retention and auditability, avoiding manual scripts or out-of-band processes. Options A, B, and D introduce operational overhead and potential human error. With DeletionPolicy set to Snapshot, the environment can be repeatedly created and torn down while preserving data states for later restoration with minimal manual steps. This aligns with IaC principles—declarative, repeatable, and reliable—and supports efficient lifecycle management of ephemeral development stacks.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Deployment, Provisioning and Automation

• AWS CloudFormation User Guide – DeletionPolicy Attribute (Snapshot for RDS)

• AWS Well-Architected Framework – Operational Excellence Pillar

The AWS Cloud Operations and Security documentation specifies that for Amazon CloudFront, automatic certificate renewal is only supported for certificates issued by AWS Certificate Manager (ACM). When a certificate is managed by ACM and validated through DNS validation, ACM automatically renews the certificate before expiration without requiring manual intervention.

Option A ensures that the certificate is issued and managed by ACM, enabling full integration with CloudFront. Option E (DNS validation) is essential for automation; AWS performs revalidation automatically as long as the DNS validation record remains in place.

By contrast, email validation (Option D) requires manual user confirmation upon renewal, which prevents automatic renewals. Certificates issued by third-party certificate authorities (Option B) are manually managed and must be reimported into ACM after renewal. CloudFront does not have a direct feature (Option C) to renew certificates; it relies on ACM’s lifecycle management.

Thus, combining ACM-issued certificates (A) with DNS validation (E) ensures continuous, automated renewal with no downtime or human action required.

The AWS Cloud Operations and Infrastructure-as-Code documentation specifies that when using AWS CloudFormation, resources are created in parallel by default unless explicitly ordered using DependsOn.

If a custom resource (Lambda) depends on another resource (like an EC2 instance) to exist before execution, a DependsOn attribute must be added to enforce creation order. This ensures the EC2 instance is launched and available before the custom resource executes its automation logic.

Updating the service token (Option B) doesn’t affect order of execution. The cfn-response module (Option C) handles callback communication but not sequencing. Fn::If (Option D) is for conditional creation, not dependency control.

Therefore, Option A is correct — adding a DependsOn attribute guarantees that CloudFormation provisions the EC2 instance before executing the Lambda custom resource.

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.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Reliability and Business Continuity

• Amazon ElastiCache for Redis – Replication Groups, Multi-AZ, and Automatic Failover

• AWS Well-Architected Framework – Reliability Pillar

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).

According to the AWS Cloud Operations and ElastiCache documentation, cache evictions occur when the cache runs out of memory and must remove items to make space for new data.

To reduce evictions and retain frequently accessed items, AWS recommends increasing the total available memory — either by scaling up to larger node types or scaling out by adding shards/nodes. Migrating to a cluster with larger nodes is the simplest and most efficient solution because it immediately expands capacity without architectural changes.

Adjusting TTL (Options B and C) controls expiration timing, not memory allocation. Adding a single node (Option A) may help, but redistributing data requires resharding, introducing more complexity.

Thus, Option D provides the lowest operational overhead and ensures high cache hit rates by increasing total cache memory.

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.

High availability requires removing single-AZ risk and eliminating manual recovery. The AWS Reliability best practices state to design for multi-AZ and automatic healing: Auto Scaling “helps maintain application availability and allows you to automatically add or remove EC2 instances” (AWS Auto Scaling User Guide). The Reliability Pillar recommends to “distribute workloads across multiple Availability Zones” and to “automate recovery from failure” (AWS Well-Architected Framework – Reliability Pillar). Attaching the Auto Scaling group to an ALB target group enables health-based replacement: instances failing load balancer health checks are replaced and traffic is routed only to healthy targets. Using an AMI in a launch template ensures consistent, repeatable instance configuration (AWS EC2 Launch Templates). Options A and C keep all instances in a single Availability Zone and rely on manual or ad-hoc restarts, which do not meet high-availability or resiliency goals. Option B only scales vertically and adds a restart rule; it neither removes the single-AZ failure domain nor provides automated replacement. Therefore, creating a multi-AZ EC2 Auto Scaling group with a launch template and attaching it to the ALB target group (Option D) is the CloudOps-aligned solution for resilience and business continuity.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide: Domain 2 – Reliability and Business Continuity

• AWS Well-Architected Framework – Reliability Pillar

• Amazon EC2 Auto Scaling User Guide – Health checks and replacement

• Elastic Load Balancing User Guide – Target group health checks and ALB integration

• Amazon EC2 Launch Templates – Reproducible instance configuration