SOA-C03 Questions and Answers

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.

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 AWS Cloud Operations and Monitoring documentation states that Amazon CloudWatch Logs Insights provides a purpose-built query engine for analyzing and visualizing log data directly within CloudWatch. For Lambda, all invocation results (including errors) are automatically logged to CloudWatch Logs.

By querying these logs with CloudWatch Logs Insights, the CloudOps engineer can efficiently count the number of “ERROR” or “Exception” occurrences over the past 7 days using simple SQL-like commands. This method is serverless, cost-efficient, and real-time.

Athena (Options A and B) would require exporting data to Amazon S3, and OpenSearch (Option D) adds unnecessary operational complexity.

Thus, Option C provides the most efficient and native AWS CloudOps approach for rapid Lambda error analysis.

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.

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 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.

According to the AWS Cloud Operations and Compute documentation, when workloads exhibit predictable traffic patterns, the best practice is to use scheduled scaling for Amazon EC2 Auto Scaling groups.

With scheduled scaling, administrators can predefine the desired capacity of an Auto Scaling group to increase before anticipated demand (in this case, before the 2-hour peak) and scale back down afterward. This ensures that sufficient compute capacity is provisioned proactively, avoiding performance degradation while maintaining cost efficiency.

AWS notes: “Scheduled actions enable scaling your Auto Scaling group at predictable times, allowing you to pre-warm instances before demand spikes.”

Manual scaling (Option D) adds operational overhead. Adjusting launch templates (Option B) doesn’t affect scaling behavior, and permanently increasing minimum capacity (Option A) wastes resources outside of peak hours.

Thus, Option C provides an automated, cost-effective, and operationally efficient CloudOps solution.

AWS Systems Manager Session Manager allows secure, auditable instance access without SSH keys or inbound ports. To control access based on instance tags, CloudOps best practices require two configurations:

Attach an IAM policy to users or groups granting ssm:StartSession, ssm:DescribeInstanceInformation, and ssm:DescribeSessions.

Include a Condition element in the IAM policy referencing instance tags, such as Condition: {"StringEquals": {"ssm:resourceTag/Environment": "Production"}}.

This ensures users can start sessions only with instances that have matching tags, providing fine-grained access control.

AWS CloudOps documentation under Security and Compliance states:

“Use IAM policies with resource tags in the Condition element to restrict which managed instances users can access using Session Manager.”

Options B and D incorrectly suggest attaching roles or service accounts that are not relevant to user-level access control. Option C (placement groups) pertains to networking and performance, not access management. Therefore, A and E together provide tag-based, least-privilege access as required.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Domain 4: Security and Compliance

• AWS Systems Manager User Guide – Controlling Access to Session Manager Using Tags

• AWS IAM Policy Reference – Condition Keys for AWS Systems Manager

• AWS Well-Architected Framework – Security Pillar

According to the AWS Cloud Operations and Database Reliability documentation, Amazon RDS Multi-AZ deployments provide high availability and automatic failover by maintaining a synchronous standby replica in a different Availability Zone.

In the event of instance failure, planned maintenance, or Availability Zone outage, Amazon RDS automatically promotes the standby to primary with minimal downtime (typically less than 60 seconds). The failover is transparent to applications because the DB endpoint remains the same.

By contrast, read replicas (Option B) are asynchronous and do not provide automated failover. Auto Scaling (Option C) applies to EC2, not RDS. RDS Proxy (Option D) improves connection management but does not add redundancy.

Thus, Option A — converting the RDS instance into a Multi-AZ deployment — delivers the required high availability and business continuity with minimal operational effort.

According to the AWS Cloud Operations and Deployment documentation, EC2 Image Builder is the AWS-managed service for automating the creation, maintenance, validation, and deployment of secure and compliant Amazon Machine Images (AMIs).

It allows CloudOps teams to define image pipelines that include only approved software modules and configuration scripts. EC2 Image Builder automatically tests and verifies these AMIs for compliance before deployment.

This process ensures configuration consistency, eliminates manual installation errors, and simplifies ongoing patch management. The service integrates with AWS Systems Manager, Amazon Inspector, and AWS CloudFormation for end-to-end automation.

In contrast:

Amazon Detective and GuardDuty (Options A & B) are security monitoring tools, not image management solutions.

Run Command (Option C) applies ad-hoc updates but does not create standard, reusable AMIs.

Therefore, Option D is correct—EC2 Image Builder provides the most operationally efficient and compliant way to create an approved baseline AMI for future deployments.

Per the AWS Cloud Operations and Data Protection documentation, S3 Object Lock enforces write-once-read-many (WORM) protection on objects for a defined retention period.

There are two modes:

Compliance mode: Even the root user cannot delete or modify objects during the retention period.

Governance mode: Privileged users with special permissions can override lock settings.

For regulatory or audit requirements that prohibit deletion, Compliance mode is the correct choice. When configured with a 3-month retention period, all backup objects are protected from deletion until expiration, ensuring compliance with data retention mandates.

Versioning (Option C) alone does not prevent deletion. IAM-based restrictions (Option A) lack time-based enforcement and require manual intervention. Governance mode (Option D) is less strict and unsuitable for regulatory retention.

Thus, Option B is the correct CloudOps solution for immutable S3 backups.

The AWS Cloud Operations and Content Delivery documentation explains that Amazon CloudFront caches objects in edge locations for a defined time based on TTL settings or origin headers. When new content is deployed to the S3 origin, previously cached versions remain in edge caches until they expire.

To immediately serve the new version, CloudOps engineers must initiate a CloudFront invalidation, which removes cached objects from all edge locations. This forces CloudFront to fetch the latest version from the origin (S3).

Invalidations can target individual objects (e.g., /index.html) or wildcard paths (e.g., /*) and are the AWS-recommended approach for dynamic content refresh after static site updates.

Changing headers (Option A), enforcing HTTPS (Option B), or applying caching policies (Option C) do not directly refresh outdated cache content.

Thus, Option D — issuing a CloudFront invalidation — ensures users receive the latest website content immediately after deployment.

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.

According to the AWS Cloud Operations and EC2 Connectivity documentation, EC2 Instance Connect Endpoint allows access to instances without internet exposure or open SSH ports. However, for successful connectivity, the EC2 instance must have Systems Manager permissions through an IAM instance profile.

If no IAM instance profile is attached, the instance cannot establish a control channel with the Systems Manager service, and EC2 Instance Connect cannot authenticate the session.

Opening port 22 (Option B) is unnecessary and contradicts the private subnet design. HTTPS rules (Option A) are irrelevant because EC2 Instance Connect communicates through AWS APIs, not direct HTTPS connections. Recreating the instance with a key pair (Option D) bypasses the intended keyless connection mechanism.

Therefore, Option C — attaching an IAM instance profile with Systems Manager permissions — enables secure, private access through EC2 Instance Connect Endpoint.