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Amazon SOA-C03 Exam Syllabus Topics:
Topic
Details
Topic 1
- Reliability and Business Continuity: This section measures the skills of System Administrators and focuses on maintaining scalability, elasticity, and fault tolerance. It includes configuring load balancing, auto scaling, Multi-AZ deployments, implementing backup and restore strategies with AWS Backup and versioning, and ensuring disaster recovery to meet RTO and RPO goals.
Topic 2
- Security and Compliance: This section measures skills of Security Engineers and includes implementing IAM policies, roles, MFA, and access controls. It focuses on troubleshooting access issues, enforcing compliance, securing data at rest and in transit using AWS KMS and ACM, protecting secrets, and applying findings from Security Hub, GuardDuty, and Inspector.
Topic 3
- Monitoring, Logging, Analysis, Remediation, and Performance Optimization: This section of the exam measures skills of CloudOps Engineers and covers implementing AWS monitoring tools such as CloudWatch, CloudTrail, and Prometheus. It evaluates configuring alarms, dashboards, and notifications, analyzing performance metrics, troubleshooting issues using EventBridge and Systems Manager, and applying strategies to optimize compute, storage, and database performance.
Topic 4
- Deployment, Provisioning, and Automation: This section measures the skills of Cloud Engineers and covers provisioning and maintaining cloud resources using AWS CloudFormation, CDK, and third-party tools. It evaluates automation of deployments, remediation of resource issues, and managing infrastructure using Systems Manager and event-driven processes like Lambda or S3 notifications.
Topic 5
- Networking and Content Delivery: This section measures skills of Cloud Network Engineers and focuses on VPC configuration, subnets, routing, network ACLs, and gateways. It includes optimizing network cost and performance, configuring DNS with Route 53, using CloudFront and Global Accelerator for content delivery, and troubleshooting network and hybrid connectivity using logs and monitoring tools.
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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q57-Q62):
NEW QUESTION # 57
A company has a microservice that runs on a set of Amazon EC2 instances. The EC2 instances run behind an Application Load Balancer (ALB).
A CloudOps engineer must use Amazon Route 53 to create a record that maps the ALB URL to example.com.
Which type of record will meet this requirement?
- A. An alias record
- B. An AAAA record
- C. A CNAME record
- D. An A record
Answer: A
Explanation:
An alias record is the recommended Route 53 record type to map domain names (e.g., example.com) to AWS-managed resources such as an Application Load Balancer. Alias records are extension types of A or AAAA records that support AWS resources directly, providing automatic DNS integration and no additional query costs.
AWS documentation states:
"Use alias records to map your domain or subdomain to an AWS resource such as an Application Load Balancer, CloudFront distribution, or S3 website endpoint." A and AAAA records are used for static IP addresses, not load balancers. CNAME records cannot be used at the root domain (e.g., example.com). Thus, Option C is correct as it meets CloudOps networking best practices for scalable, managed DNS resolution to ALBs.
References (AWS CloudOps Documents / Study Guide):
* AWS Certified CloudOps Engineer - Associate (SOA-C03) Exam Guide - Domain 5: Networking and Content Delivery
* Amazon Route 53 Developer Guide - Alias Records
* AWS Well-Architected Framework - Reliability and Performance Efficiency Pillars
* Elastic Load Balancing - Integrating with Route 53
NEW QUESTION # 58
An ecommerce company uses Amazon ElastiCache (Redis OSS) for caching product queries. The CloudOps engineer observes a large number of cache evictions in Amazon CloudWatch metrics and needs to reduce evictions while retaining popular data in cache.
Which solution meets these requirements with the least operational overhead?
- A. Migrate to a new ElastiCache cluster with larger nodes.
- B. Add another node to the ElastiCache cluster.
- C. Increase the ElastiCache TTL value.
- D. Decrease the ElastiCache TTL value.
Answer: A
Explanation:
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.
NEW QUESTION # 59
A CloudOps engineer creates an AWS CloudFormation template to define an application stack that can be deployed in multiple AWS Regions. The CloudOps engineer also creates an Amazon CloudWatch dashboard by using the AWS Management Console. Each deployment of the application requires its own CloudWatch dashboard.
How can the CloudOps engineer automate the creation of the CloudWatch dashboard each time the application is deployed?
- A. Create a script by using the AWS CLI to run the aws cloudformation put-dashboard command with the name of the dashboard. Run the command each time a new CloudFormation stack is created.
- B. Export the existing CloudWatch dashboard as JSON. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Include the exported JSON in the resource's DashboardBody property.
- C. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Use the intrinsic Ref function to reference the ID of the existing CloudWatch dashboard.
- D. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Specify the name of the existing dashboard in the DashboardName property.
Answer: B
Explanation:
According to CloudOps automation and monitoring best practices, CloudWatch dashboards should be provisioned as infrastructure-as-code (IaC) resources using AWS CloudFormation to ensure consistency, repeatability, and version control. AWS CloudFormation supports the AWS::CloudWatch::Dashboard resource, where the DashboardBody property accepts a JSON object describing widgets, metrics, and layout.
By exporting the existing dashboard configuration as JSON and embedding it into the CloudFormation template, every deployment of the application automatically creates its corresponding dashboard. This method aligns with the CloudOps requirement for automated deployment and operational visibility within the same stack lifecycle.
AWS documentation explicitly states:
"Use the AWS::CloudWatch::Dashboard resource to create a dashboard from your template. You can include the same JSON you use to define a dashboard in the console." Option A requires manual execution. Options C and D incorrectly reference or reuse existing dashboards, failing to produce unique, deployment-specific dashboards.
References (AWS CloudOps Documents / Study Guide):
* AWS Certified CloudOps Engineer - Associate (SOA-C03) Exam Guide - Domain 1: Monitoring and Logging
* AWS CloudFormation User Guide - Resource Type: AWS::CloudWatch::Dashboard
* AWS Well-Architected Framework - Operational Excellence Pillar
* Amazon CloudWatch - Automating Dashboards with Infrastructure as Code
NEW QUESTION # 60
A company hosts a production MySQL database on an Amazon Aurora single-node DB cluster. The database is queried heavily for reporting purposes. The DB cluster is experiencing periods of performance degradation because of high CPU utilization and maximum connections errors. A CloudOps engineer needs to improve the stability of the database.
Which solution will meet these requirements?
- A. Create a multi-node Amazon ElastiCache cluster. Ensure that all reporting requests use the ElastiCache cluster. Use the database if the data is not in the cache.
- B. Create an Aurora Replica node. Create an Auto Scaling policy to scale replicas based on CPU utilization. Ensure that all reporting requests use the read-only connection string.
- C. Create a second Aurora MySQL single-node DB cluster in a second Availability Zone. Ensure that all reporting requests use the connection string for this additional node.
- D. Create an AWS Lambda function that caches reporting requests. Ensure that all reporting requests call the Lambda function.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Doocuments:
Amazon Aurora supports up to 15 Aurora Replicas that share the same storage volume and provide read scaling and improved availability. Official guidance states that replicas "offload read traffic from the writer" and that you should direct read-only workloads to the reader endpoint, reducing CPU pressure and connection counts on the primary. Aurora also supports Replica Auto Scaling through Application Auto Scaling policies using metrics such as CPU utilization or connections to add or remove replicas automatically. This design addresses both high CPU and maximum connections by moving reporting traffic to read replicas while keeping a single write primary for OLTP. Option B creates a separate cluster with independent storage, increasing operational overhead and data synchronization complexity. Options C and D introduce application-layer caching changes that may not guarantee data freshness or relieve the write node directly. Therefore, adding read replicas and routing reporting to the reader endpoint, with auto scaling based on load, is the least intrusive, CloudOps-aligned way to stabilize performance.
References (AWS CloudOps Documents / Study Guide):
* Amazon Aurora - Replicas and Reader Endpoint (Aurora User Guide)
* Aurora Replica Auto Scaling (Aurora & Application Auto Scaling Guides)
* AWS Well-Architected Framework - Reliability & Performance Efficiency
NEW QUESTION # 61
A company has an AWS CloudFormation template that includes an AWS::EC2::Instance resource and a custom resource (Lambda function). The Lambda function fails because it runs before the EC2 instance is launched.
Which solution will resolve this issue?
- A. Add a DependsOn attribute to the custom resource. Specify the EC2 instance in the DependsOn attribute.
- B. Use the Fn::If intrinsic function to check for the EC2 instance before the custom resource runs.
- C. Update the custom resource's service token to point to a valid Lambda function.
- D. Update the Lambda function to use the cfn-response module to send a response to the custom resource.
Answer: A
Explanation:
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.
NEW QUESTION # 62
......
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