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The AWS Certified CloudOps Engineer - Associate (SOA-C03) is one of the popular exams of SOA-C03. It is designed for Amazon aspirants who want to earn the AWS Certified CloudOps Engineer - Associate (SOA-C03) certification and validate their skills. The SOA-C03 test is not an easy exam to crack. It requires dedication and a lot of hard work. You need to prepare well to clear the SOA-C03 test on the first attempt. One of the best ways to prepare successfully for the SOA-C03 examination in a short time is using real Amazon SOA-C03 Exam Dumps.

Amazon SOA-C03 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 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 (Q119-Q124):

NEW QUESTION # 119
An application uses an Amazon Aurora MySQL DB cluster that includes one Aurora Replica. The application' s read performance degrades when there are more than 200 user connections. The number of user connections is approximately 180 on a consistent basis. Occasionally, the number of user connections increases rapidly to more than 200.
A CloudOps engineer must implement a solution that will scale the application automatically as user demand increases or decreases.
Which solution will meet these requirements?

Answer: A

Explanation:
Aurora Auto Scaling can automatically add or remove Aurora Replicas based on target metrics, including average connections across Aurora Replicas. AWS documentation lists "Average connections of Aurora Replicas" as a target metric when adding an auto scaling policy to an Aurora DB cluster. Because performance degrades above 200 connections and baseline usage is around 180, setting a target near 195 allows scaling to begin before the connection count crosses the problem threshold. Option A is vertical scaling and does not automatically respond to fluctuating demand. Option B is not how Aurora switches between provisioned and serverless modes during spikes. Option C is unnecessary and does not address read scaling with replicas. Therefore, an Aurora auto scaling policy using the database connections metric is correct.


NEW QUESTION # 120
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?

Answer: C

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 # 121
A CloudOps engineer has successfully deployed a VPC with an AWS CloudFormation template The CloudOps engineer wants to deploy the same template across multiple accounts that are managed through AWS Organizations.
Which solution will meet this requirement with the LEAST operational overhead?

Answer: D

Explanation:
AWS CloudFormation StackSets is purpose-built for deploying CloudFormation templates across multiple AWS accounts and Regions from a central management account. When integrated with AWS Organizations, StackSets automatically handles account targeting and stack synchronization with minimal manual effort, providing the lowest operational overhead compared to scripting or manual deployment approaches.


NEW QUESTION # 122
A company runs a critical application by using Amazon DynamoDB. During a recent deployment, the application accidentally wrote incorrect data to a DynamoDB table. The table has point-in-time recovery (PITR) enabled with continuous backups. DynamoDB Streams is enabled on the table. The company's recovery point objective (RPO) is 2 minutes.
A CloudOps engineer must restore the table to its state from 2 minutes before the corruption occurred.
Which solution will meet these requirements?

Answer: A

Explanation:
DynamoDB point-in-time recovery continuously backs up table data and can restore the table to a selected second within the recovery window. AWS documentation states that a PITR restore restores the data to a new table, not in place on the existing table. Therefore, the correct process is to restore the table to the timestamp two minutes before the corruption and then update the application to use the newly restored table. Option A is wrong because PITR does not update the existing table in place. Option C uses an on-demand snapshot, which might not meet the 2-minute RPO. Option D is unsafe because DynamoDB Streams are not a managed reverse-transaction rollback mechanism. PITR to a new table is the reliable recovery method.


NEW QUESTION # 123
A company has an internal web application that runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group in a single Availability Zone. A CloudOps engineer must make the application highly available.
Which action should the CloudOps engineer take to meet this requirement?

Answer: D

Explanation:
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.


NEW QUESTION # 124
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