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Utilizing Exam SOA-C03 Pattern - Say Goodbye to AWS Certified CloudOps Engineer - Associate
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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q194-Q199):
NEW QUESTION # 194
A company runs a workload on a high performance computing (HPC) cluster on AWS. The workload is Linux-based and uses three Amazon EC2 instances. Each EC2 instance has a 10 TiB Throughput Optimized HDD (st1) Amazon EBS volume. A CloudOps engineer determines that the current storage is not meeting the workload's performance needs. The workload needs a durable file store that has throughput of 100,000 IOPS.
Which solution will meet these requirements?
- A. Create an Amazon FSx for Lustre file system. Configure an appropriate number of IOPS.
- B. Create an Amazon ElastiCache (Redis OSS) instance. Keep the append-only file (AOF) feature disabled.
- C. Create an Amazon S3 bucket in the same AWS Region where the HPC cluster is deployed. Use the same S3 bucket prefix on all objects.
- D. Create an Amazon S3 bucket in the same AWS Region where the HPC cluster is deployed. Enable S3 Transfer Acceleration.
Answer: A
Explanation:
Amazon FSx for Lustre is designed for high-performance computing workloads that need a shared, durable, high-throughput file system. It supports Linux clients and is purpose-built for workloads such as machine learning, analytics, media processing, and HPC. The current use of separate st1 EBS volumes is not meeting performance needs and also does not provide a shared high-performance file system across the cluster.
ElastiCache is an in-memory cache, not a durable POSIX-style HPC file store. Amazon S3 is durable object storage, but it is not a high-performance shared file system for Linux HPC applications that expect file-system semantics. S3 Transfer Acceleration improves long-distance data transfer to S3 but does not solve local HPC file I/O. Therefore, FSx for Lustre is the correct performance optimization choice.
NEW QUESTION # 195
A company runs thousands of Amazon EC2 instances that are based on the Amazon Linux 2 Amazon Machine Image (AMI). A SysOps administrator must implement a solution to record commands and output from any user that needs an interactive session on one of the EC2 instances. The solution must log the data to a durable storage location. The solution also must provide automated notifications and alarms that are based on the log data.
Which solution will meet these requirements with the MOST operational efficiency?
- A. Require all users to use a central bastion host when they need command line access to an EC2 instance.
Configure the unified Amazon CloudWatch agent on the bastion host to send session logs to Amazon CloudWatch Logs. Set up a metric filter and a metric alarm for relevant security findings in CloudWatch Logs. - B. Require all users to use AWS Systems Manager Session Manager when they need command line access to an EC2 instance. Configure Session Manager to stream session logs to Amazon CloudWatch Logs.
Set up a metric filter and a metric alarm for relevant security findings in CloudWatch Logs. - C. Configure command session logging on each EC2 instance. Require all users to use AWS Systems Manager Run Command documents when they need command line access to an EC2 instance.
Configure the unified Amazon CloudWatch agent to send session logs to Amazon CloudWatch Logs.Set up CloudWatch alarms that are based on Amazon Athena query results. - D. Configure command session logging on each EC2 instance. Configure the unified Amazon CloudWatch agent to send session logs to Amazon CloudWatch Logs. Set up query filters and alerts by using Amazon Athena.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:
The most operationally efficient solution is C because AWS Systems Manager Session Manager is purpose- built for secure, auditable interactive access to EC2 instances at scale-without managing bastion hosts or distributing SSH keys. Session Manager can be configured to log session activity, including commands and output, to durable destinations such as Amazon CloudWatch Logs (and optionally Amazon S3). This directly satisfies the requirement to record interactive sessions and store logs durably.
For automated notifications and alarms, CloudWatch Logs supports metric filters that transform matching log patterns into CloudWatch metrics. Those metrics can then drive CloudWatch alarms and notifications (for example, via Amazon SNS). This is a standard CloudOps pattern: centralize logs, derive metrics from security-relevant patterns, and alert automatically.
Option A and D require installing and operating agents and building a more complex analytics path (Athena queries for alerting), which is less efficient and introduces more moving parts across thousands of instances.
Option B adds a bastion host dependency that becomes an operational burden (scaling, patching, hardening, HA) and a potential choke point. Session Manager reduces these burdens by using SSM Agent already installed, IAM-based access control, and centralized logging/monitoring integrations.
References:
AWS Systems Manager User Guide - Session Manager and session logging to CloudWatch Logs/S3 Amazon CloudWatch Logs User Guide - Metric filters and alarms from log patterns AWS SysOps Administrator Study Guide - Centralized logging, auditing, and operational monitoring
NEW QUESTION # 196
A company runs an application that logs user data to an Amazon CloudWatch Logs log group. The company discovers that personal information the application has logged is visible in plain text in the CloudWatch logs.
The company needs a solution to redact personal information in the logs by default. Unredacted information must be available only to the company ' s security team. Which solution will meet these requirements?
- A. Create an OpenSearch domain. Create an AWS Glue workflow that runs a Detect PII transform job and streams the output to the OpenSearch domain. Configure the CloudWatch log group to stream the logs to AWS Glue. Modify the OpenSearch domain access policy to allow only the security team to access the domain.
- B. Create a customer managed AWS KMS key. Configure the KMS key policy to allow only the security team to perform decrypt operations. Associate the KMS key with the application log group.
- C. Create an Amazon S3 bucket. Create an export task from appropriate log groups in CloudWatch. Export the logs to the S3 bucket. Configure an Amazon Macie scan to discover personal data in the S3 bucket.
Invoke an AWS Lambda function to move identified personal data to a second S3 bucket. Update the S3 bucket policies to grant only the security team access to both buckets. - D. Create an Amazon CloudWatch data protection policy for the application log group. Configure data identifiers for the types of personal information that the application logs. Ensure that the security team has permission to call the unmask API operation on the application log group.
Answer: D
Explanation:
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 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)
NEW QUESTION # 197
A company has a stateful web application that is hosted on Amazon EC2 instances in an Auto Scaling group.
The instances run behind an Application Load Balancer (ALB) that has a single target group. The ALB is configured as the origin in an Amazon CloudFront distribution. Users are reporting random logouts from the web application.
Which combination of actions should a CloudOps engineer take to resolve this problem? (Select TWO.)
- A. Configure cookie forwarding in the CloudFront distribution cache behavior.
- B. Change to the least outstanding requests algorithm on the ALB target group.
- C. Enable group-level stickiness on the ALB listener rule.
- D. Configure header forwarding in the CloudFront distribution cache behavior.
- E. Enable sticky sessions on the ALB target group.
Answer: A,E
Explanation:
Stateful applications require session persistence to ensure that subsequent requests from the same user are routed to the same backend instance. When CloudFront is used in front of an ALB, session-related cookies must be forwarded correctly; otherwise, CloudFront can route requests to different targets, causing session loss and random logouts.
Configuring cookie forwarding in the CloudFront cache behavior ensures that session cookies (such as authentication tokens) are forwarded to the ALB and not stripped or cached incorrectly. Without this configuration, CloudFront may serve cached responses that do not align with the user's active session state, leading to authentication issues.
On the ALB side, sticky sessions (session affinity) must be enabled on the target group to ensure that requests with the same session cookie are consistently routed to the same EC2 instance. ALB stickiness uses application cookies to bind a user session to a specific target, which is critical for stateful applications that store session data in memory.
Option A affects load distribution efficiency but does not address session persistence. Option C (header forwarding) is unnecessary unless the application explicitly stores session state in headers, which is uncommon. Option D applies only when using multiple target groups and listener rules, which is not the case here.
Together, enabling cookie forwarding in CloudFront and sticky sessions at the ALB target group resolves the logout issue by maintaining consistent session routing from the user through CloudFront to the same backend instance.
NEW QUESTION # 198
A company asks a SysOps administrator to provision an additional environment for an application in four additional AWS Regions. The application is running on more than 100 Amazon EC2 instances in the us-east-
1 Region, using fully configured Amazon Machine Images (AMIs). The company has an AWS CloudFormation template to deploy resources in us-east-1.
What should the SysOps administrator do to provision the application in the MOST operationally efficient manner?
- A. Create a snapshot of the running instance. Copy the snapshot to the other Regions. Create an AMI from the snapshots. Update the CloudFormation template for each Region to use the new AMI.
- B. Update the CloudFormation template to include the additional Regions in the Auto Scaling group.Update the existing stack in us-east-1.
- C. Copy the AMI to each Region by using the aws ec2 copy-image command. Update the CloudFormation template to include mappings for the copied AMIs.
- D. Run the existing CloudFormation template in each additional Region based on the success of the template that is used currently in us-east-1.
Answer: C
NEW QUESTION # 199
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