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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitoring, Logging, and Remediation | 20% | - Centralized logging and log analysis with AWS services - Metrics and monitoring using Amazon CloudWatch - Automated remediation and operational workflows |
| Topic 2: Cost and Performance Optimization | 28% | - Cost monitoring and optimization strategies - Resource performance tuning - Right-sizing and capacity planning |
| Topic 3: Reliability and Business Continuity | 16% | - Data replication and recovery mechanisms - Backup and disaster recovery strategies - High availability and fault tolerance design |
| Topic 4: Deployment, Provisioning, and Automation | 18% | - Automated deployment pipelines - Infrastructure as Code using AWS CloudFormation - Configuration management and orchestration tools |
| Topic 5: Security and Compliance | 18% | - Security monitoring and auditing - Data protection and encryption - Identity and access management (IAM) |
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NEW QUESTION # 91
A company runs applications that generate log files. The company stores the log files in Amazon S3. A CloudOps engineer must automatically process the log files whenever new files upload to the S3 bucket. Which solution will meet this requirement?
Answer: A
Explanation:
Amazon S3 event notifications are the native mechanism for invoking processing when objects are uploaded to an S3 bucket. The CloudOps engineer can configure the bucket to send ObjectCreated events to an AWS Lambda function, and the Lambda function can process each new log file by using the bucket name and object key from the event payload. This is serverless, event-driven, and has the least operational overhead. CodePipeline is intended for software delivery workflows, not generic log-file processing. Step Functions is useful for orchestrating multi-step workflows, but polling or waiting for S3 uploads is unnecessary here. EventBridge can receive some S3 events, but the direct S3 event notification to Lambda is simpler and more targeted for this requirement.
NEW QUESTION # 92
A company needs to upload gigabytes of files daily to Amazon S3 and requires higher throughput and faster upload speeds.
Which action should a CloudOps engineer take?
Answer: A
Explanation:
The AWS Cloud Operations and Storage documentation confirms that S3 Transfer Acceleration is designed to increase upload speed for objects transferred to S3 buckets over long distances.
It uses AWS Global Edge Network and Amazon CloudFront edge locations to route data through optimized network paths, reducing latency and achieving higher throughput compared to standard S3 uploads.
After enabling Transfer Acceleration on the bucket, users upload files to the accelerated endpoint (e.g., bucketname.s3-accelerate.amazonaws.com). This feature requires no changes to application logic besides endpoint modification and provides immediate performance improvement.
CloudFront (Option A) is for content delivery, not uploads. ElastiCache (Option B) and Global Accelerator (Option C) are unrelated to S3 upload performance.
Thus, Option D is correct - enable S3 Transfer Acceleration for faster, optimized file uploads.
Reference: AWS Cloud Operations & Storage Guide - Enhancing Upload Speed with Amazon S3 Transfer Acceleration
NEW QUESTION # 93
A company moves workloads from public subnets to private subnets to improve security. During testing, servers in the private subnets cannot reach an external API. The VPC has a CIDR block of 10.0.0.0/16, two public subnets, two private subnets, one internet gateway, and a NAT gateway in each private subnet.
The company must ensure that workloads in the private subnets can reach the external API.
Which solution will meet this requirement?
Answer: C
Explanation:
For IPv4 traffic, private subnets require a NAT gateway in a public subnet to access the internet.
NAT gateways must be deployed in public subnets and associated with an Elastic IP address.
Private subnet route tables must direct 0.0.0.0/0 traffic to the NAT gateway.
The question states that NAT gateways are incorrectly placed in private subnets, which cannot provide internet access. Deploying NAT gateways in public subnets resolves this issue and restores outbound connectivity to external APIs.
NEW QUESTION # 94
A company is migrating a legacy application to AWS. The application runs on EC2 instances across multiple Availability Zones behind an Application Load Balancer (ALB). The target group routing algorithm is set to weighted random, and the application requires session affinity (sticky sessions).
After deployment, users report random application errors that were not present before migration, even though target health checks are passing.
Which solution will meet this requirement?
Answer: C
Explanation:
According to the AWS Cloud Operations and Elastic Load Balancing documentation, Application Load Balancer (ALB) supports multiple routing algorithms to distribute requests among targets:
* Round robin (default)
* Least outstanding requests (LOR)
* Weighted random
When applications require session affinity, AWS recommends using "least outstanding requests" as the load balancing algorithm because it reduces latency, distributes load evenly, and ensures consistent target responsiveness during high traffic.
Using weighted random routing with sticky sessions can cause sessions to be routed inconsistently if one target's capacity fluctuates, leading to session mismatches and application errors - especially when user sessions rely on instance-specific state.
Disabling cross-zone balancing (Option C) or adjusting deregistration delay (Option D) does not address routing inconsistency. Anomaly mitigation (Option B) protects against target performance degradation, not sticky-session misrouting.
Therefore, the correct solution is Option A - changing the target group's routing algorithm to least outstanding requests ensures smoother, predictable session handling and resolves random application errors.
Reference: AWS Cloud Operations & Load Balancing Guide - Optimizing Application Load Balancer Routing Algorithms for Stateful Applications
NEW QUESTION # 95
A CloudOps engineer configures an application to run on Amazon EC2 instances behind an Application Load Balancer (ALB) in a simple scaling Auto Scaling group with the default settings. The Auto Scaling group is configured to use the RequestCountPerTarget metric for scaling. The CloudOps engineer notices that the RequestCountPerTarget metric exceeded the specified limit twice in 180 seconds.
How will the number of EC2 instances in this Auto Scaling group be affected in this scenario?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Doocuments:
With simple scaling policies, an Auto Scaling group performs one scaling activity when the alarm condition is met, then observes a default cooldown period (300 seconds) before another scaling activity of the same type can begin. CloudOps guidance explains that cooldown prevents rapid successive scale-outs by allowing time for the newly launched instance(s) to register with the load balancer and impact the metric. Even if the alarm breaches multiple times during the cooldown window, the group waits until the cooldown completes before evaluating and acting again. In this case, although RequestCountPerTarget exceeded the threshold twice within 180 seconds, the group will launch a single instance and then wait for cooldown before any additional scale-out can occur. Options A, C, and D do not reflect the behavior of simple scaling with cooldowns; A describes step/target-tracking-like behavior, and C/D are not Auto Scaling mechanics.
References:* Amazon EC2 Auto Scaling - Simple Scaling Policies and Cooldown (User Guide)* Elastic Load Balancing Metrics - ALB RequestCountPerTarget (CloudWatch Metrics)* AWS Well-Architected Framework - Performance Efficiency & Operational Excellence
NEW QUESTION # 96
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