Amazon Web Services SAP-C02 Exam With Confidence Using Practice Dumps

Comprehensive and Detailed Explanation:

This question is testing the correct load balancing design for a stateful web application that:

runs on multiple EC2 instances,

must scale horizontally,

uses browser cookies for session management,

requires session affinity.

The correct solution is to place the EC2 instances in an Auto Scaling group behind an Application Load Balancer and enable sticky sessions on the target group. This allows the application to scale out across multiple instances while ensuring that repeat requests from the same client are routed to the same target for the duration of the stickiness configuration.

Why C is correct

An Application Load Balancer is designed for Layer 7 HTTP/HTTPS traffic, which is exactly what a browser-based web application uses. Because the application uses cookies and requires session affinity, ALB is the correct AWS service since it supports sticky sessions for target groups. The EC2 instances can be placed in an Auto Scaling group so the application can add or remove instances as demand changes. This directly satisfies the horizontal scaling requirement.

ALB also integrates natively with Auto Scaling groups, health checks, and target groups. For web applications that rely on session persistence, ALB stickiness is the standard design choice. The application is third-party, so changing the application to externalize sessions may not be possible. Therefore, keeping requests bound to the same backend instance is the appropriate architecture.

Why A is incorrect

Route 53 does not provide cookie-based session affinity to specific EC2 instances. Multivalue answer routing can return multiple healthy records, but it is a DNS-level mechanism, not an HTTP session persistence mechanism. Route 53 Resolver rules also do not inspect browser cookies and do not ensure that a given cookie value maps consistently to one EC2 instance.

In addition, exposing each EC2 instance with a public IP is not the right scalable architecture for a horizontally scaled web application. This option lacks proper load balancer behavior and does not provide real application-layer stickiness.

Why B is incorrect

CloudFront cannot use an Auto Scaling group directly as an origin. CloudFront origins are typically an Application Load Balancer, Network Load Balancer, S3 bucket, custom HTTP origin, or similar endpoint. An Auto Scaling group itself is not a valid origin endpoint for CloudFront.

Also, CloudFront Functions are used for lightweight request and response manipulation at the edge. They are not the correct mechanism to implement instance-level session affinity for a fleet of EC2 instances. Even if cookies are forwarded, CloudFront is not the service that should manage sticky routing among application servers. That role belongs to the load balancer.

Why D is incorrect

Gateway Load Balancer is designed for deploying, scaling, and managing third-party virtual appliances such as firewalls, IDS, and deep packet inspection systems. It is not intended to front standard web applications for browser traffic.

Flow stickiness on GWLB is not the same as HTTP cookie-based session affinity for a web application. GWLB operates for appliance insertion use cases, not for traditional user-facing web application request distribution. Therefore, it does not meet the application requirement appropriately.

The cleanest design is an AWS Config organization conformance pack deployed centrally. Conformance packs are YAML templates that can include AWS Config managed rules, custom rules, and remediation actions. AWS Config also supports managing conformance packs across all member accounts in an AWS Organizations organization, allowing centralized deployment, update, and deletion. The PutOrganizationConformancePack API deploys a conformance pack across member accounts and can create AWS Config rules and remediation actions without requiring member-account IAM permissions for those individual rule operations. Because the requirement includes four custom rules and five managed rules, the conformance pack must include all nine rules. Deploying only custom rules leaves the managed rules outside the update model. CloudFormation StackSets add unnecessary operational overhead and do not provide the same native organization conformance-pack governance.

For migration planning, AWS provides specific tooling to discover on-premises servers, collect detailed performance and configuration data, and analyze application dependencies. The primary service for this purpose is AWS Application Discovery Service, which integrates with AWS Migration Hub.

The AWS Application Discovery Agent is installed on on-premises physical servers and VMs. It collects detailed information such as CPU, memory, and disk utilization; processes and services running on the system; system configuration details; and network connections between systems. This allows the company to understand how servers communicate, what applications are running, and what dependencies exist between components.

This data is sent to AWS Application Discovery Service and surfaced through AWS Migration Hub, where the company can view discovered servers, group them logically into applications, and analyze migration readiness. Migration Hub can use this collected data to provide recommendations for EC2 instance sizing that are based on actual on-premises utilization metrics, helping choose appropriate EC2 instance types and sizes.

Option C directly describes installing the AWS Application Discovery Agent, using AWS Migration Hub to discover and group servers into applications, and using Migration Hub to generate EC2 instance recommendations. This aligns with AWS’s migration assessment tooling and meets all the stated goals: performance measurement, system configuration listing, network connection understanding, dependency analysis, and instance sizing recommendations.

Option A uses AWS Systems Manager Agent and Application Manager. While Systems Manager can manage servers and collect some information, it is not the primary tool for detailed migration discovery, networking dependency mapping, and migration-focused analysis. It also suggests using AWS Pricing Calculator for instance recommendations, which requires manual input and does not automatically derive recommendations from observed utilization and dependencies.

Option B suggests using the Amazon Inspector agent to gather performance and usage information. Amazon Inspector is designed for vulnerability and security assessments, not for detailed migration discovery or dependency mapping. Additionally, AWS Compute Optimizer currently bases its recommendations on usage metrics from AWS resources, not on-premises servers.

Option D uses the CloudWatch agent to collect metrics and then Migration Hub and Compute Optimizer. The CloudWatch agent is not the standard agent for migration discovery and dependency analysis of on-premises workloads. Also, Compute Optimizer focuses on optimization of existing AWS resources rather than creating recommendations based on on-premises utilization.

Therefore, installing the AWS Application Discovery Agent and using AWS Migration Hub (option C) is the correct solution to satisfy all the requirements for migration assessment and EC2 sizing recommendations.