This solution establishes a centrally managed, shared network environment. The first step is creating a dual-stack VPC with both IPv4 and IPv6 CIDR blocks and correctly sized subnets (A). Next, to allow other teams in the workload account to use this network, the subnets must be shared using AWS Resource Access Manager (RAM) within the AWS Organization (C). Finally, to provide comprehensive dual-stack internet connectivity, an Internet Gateway (for bidirectional traffic), NAT Gateways (for IPv4 outbound), and an Egress-Only Internet Gateway (for IPv6 outbound) are required, along with the necessary route table updates (E). This combination meets all specified requirements for central management, resource sharing, and dual-stack connectivity.

B. While using an Amazon-provided IPv6 CIDR is valid, option A describes an equally valid and specific configuration that forms a complete solution when combined with C and E.

D. AWS VPC sharing is accomplished by sharing subnets via AWS RAM, not by sharing the VPC object itself. Accounts need access to subnets to launch resources.

F. This option is outdated and incomplete. It proposes NAT instances instead of managed NAT Gateways and omits the essential Egress-Only Internet Gateway required for IPv6 outbound traffic.

1. VPC and Subnet Sizing: AWS Documentation, "VPC and subnet sizing for IPv6". This guide confirms that /56 is the standard IPv6 CIDR block size for a VPC and /64 is the fixed size for subnets.

Source: AWS Documentation > Amazon VPC > User Guide > IP addressing for your VPCs and subnets > VPC and subnet sizing for IPv6.

2. VPC Sharing with AWS RAM: AWS Documentation, "Share your VPC with other accounts". This document explicitly states, "To share your VPC, you share one or more subnets with other AWS accounts... You cannot share a VPC in its entirety." This supports option C and invalidates option D.

Source: AWS Documentation > Amazon VPC > User Guide > Build a VPC > Share your VPC with other accounts.

3. Dual-Stack Internet Connectivity: AWS Documentation, "Networking in your dual-stack VPC". This page details the required components for internet access: an Internet Gateway for public subnets, NAT Gateways for IPv4 outbound from private subnets, and an Egress-Only Internet Gateway for IPv6 outbound from private subnets. This supports option E.

Source: AWS Documentation > Amazon VPC > User Guide > IP addressing for your VPCs and subnets > Dual-stack VPCs > Networking in your dual-stack VPC.

4. NAT Gateways vs. NAT Instances: AWS Documentation, "Compare NAT gateways and NAT instances". This document recommends using NAT gateways over NAT instances for better availability, higher bandwidth, and reduced administrative effort, making option E superior to F.

Source: AWS Documentation > Amazon VPC > User Guide > NAT > Compare NAT gateways and NAT instances.

The core requirements are end-to-end encryption terminated on the Amazon EC2 instances and session affinity. A Network Load Balancer (NLB) operating at the transport layer (Layer 4) is required to meet these needs. By configuring a TCP listener on port 443, the NLB passes the encrypted traffic directly to the target EC2 instances without decrypting it. This allows the TLS session to be terminated on the EC2 instances themselves, fulfilling the end-to-end encryption requirement using the application's certificate. The NLB's session affinity (sticky sessions) feature ensures that subsequent requests from the same client are routed to the same EC2 instance, satisfying the session persistence requirement.

B. An Application Load Balancer (ALB) with an HTTPS listener terminates the TLS connection at the load balancer, not the EC2 instance. Forwarding traffic via HTTP to the targets breaks the end-to-end encryption requirement.

C. A Network Load Balancer with a TLS listener terminates the TLS connection at the load balancer. This contradicts the requirement for the connection to be encrypted all the way to the application on the EC2 instance.

D. This configuration is invalid. An Application Load Balancer cannot have an HTTP listener on port 443. An HTTPS listener is required for encrypted traffic, which would terminate TLS at the load balancer, failing the end-to-end encryption requirement.

1. AWS Documentation, Elastic Load Balancing User Guide for Network Load Balancers: "Listeners for your Network Load Balancer". It states, "If you configure a TCP listener on port 443, the load balancer passes the request to the targets without decryption. The targets are responsible for decrypting the traffic." This directly supports the pass-through mechanism described in option A for end-to-end encryption.

2. AWS Documentation, Elastic Load Balancing User Guide for Network Load Balancers: "Sticky sessions for your Network Load Balancer". The documentation confirms, "By default, a Network Load Balancer routes each request independently to a registered target... If you enable sticky sessions, the requests from a client are sent to the same target." This supports the session affinity requirement.

3. AWS Documentation, Elastic Load Balancing User Guide for Application Load Balancers: "Listeners for your Application Load Balancers". It details that for an HTTPS listener, "Elastic Load Balancing uses a server certificate to terminate the front-end connection and then to decrypt requests from clients before sending them to the targets." This confirms that ALBs (Options B and D) terminate encryption, violating the requirement.

4. AWS Documentation, Elastic Load Balancing User Guide for Network Load Balancers: "TLS listeners for your Network Load Balancer". It specifies, "To use a TLS listener, you must deploy a server certificate on your load balancer. The load balancer uses this certificate to terminate the connection and decrypt requests from clients before sending them to targets." This confirms that an NLB with a TLS listener (Option C) also terminates encryption.

Amazon Transit Gateway Network Manager provides centralized monitoring and visibility for a global network, including hybrid connectivity over AWS Direct Connect. It generates events for network changes, including BGP routing updates. When a new route is advertised from on-premises, Network Manager emits an event to Amazon EventBridge. An EventBridge rule can be configured to match this specific event and trigger a target, such as an Amazon SNS topic, to send a notification. This creates an efficient, event-driven architecture that directly addresses the requirement for real-time notifications on route changes.

A. Amazon CloudWatch metrics for Direct Connect track connection health, data throughput, and BGP session state, but not the advertisement of individual routes.

C. A Lambda function would have to periodically poll the route tables and compare states. This is an inefficient, complex, and non-real-time polling approach.

D. There is no native feature to enable Amazon CloudWatch Logs on a Direct Connect transit VIF to capture BGP route advertisements.

1. AWS Transit Gateway User Guide, Network Manager, Monitoring your global network with Events: "Network Manager generates events for changes to the network topology, routing, and connection status. Events are delivered to Amazon EventBridge (formerly Amazon CloudWatch Events)... For example, you can create an event to be notified when a BGP route is learned or no longer advertised from a specific BGP peer."

2. Amazon EventBridge User Guide, Events from AWS services, Network Manager events: This section details the event patterns generated by Network Manager that can be used to trigger rules in EventBridge. The aws.networkmanager source provides events for routing updates.

3. AWS Direct Connect User Guide, Monitoring, Monitoring with Amazon CloudWatch: This page lists the available metrics for Direct Connect connections and virtual interfaces. The list includes metrics like ConnectionState and BGPPeeringState but lacks any metric for tracking the number or content of advertised routes.

An AWS Site-to-Site VPN connection is configured to carry either IPv4 or IPv6 traffic inside the tunnel, but not both simultaneously. This is determined by the InsideIpVersion parameter, which is immutable after the VPN connection is created. To support the new IPv6 workloads while maintaining the existing IPv4 connectivity, a new, separate Site-to-Site VPN connection must be created specifically for IPv6 traffic. This new connection will have its InsideIpVersion parameter set to ipv6. This is the standard AWS-managed approach and represents the least operational overhead compared to building and maintaining a custom solution.

B. A self-managed EC2 instance for VPN introduces significant operational overhead for patching, high availability, and management, which contradicts the requirement for the least overhead.

C. The traffic version (IPv4 or IPv6) inside a VPN tunnel is an immutable property. An existing Site-to-Site VPN connection cannot be updated to change this setting.

D. The customer gateway's public IP address is for the tunnel's outer encapsulation. Changing it does not affect the type of traffic (IPv4 vs. IPv6) allowed inside the tunnel.

1. AWS Site-to-Site VPN User Guide: In the section "IPv6 traffic over a Site-to-Site VPN connection," the documentation states, "A single Site-to-Site VPN connection tunnel supports either IPv4 or IPv6 traffic, but not both at the same time. To support both IPv4 and IPv6 traffic, create a Site-to-Site VPN connection for IPv4 traffic, and a separate Site-to-Site VPN connection for IPv6 traffic."

2. Amazon EC2 API Reference, CreateVpnConnection: The documentation for this API call specifies the VpnTunnelOptions parameter, which includes InsideIpVersion. This parameter must be set to ipv4 or ipv6 at the time of creation.

3. Amazon EC2 API Reference, ModifyVpnConnection: The documentation for modifying a VPN connection does not list InsideIpVersion or its parent VpnTunnelOptions as a modifiable parameter, confirming its immutability after creation.

The requirement is that all traffic "must be encrypted at all times." This mandates a configuration that strictly enforces encryption and prevents unencrypted traffic flow. MACsec is a point-to-point Layer 2 encryption protocol, requiring configuration on both the on-premises device and the AWS Direct Connect endpoint.

First, the same MACsec secret key (CKN/CAK pair) must be configured on the company's on-premises router to match the key generated in AWS (Option A).

Second, on the AWS side, the CKN/CAK pair must be associated with the Direct Connect connection. To meet the strict encryption requirement, the MACsec mode must be set to mustencrypt. This mode ensures that the connection will be down if a secure MACsec session is not established, thereby preventing any unencrypted traffic. The logical operational sequence is to associate the key first and then update the encryption mode (Option D).

B: While the actions are correct, the order is less logical. Associating the key before enforcing a strict encryption mode is the standard procedure to prevent configuration-related link failures.

C: The shouldencrypt mode is incorrect because it allows unencrypted traffic if MACsec negotiation fails, which violates the requirement that traffic "must be encrypted at all times."

E: The shouldencrypt mode does not meet the strict requirement for mandatory encryption, as it permits the connection to pass unencrypted traffic if a secure session is not established.

1. AWS Direct Connect User Guide, "MACsec" section: This document outlines the configuration steps and encryption modes. It states, "To enable MACsec, you must do the following: ... 2. Associate the MACsec secret key with a connection. 3. Configure your on-premises device." This supports the actions in options A and D.

2. AWS Direct Connect User Guide, "MACsec" section, under "Encryption modes": The guide defines the modes: "mustencrypt – The connection is down if the MACsec session is not established. shouldencrypt – The connection is up even if the MACsec session is not established. Traffic will flow unencrypted." This confirms that mustencrypt is the only mode that satisfies the question's strict requirement.

3. AWS CLI Command Reference, directconnect, update-connection: The documentation for the update-connection command shows that encryptionMode is a parameter that can be set to mustencrypt or shouldencrypt. This is a separate action from associating the key using the associate-mac-sec-key command, supporting the sequence described in option D.

The requirement is to perform content inspection on all network traffic from a fleet of EC2 instances. This necessitates capturing the actual packet data, not just metadata. VPC Traffic Mirroring is the AWS feature designed for this purpose. It copies network traffic from a source (the EC2 instances' network interfaces) and sends it to a target for analysis. A Network Load Balancer (NLB) is a valid and scalable target for a mirror session, allowing traffic to be distributed to a fleet of inspection appliances. This setup directly meets the requirement for centralized content inspection.

A. VPC Flow Logs capture metadata about IP traffic (e.g., source/destination IPs, ports, packet count), not the actual packet content, making them unsuitable for content inspection.

C. Amazon Data Firehose is not a valid target for a VPC Traffic Mirroring session. The supported targets are a network interface or a Network Load Balancer.

D. This option also relies on VPC Flow Logs, which, as stated for option A, do not contain the packet payload required for content inspection.

1. AWS Documentation, VPC User Guide, "Traffic mirroring": "Traffic mirroring is an Amazon VPC feature that you can use to copy network traffic from an elastic network interface of an Amazon EC2 instance. You can then send the traffic to out-of-band security and monitoring appliances for deep packet inspection, content inspection, threat monitoring, and troubleshooting."

2. AWS Documentation, VPC User Guide, "Traffic mirroring targets": This section explicitly lists the valid targets for mirrored traffic. It states, "You can send the mirrored traffic to the following targets: A network interface [or] A Network Load Balancer that has a UDP listener." This confirms that an NLB is a supported target.

3. AWS Documentation, VPC User Guide, "VPC Flow Logs": "Flow logs is a feature that enables you to capture information about the IP traffic going to and from network interfaces in your VPC... Flow log data does not capture the contents of the traffic." This confirms that flow logs are insufficient for content inspection.

Bidirectional Forwarding Detection (BFD) is a network protocol designed for rapid detection of path failures. When used with BGP over a Direct Connect connection, BFD can detect a failure in the path in under a second, compared to the default BGP hold-down timer which can take 90 seconds or more. This allows for near-instantaneous failover to the secondary connection. According to AWS documentation, asynchronous BFD is automatically enabled on the AWS side of a Direct Connect virtual interface when it is configured on the customer's on-premises router. Therefore, configuring BFD on the on-premises router is the direct action that implements this high-speed failover mechanism, providing the largest reduction in failover time.

A. Reducing the BGP hold-down timer improves failover time but is still measured in multiple seconds and is significantly slower than BFD's sub-second detection.

B. A CloudWatch alarm and Lambda function approach is reactive and introduces significant latency from detection, alarm state change, and function invocation, resulting in a failover time of minutes.

C. While BFD must be active on the AWS side, this is enabled automatically in response to the on-premises router configuration. Therefore, this option is less precise than D.

1. AWS Direct Connect User Guide, "Bidirectional Forwarding Detection (BFD)" section: "BFD liveness detection provides a faster detection of path failures than BGP timers... Asynchronous BFD is automatically enabled for Direct Connect virtual interfaces on the AWS side when you enable it on your router." This confirms that BFD is the fastest method and the primary configuration step is on the on-premises equipment.

2. AWS Direct Connect User Guide, "Bidirectional Forwarding Detection (BFD)" section: "We recommend that you configure the BFD liveness detection minimum interval to 300, and the BFD liveness detection multiplier to 3." This configuration results in a detection time of less than one second (300ms 3 = 900ms), a significant reduction from the default BGP hold timer of 90 seconds.

3. AWS Blog, "AWS Direct Connect introduces Bidirectional Forwarding Detection (BFD) for faster failover" (Nov 19, 2019): "With BFD, path failure detection time can be reduced to less than a second, compared to the default BGP convergence time of three minutes, or 180 seconds." This highlights the magnitude of the failover time reduction provided by BFD.

The primary requirement is to find the lowest-cost solution for high-volume data transfer between VPCs. VPC Peering offers the most cost-effective data transfer rates. Data transferred over a VPC peering connection within the same Availability Zone (AZ) is free. By using the zonal DNS names of the Network Load Balancers (NLBs) in the services VPCs, the front-end application can explicitly send traffic to the NLB node located in the same AZ as the source pod. This strategy eliminates cross-AZ data transfer charges, which would be substantial given the 10 TB of monthly traffic. This makes VPC Peering the most economical choice compared to AWS Transit Gateway or AWS PrivateLink, both of which incur mandatory data processing fees regardless of the AZ.

A. A transit gateway incurs a data processing fee of $0.02 per GB, which is double the cost of cross-AZ VPC peering and significantly more expensive than same-AZ peering (which is free).

B. AWS PrivateLink has hourly costs for each VPC endpoint in each AZ, in addition to a data processing fee of $0.01 per GB. This makes it more expensive than the free same-AZ VPC peering option.

D. A transit gateway is inherently more expensive for data processing. Using Regional DNS names would distribute traffic across all AZs, guaranteeing cross-AZ data transfer costs, which contradicts the goal of minimizing cost.

1. Amazon EC2 On-Demand Pricing - Data Transfer: Under the "Data Transfer" section, it specifies the costs for data transfer via "Amazon VPC Peering". It explicitly states that for traffic within the same AWS Region, data transfer within the "Same Availability Zone" is "$0.00 per GB". Data transfer to a "Different Availability Zone" is "$0.01 per GB". This confirms that keeping traffic in the same AZ via peering is free. (Source: Official AWS EC2 Pricing Documentation).

2. AWS Transit Gateway Pricing: This page details that Transit Gateway has a "$0.02 per GB of data processed" fee, in addition to hourly attachment costs. This is demonstrably more expensive than the VPC peering model for this use case. (Source: Official AWS Transit Gateway Pricing Documentation).

3. AWS PrivateLink Pricing: This page shows that PrivateLink has a "$0.01 per GB for data processed" fee and an hourly charge for each VPC Endpoint. The combination of these costs makes it more expensive than same-AZ VPC peering. (Source: Official AWS PrivateLink Pricing Documentation).

4. Elastic Load Balancing User Guide - Load balancer DNS names: The documentation for Network Load Balancers states: "For each Availability Zone that you enable for your load balancer, the load balancer node in that zone uses a zonal DNS name... If you need to target a load balancer node in a specific zone, you can use its zonal DNS name." This confirms the technical validity of the strategy proposed in the correct answer. (Source: AWS Elastic Load Balancing User Guide, section on DNS names).

This solution requires two components: a deployment mechanism and an application design pattern.

Option C, using a CDK pipeline, provides the ideal deployment mechanism. CDK Pipelines (built on AWS CodePipeline) are purpose-built to automate deployments across multiple stages, which can be configured for different AWS accounts and Regions. This creates a consistent, repeatable process with the least manual effort, as deployments are triggered automatically from a source code repository.

Option B provides the best application design pattern. To be reusable, the CDK code should not contain hardcoded resource IDs. By using context methods like Vpc.fromLookup(), the CDK application can dynamically discover the IDs of existing resources (like VPCs and hosted zones) in the target account and Region during the synthesis stage. This makes the stack portable across any environment.

A. Using CloudFormation parameters is less dynamic than CDK context lookups for discovering existing resources and often requires more manual configuration per deployment.

D. A custom script is a less robust, less secure, and less manageable solution than a native, fully managed CDK Pipeline for CI/CD.

E. This describes a manual deployment process. Running cdk deploy with flags locally for each environment directly contradicts the requirement for automation and least manual effort.

1. AWS CDK Developer Guide, "CDK Pipelines: Continuous delivery for AWS CDK applications": This guide explains that CDK Pipelines are the recommended way to set up a robust, multi-account, multi-Region continuous deployment pipeline for CDK applications, which minimizes manual deployment steps. (Supports Option C).

2. AWS CDK Developer Guide, "Runtime context": This section details context providers. It states, "The AWS CDK can retrieve context from the AWS environment during synthesis." This includes looking up existing VPCs, Availability Zones, and Route 53 Hosted Zones, which is the mechanism described in Option B.

3. AWS CDK API Reference, awsec2.Vpc.fromLookup() method: The documentation for this static method explicitly states it is used to "Import a VPC from another stack or from the same stack by looking it up in the target account." This directly supports the lookup approach in Option B for using pre-existing network components.

4. AWS CDK Developer Guide, "Environments": This document clarifies that a CDK stack is deployed to a specific environment (account and Region). It explains how the CDK determines this context at runtime, which is essential for the context lookups in Option B to function correctly within the pipeline stages from Option C.

The requirement is to analyze logs from AWS WAF using Amazon Athena. To do this, the WAF logs must be stored in an Amazon S3 bucket, as Athena queries data directly in S3. The standard and recommended method for exporting AWS WAF logs is to configure the web ACL to send log data to an Amazon Kinesis Data Firehose delivery stream. This delivery stream can then be configured to deliver the logs to an S3 bucket in a format suitable for analysis. Once the logs are in S3, an Athena table can be created to query and analyze the WAF-detected attack patterns.

A. VPC flow logs capture IP traffic information for network interfaces. They do not contain the application-layer details of AWS WAF rule evaluations or actions, which are necessary to analyze attacks.

B. AWS CloudTrail logs API activity within your AWS account. It records actions like creating or modifying a web ACL, but not the web requests that the WAF inspects.

D. Application Load Balancer (ALB) access logs record details about requests sent to the ALB. However, in this architecture, WAF is associated with CloudFront, so it will block malicious requests at the edge before they even reach the ALB. Furthermore, ALB logs do not contain WAF-specific fields like ruleGroupId or action.

1. AWS WAF Developer Guide, Logging and monitoring web ACL traffic: "To enable logging, you configure your web ACL to send the logs to an Amazon Kinesis Data Firehose data stream... Kinesis Data Firehose can deliver your web ACL traffic logs to a number of destinations. This guide provides instructions for Amazon S3." This document outlines the exact process described in the correct answer.

2. AWS Documentation, Amazon Athena User Guide, Querying AWS WAF logs: "AWS WAF is a web application firewall that lets you monitor HTTP and HTTPS requests that are forwarded to an Amazon API Gateway API, Amazon CloudFront, or an Application Load Balancer. You can use Athena to query AWS WAF logs." The guide presupposes that logging has been configured to deliver logs to S3, typically via Kinesis Data Firehose.

3. AWS Security Blog, "How to analyze AWS WAF logs using Amazon Athena and Amazon QuickSight": This official blog post details the architecture for analysis: "This post shows you how to set up an analysis solution for AWS WAF logs. The solution uses Amazon Kinesis Data Firehose to deliver logs to Amazon Simple Storage Service (Amazon S3). From there, you can use Amazon Athena to query the logs..." This directly supports option C as the correct solution.