CCNA Design High Performing Architectures Questions

EC2 Instance Store provides high-performance, local block-level storage that is physically attached to the host computer. This makes it ideal for temporary storage of information that changes frequently, such as buffers, caches, and scratch space. Architects must account for its ephemeral nature while leveraging its superior I/O capabilities for high-performance workloads.

Amazon FSx for Lustre is a fully managed, high-performance file system optimized for compute-intensive workloads like HPC, machine learning, and media processing. It provides sub-millisecond latencies, millions of IOPS, and hundreds of gigabytes per second of throughput, making it ideal for Linux-based HPC clusters that require a shared, POSIX-compliant file system. Unlike general-purpose file systems, Lustre is designed for parallel access from many compute nodes simultaneously, which is essential for HPC applications.

The policy shown is a VPC endpoint policy (or an S3 bucket policy restricting access to a VPC endpoint), which forces traffic between EC2 and S3 to traverse the AWS private backbone via a Gateway or Interface VPC Endpoint instead of the public internet. This keeps traffic on the private AWS network, reducing latency, avoiding NAT gateway data-processing charges, and improving security posture.

Spot Instances provide up to a 90% discount over On-Demand pricing. Since the transcoding workload is fault-tolerant and capable of resuming work, it is a perfect candidate for Spot Instances. By using an Auto Scaling group with a mix of Spot and On-Demand instances, the application can achieve high performance at a fraction of the cost, utilizing cheaper capacity while maintaining a safety net of On-Demand instances.

Amazon ElastiCache for Redis is purpose-built for sub-millisecond, in-memory session storage, so any EC2 instance behind an Auto Scaling group or load balancer can read/write the same session state without shared-disk contention. This decouples session state from individual compute nodes, allowing horizontal scaling and eliminating the need for sticky routing. Redis also supports TTL-based expiration and optional replication/Multi-AZ for durability.

DynamoDB Accelerator (DAX) is an in-memory cache purpose-built for DynamoDB that delivers microsecond response times for eventually consistent reads — well within the sub-millisecond requirement. DAX sits in front of the table as a write-through cache, so frequently accessed keys are served from RAM rather than from DynamoDB's SSD-backed storage, eliminating the 10-15 ms round trip. It requires only a minor application change (swap the DynamoDB client for the DAX client) and is the standard AWS answer for 'sub-millisecond DynamoDB reads.'

Amazon CloudFront is a global content delivery network (CDN) that caches static content at edge locations worldwide, dramatically reducing latency for geographically distributed users. It integrates natively with S3 origins and supports cache behaviors, signed URLs, and Lambda@Edge for dynamic customization. This makes it the purpose-built service for low-latency global static content delivery.

Creating an Amazon S3 VPC Endpoint (Gateway Endpoint) allows resources within an Amazon VPC (such as an EC2 instance) to communicate with Amazon S3 without requiring an internet gateway, NAT device, or VPN connection. Traffic between the VPC and S3 leaves the instances and goes directly to S3 via the AWS network backbone, significantly improving retrieval performance, reducing latency, and avoiding public internet bottlenecks. CloudFront is intended for global end-user content delivery rather than optimizing backend EC2-to-S3 communication.

Provisioned IOPS SSD (io1/io2) volumes are designed for I/O-intensive workloads and allow you to specify a consistent IOPS rate. They provide significantly higher IOPS than gp2 volumes and are the best choice for applications with high IOPS demand. This directly addresses the performance issue.

In a CloudFront cache policy, QueryStringBehavior set to 'all' (or forwarding all query strings) causes CloudFront to treat every unique query string combination as a separate cache object, drastically reducing the cache hit ratio. Changing it to 'whitelist' (forwarding only the query strings the origin actually needs) or 'none' (ignoring query strings entirely) collapses many variants into a single cached object, which increases the cache hit ratio and reduces origin load. This is the most direct fix for the described symptom.

Provisioned Concurrency is the recommended solution for reducing cold start latency in AWS Lambda. It keeps a specified number of execution environments initialized and ready to respond immediately to incoming requests. This is critical for high-performance applications where unpredictable spikes in traffic could otherwise lead to unacceptable delays.

Amazon Athena is a serverless, interactive query service that makes it easy to analyze data in S3 using standard SQL. For large analytical workloads, Amazon Redshift Spectrum allows you to query data directly from S3, providing even higher performance for petabyte-scale data by leveraging the Redshift massively parallel processing engine, which is optimized for complex join and aggregation operations across massive datasets.

To achieve maximum throughput, the application should use an S3 VPC Endpoint. This ensures that traffic between the EC2 instance and S3 stays within the AWS network, bypassing the public internet and avoiding potential bandwidth bottlenecks. Using VPC Endpoints also provides secure connectivity, which is critical for high-performance data transfers, as it prevents the exposure of traffic to external network risks while maintaining consistent latency and high speed.

Static websites hosted on S3 are limited by the speed of the browser-to-bucket connection. By placing an Amazon CloudFront distribution in front of the S3 bucket, content is cached at edge locations globally. This brings the content closer to the users, reducing the distance data travels and minimizing latency, which results in faster page load times regardless of where the user is located geographically.

An Amazon S3 Gateway Endpoint allows EC2 instances in a VPC to access S3 without traversing the public internet or a NAT gateway. Traffic stays within the AWS network, which can reduce latency and improve throughput, resolving the network bottleneck. It also eliminates data transfer costs associated with NAT gateways.

The symptoms — high latency, 503 errors, low database CPU — point to connection exhaustion rather than compute saturation. Each application instance opening its own database connections can exhaust the RDS max_connections limit, causing new connections to be refused and 503s to surface at the web tier. Amazon RDS Proxy pools and multiplexes connections, allowing many application connections to share a smaller set of database connections, which resolves the bottleneck without scaling the database.

Amazon RDS Proxy sits between the application and the database, pooling and reusing persistent connections so that many application connections map to a small number of database connections. This directly addresses the legacy driver's persistent-connection behavior that is exhausting the database's connection limit, without requiring application changes.

Target tracking scaling policies automatically adjust the number of EC2 instances based on a specified metric (e.g., average CPU utilization or request count per target), maintaining performance during spikes while scaling in during low demand to optimize cost. This is the most efficient and responsive approach for variable workloads behind an ALB.

Creating an RDS Read Replica allows the application to offload read-only traffic from the primary database instance. By routing read queries to the replica, the primary instance can focus solely on write operations. This architecture is a standard practice for scaling read-heavy workloads in relational databases, ensuring lower latency and better resource utilization without requiring significant code modifications or complex database sharding.

Cross-region read replicas allow you to serve read traffic from a location physically closer to your users, reducing latency. This architectural pattern is essential for high-performing global applications where the primary database is located in a single region but the user base is distributed worldwide.

Elastic Fabric Adapter (EFA) is a network interface for Amazon EC2 instances that enables customers to run applications requiring high levels of inter-node communications at scale. It uses a custom protocol to provide lower and more consistent latency than traditional TCP/IP stacks used in standard networking.

Aurora Auto Scaling automatically adds and removes Aurora Replicas based on metrics like CPU utilization or the number of connections, scaling read capacity in response to demand spikes without manual intervention. This is the most effective solution because it handles peak-hour surges dynamically while maintaining high availability across Availability Zones. Manual scaling (Option A) is reactive and slow, and vertical scaling of the primary (Option C) does not address read traffic distribution.

C-family instances are compute-optimized, delivering the highest CPU performance per dollar for compute-intensive workloads, which matches the application's requirement. Pairing them with a dynamic scaling policy (target tracking or step scaling) lets the Auto Scaling group respond automatically to real-time demand changes. Together they satisfy both the performance and elasticity requirements.

The bucket policy shown in the exhibit restricts access to requests originating from a specific VPC Endpoint (aws:sourceVpce condition). If the EC2 instances are not routing S3 traffic through that endpoint — for example, they are using the public S3 endpoint or a different endpoint — the policy denies the request and S3 returns 403 Forbidden even though the IAM role has s3:GetObject. The fix is to ensure the instances use the specified VPC Endpoint (via route table entries or endpoint policies).

Aurora Global Database is purpose-built for this exact scenario: it replicates data from a primary Aurora cluster to secondary clusters in other regions with typical latency under one second, and the secondary clusters serve low-latency local reads. Because writes are infrequent and can tolerate propagation delay, the asynchronous replication model is acceptable, and each region's application can read from its local secondary cluster endpoint. This delivers the lowest read latency across North America, Europe, and Asia while keeping the source of truth in a single primary region.

S3 automatically partitions request load by prefix, and a single prefix concentrates all GET requests on one partition, creating a hotspot. Introducing random or hashed prefixes (e.g., a hash of the object key as the first characters) spreads requests across many partitions, allowing S3 to scale request throughput and reduce latency during peak hours. This is the standard fix for high-request-rate workloads on small objects.

AWS Global Accelerator uses the AWS global network to improve the availability and performance of applications. It provides static IP addresses that act as a fixed entry point and can route traffic to endpoints in multiple regions using any TCP or UDP protocol, ensuring optimal performance.