A company runs its application by using Amazon EC2 instances and AWS Lambda functions. The EC2 instances run in private subnets of a VPC. The Lambda functions need direct network access to the EC2 instances for the application to work.
The application will run for 1 year. The number of Lambda functions that the application uses will increase during the 1-year period. The company must minimize costs on all application resources.
Which solution will meet these requirements?
Compute Savings Plans apply to EC2, AWS Fargate, and AWS Lambda usage, maximizing coverage for mixed architectures while retaining flexibility across instance families, regions, OS, and tenancy. For private connectivity, Lambda functions must be configured with VPC access to attach ENIs in the target subnets, enabling direct network access to EC2 in private subnets (no public subnets are required for intra-VPC communication). EC2 Instance Savings Plans only discount EC2 usage and are tied to a specific instance family in a region, reducing flexibility and leaving Lambda costs undiscounted. Keeping Lambda in the service VPC prevents direct access to private EC2 without VPC configuration. Thus, a 1-year Compute Savings Plan plus connecting Lambda to the private subnets minimizes total cost and meets connectivity needs.
References: AWS Savings Plans --- Compute Savings Plans applicability (EC2, Fargate, Lambda); AWS Lambda Developer Guide --- Configuring Lambda to access VPC resources (ENIs, subnets, security groups).
A company runs a web application on Amazon EC2 instances behind an Application Load Balancer ALB. The application uses Amazon DynamoDB as its database. The company wants to ensure high performance for reads and writes.
Which solution will meet this requirement MOST cost-effectively?
The most cost-effective general solution isDynamoDB auto scaling. AWS recommends atarget utilization of 70%for provisioned throughput with auto scaling, which lets DynamoDB adjust capacity up or down based on sustained workload patterns. That improves both read and write performance while controlling cost better than manual scaling. A GSI is only useful for specific alternate query patterns and does not solve overall throughput management by itself. DAX helps only with read-heavy caching, not writes. A custom CloudWatch-plus-Lambda scaling solution adds unnecessary operational work compared to native auto scaling. Because the question asks broadly for read and write performance at the best cost, auto scaling with the recommended 70% target is the strongest answer.
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A company runs its applications on both Amazon EKS clusters and on-premises Kubernetes clusters. The company wants to view all clusters and workloads from a central location.
Which solution will meet these requirements with the LEAST operational overhead?
The correct answer isBbecause the company wants to view bothAmazon EKS clustersandon-premises Kubernetes clustersfrom acentral locationwith theleast operational overhead.Amazon EKS Connectoris designed for this purpose. It allows externally managed Kubernetes clusters, including on-premises clusters, to be registered to AWS so they can be viewed in theAmazon EKS consolealongside native EKS clusters. This creates a centralized management experience without requiring the company to migrate or rebuild the existing on-premises clusters.
EKS Connector is a low-overhead solution because it extends visibility into Kubernetes environments that are not running directly on Amazon EKS. It provides centralized cluster registration and observability at the AWS management layer while preserving the existing cluster deployments. This is especially useful for hybrid Kubernetes environments where organizations want a single control point for inventory and visibility.
Option A is incorrect becauseAmazon CloudWatch Container Insightsis primarily for metrics, logs, and performance monitoring. Although it provides observability, it is not the primary service for centrally registering and viewing clusters themselves in a unified cluster-management context. Option C is incorrect becauseAWS Systems Manageris not the main service for centralized Kubernetes cluster management. Option D is incorrect becauseAmazon EKS Anywhereis used to run Kubernetes on-premises, but it is not the simplest way to centrally view existing clusters with the least operational effort.
AWS guidance for hybrid Kubernetes visibility recommendsAmazon EKS Connectorfor connecting external Kubernetes clusters to AWS. Therefore, it is the most appropriate solution.
A company needs to design a solution to process videos that users upload to an Amazon S3 bucket. Each video file is approximately 1 GB in size and takes approximately 20 minutes to process. During peak hours, the company expects to process approximately 100 simultaneous uploads. The video file processing is stateless and can run in parallel as soon as the video files arrive in the S3 bucket.
Which solution will meet these requirements in the MOST cost-effective way?
The workload isstateless,parallel, and each job runs for about20 minutes, which makes Lambda a poor fit because Lambda has a maximum execution time of 15 minutes. AWS Fargate is a strong match for event-driven container workloads because it removes server management overhead, andFargate Spotlowers cost for interruption-tolerant processing. AWS also provides patterns for runningevent-driven workloads at scale with Fargate, and EventBridge can be used to trigger container tasks from S3-originated events. Compared with EKS or EC2 On-Demand, ECS on Fargate Spot is the most cost-effective managed container approach here.
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A company currently stores 5 TB of data in on-premises block storage systems. The company's current storage solution provides limited space for additional data. The company runs applications on premises that must be able to retrieve frequently accessed data with low latency. The company requires a cloud-based storage solution.
Which solution will meet these requirements with the MOST operational efficiency?
The company needs a cloud-based storage solution for frequently accessed data with low latency, while retaining their current on-premises infrastructure for some data storage. AWS Storage Gateway'sVolume Gateway with cached volumesis the most appropriate solution for this scenario.
AWS Storage Gateway - Volume Gateway (Cached Volumes):
Volume Gateway with cached volumesallows you to store frequently accessed data in the AWS Cloud while keeping the most recently accessed data cached locally on-premises. This ensures low-latency access to active data while providing scalability for the rest of the data in the cloud.
The cached volume option stores the primary data in Amazon S3 but caches frequently accessed data locally, ensuring fast access. This configuration is well-suited for applications that require fast access to frequently used data but can tolerate cloud-based storage for the rest.
Since the company is facing limited on-premises storage, cached volumes provide an ideal solution, as they reduce the need for additional on-premises storage infrastructure.
Why Not the Other Options?:
Option A (S3 File Gateway): S3 File Gateway provides a file-based interface (SMB/NFS) for storing data directly in S3. While it is great for file storage, the company's need for block-level storage with iSCSI targets makes Volume Gateway a better fit.
Option C (Volume Gateway - Stored Volumes): Stored volumes keep all the data on-premises and asynchronously back up to AWS. This would not address the company's storage limitations since they would still need substantial on-premises storage.
Option D (Tape Gateway): Tape Gateway is designed for archiving and backup, not for frequently accessed low-latency data.
AWS Reference:
AWS Storage Gateway - Volume Gateway
Tariq Nawaz
19 days ago