Amazon Web Services CLF-C02 - AWS Certified Cloud Practitioner

Understanding Amazon Snowball Edge: Amazon Snowball Edge is a data migration and edge computing device that helps in transferring large amounts of data to and from AWS.

No-Cost Activities:

Transfer into S3: AWS does not charge for transferring data from the Snowball Edge device into Amazon S3. This is part of the service to facilitate easy data migration into the AWS cloud.

Other Costs: The use of the Snowball Edge appliance for up to 10 days is included in the service fee. However, any usage beyond the 10-day period may incur additional costs.

How to Utilize Snowball Edge:

Order the Device: Use the AWS Management Console to order a Snowball Edge device.

Load Data: Transfer your data onto the Snowball Edge appliance.

Ship Back: Ship the device back to AWS, where the data will be uploaded to Amazon S3 at no additional cost.

Amazon Snowball Edge Pricing

Amazon Snowball Edge Documentation

Amazon AppStream 2.0 and Amazon WorkSpaces are AWS services that can be used to provide managed Windows virtual desktops and applications to remote employees over secure network connections. Amazon AppStream 2.0 is a fully managed application streaming service that allows users to access Windows desktop applications from any device, without installing or managing any software. Amazon AppStream 2.0 delivers applications over an encrypted connection and isolates them from the underlying infrastructure, ensuring security and compliance1. Amazon WorkSpaces is a fully managed desktop virtualization service that allows users to access Windows or Linux desktops from any device, with a consistent user experience. Amazon WorkSpaces provides persistent, cloud-based virtual desktops that can be customized and scaled according to the user’s needs. Amazon WorkSpaces also offers encryption, backup, and monitoring features to ensure security and reliability2. References:

Amazon AppStream 2.0

Amazon WorkSpaces

AWS Outposts is a fully managed service that extends AWS infrastructure, services, APIs, and tools to customer premises. By providing local access to AWS managed infrastructure, AWS Outposts enables customers to build and run applications on premises using the same programming interfaces as in AWS Regions, while using local compute and storage resources for lower latency and local data processing needs. An Outpost is a pool of AWS compute and storage capacity deployed at a customer site. AWS operates, monitors, and manages this capacity as part of an AWS Region. You can create subnets on your Outpost and specify them when you create AWS resources such as EC2 instances, EBS volumes, ECS clusters, and RDS instances. Instances in Outpost subnets communicate with other instances in the AWS Region using private IP addresses, all within the same VPC. Outposts solutions allow you to extend and run native AWS services on premises, and isavailable in a variety of form factors, from 1U and 2U Outposts servers to 42U Outposts racks, and multiple rack deployments. With AWS Outposts, you can run some AWS services locally and connect to a broad range of services available in the local AWS Region2. AWS Outposts is a hybrid cloud deployment model that uses AWS Outposts as part of the application deployment infrastructure. Hybrid cloud is a cloud computing environment that uses a mix of on-premises, private cloud, and public cloud services with orchestration between the platforms. Hybrid cloud provides businesses with greater flexibility, more deployment options, and optimized costs. By using AWS Outposts, customers can benefit from the fully managed infrastructure, services, APIs, and tools of AWS on premises, while still having access to the full range of AWS services available in the Region for a truly consistent hybrid experience3. References: On-Premises Private Cloud - AWS Outposts Family - AWS, What is AWS Outposts? - AWS Outposts

Amazon EC2 Auto Scaling is a service that helps you maintain application availability and allows you to automatically add or remove EC2 instances according to definable conditions. You can create collections of EC2 instances, called Auto Scaling groups, and specify the minimum and maximum number of instances in each group. You can also define scaling policies that adjust the number of instances based on the demand on your application. Amazon EC2 Auto Scaling helps you improve the performance, reliability, and cost-efficiency of your EC2workloads123. References: 1: VDI Desktops - Amazon WorkSpaces Family - AWS, 2: What is Amazon EC2 Auto Scaling? - Amazon EC2 Auto Scaling, 3: Discover Amazon EC2 Auto Scaling Unit | Salesforce Trailhead

AWS Software Development Kit (SDK) is a set of platform-specific building tools for developers. It allows developers to access AWS services from application code using familiar programming languages. It provides pre-built components and libraries that can be incorporated into applications, as well as tools to debug, monitor, and optimize performance2. References: What is SDK? - SDK Explained - AWS

VPC 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 can be published to the following locations: Amazon CloudWatch Logs, Amazon S3, or Amazon Kinesis Data Firehose. You can use VPC Flow Logs to monitor network traffic, diagnose security issues, troubleshoot connectivity problems, and perform network forensics1. References:

Logging IP traffic using VPC Flow Logs - Amazon Virtual Private Cloud

Spot Instancesare the most cost-effective EC2 instance purchasing option for batch workloads that can handle interruptions and can be restarted from where they left off. Spot Instances offer significant cost savings (up to 90%) over On-Demand Instances by using spare EC2 capacity. They are ideal for workloads that are fault-tolerant and flexible in terms of timing.

A. Reserved Instances: Incorrect, as they require a long-term commitment and do not offer the flexibility needed for short-term, interruptible workloads.

C. Dedicated Instances: Incorrect, as they are designed to run on hardware dedicated to a single customer, which is more expensive.

D. On-Demand Instances: Incorrect, as they are more expensive than Spot Instances and are used for applications that require immediate or predictable capacity.

AWS Cloud References:

Amazon EC2 Spot Instances

According to the AWS Shared Responsibility Model, AWS is responsible for the security of the cloud, while the customer is responsible for the security in the cloud. This means that AWS is responsible for protecting the infrastructure that runs AWS services, such as DynamoDB, while the customer is responsible for properly configuring the security of the provided service. For abstracted services, such as DynamoDB, the customer is primarily responsible for managing their data, classifying their assets, and using IAM tools to apply the appropriatepermissions12. Therefore, the customer is responsible for controlling the access to DynamoDB tables, such as by creating IAM policies, roles, and users, and using encryption and authentication mechanisms3. References:

Shared Responsibility Model - Amazon Web Services (AWS)

Security and compliance in Amazon DynamoDB - Amazon DynamoDB

What is Shared Responsibility Model? - Check Point Software

Amazon Elastic File System (Amazon EFS) is a fully managed, scalable, and serverless NFS (Network File System) file system specifically designed for use with AWS services and on-premises resources. It enables companies to create and configure file systems that can be accessed from multiple Amazon EC2instances simultaneously, making it ideal for use cases that require shared file storage for AWS compute services.

Why Amazon EFS Fits the Requirements:

Managed Service: Amazon EFS is a fully managed file storage service that simplifies the process of setting up and managing NFS file systems.

Scalability and Elasticity: EFS automatically scales to accommodate the storage needs of applications, without the need to provision or manage storage capacity.

NFS Compatibility: Amazon EFS natively supports the NFSv4 protocol, making it compatible with a wide range of applications and workloads that require NFS access.

Integration with AWS Compute Services: EFS integrates seamlessly with Amazon EC2 and other AWS services, providing a shared file storage solution across multiple instances and services within the AWS cloud environment.

Why Other Options Do Not Fit:

A. Amazon Elastic Block Store (Amazon EBS): While EBS provides block-level storage that can be attached to individual EC2 instances, it is not a file system, nor does it provide managed NFS file storage capabilities. EBS is designed for single-instance access rather than shared file access across multiple instances.

B. AWS Storage Gateway Tape Gateway: Tape Gateway is designed for archival purposes and allows companies to store virtual tape backups in Amazon S3 or Glacier. It does not support NFS file storage and is not intended for regular compute access.

C. Amazon S3 Glacier Flexible Retrieval: Amazon S3 Glacier is optimized for data archiving and long-term storage of infrequently accessed data, but it does not provide NFS file system capabilities, nor is it suitable for high-performance access needs associated with compute services.

For more details, you can refer to theAWS Cloud Practitioner Essentialscontent, specifically the modules onStorage Serviceswhere Amazon EFS is covered as the managed NFS file storage solution offered by AWS.

Amazon SageMakeris a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. It offers integrated Jupyter notebooks for data exploration, pre-built algorithms, and automatic model tuning to optimize hyperparameters.

Why other options are not suitable:

A. Amazon Personalize: A managed machine learning service that provides personalized recommendations, but does not offer the full suite of ML tools for building, training, and deploying models.

B. Amazon Comprehend: A natural language processing (NLP) service, not a general-purpose ML model building and deployment service.

C. Amazon Forecast: A managed service specifically for creating accurate forecasts using machine learning, not for general-purpose ML model development.

One of the primary advantages of the AWS Cloud is the ability to provision resources on demand. Users no longer need to over-provision or guess the capacity needed for infrastructure, which helps optimizecosts and improve agility. AWS handles infrastructure scaling dynamically based on the actual usage. Options B, C, and D are incorrect as users do not maintain sole ownership of IT hardware or control of underlying infrastructure, and while they do maintain some control over the operating system in some cases, it is not an advantage specific to the cloud.

Amazon EC2 is the most suitable AWS service for this workload. Amazon EC2 provides secure, resizable compute capacity in the cloud. You can launch virtual servers, called instances, and configure them according to your needs. You can choose from different instance types, sizes, and families, and pay only for the resources you use. Amazon EC2 also offers features such as auto scaling, load balancing, security groups, and placement groups to optimize your performance, availability, and security1. Amazon EC2 is ideal for workloads that require consistent and reliable compute power, such as data processing, web hosting, gaming, and high-performance computing2. The other services are not suitable for this workload. AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You pay only for the compute time you consume. Lambda is best for short-lived, stateless, and event-driven workloads that can becompleted in under 15 minutes3. AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances, serverless Lambda functions, or Amazon ECS services. CodeDeploy is not a compute service, but a tool to help you update your applications with minimal downtime4. AWS Wavelength is a service that delivers ultra-low latency applications for 5G devices. Wavelength embeds AWS compute and storage services at the edge of telecommunications providers’ 5G networks. Wavelength is designed for mobile edge computing, such as interactive gaming, video streaming, and augmentedreality. References: Amazon EC2, Amazon EC2 Use Cases, AWS Lambda, AWS CodeDeploy, [AWS Wavelength]

Users can change their own IAM user password using:

AWS Management Console: The graphical interface allows users to navigate to the "My Security Credentials" page and change their password.

AWS Command Line Interface (CLI): Users with the appropriate permissions can use theaws iam change-passwordcommand to change their password.

Why other options are not suitable:

B. AWS Key Management Service (AWS KMS): Used for creating and managing encryption keys, not for managing user passwords.

D. AWS Resource Access Manager (AWS RAM): Used for resource sharing between accounts, not for password management.

E. AWS Secrets Manager: A service for securely storing and managing secrets, not for changing IAM user passwords.

AWS CloudFormation is a service that allows you to model and provision your AWS resources using templates. You can define your infrastructure as code and automate the creation and update of your resources. AWS CloudFormation also supports nested stacks, change sets, and rollback features to help you manage complex and dynamic environments34. References:

AWS CloudFormation

AWS Certified Cloud Practitioner Exam Guide

According to the AWS shared responsibility model, AWS is responsible for protecting the infrastructure that runs all ofthe services offered in the AWS Cloud, such as data centers, hardware, software, networking, and facilities1. This includes the configuration of infrastructure devices, such as routers, switches, firewalls, and load balancers2. Customers are responsible for managing their data, applications, operating systems, security groups, and other aspects of their AWS environment1. Therefore, options A, B, and D are customer responsibilities, not AWS responsibilities. References: 1: AWS Well-Architected Framework - Elasticity; 2: Reactive Systems on AWS - Elastic