AWS SAA-C03：关键任务工作负载的存储解决方案

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"AWS新上线的SAA-C03学习文档提供了关于AWS服务的深入理解，特别是针对那些需要处理高优先级工作负载和数据管理需求的问题。文档中的一个关键部分是关于持久块存储的配置。当组织需要为mission-critical工作负载选择一个持久的EBS卷时，备份数据的安全性和长期存储成为关键考虑因素。问题41涉及到如何满足这样的需求：组织需要一个EBS卷用于关键任务，并且备份数据需要存储在对象存储服务中，之后在30天后转移到数据归档存储。正确选项B建议在EC2实例上附加一个EBS卷，并使用Amazon S3来存储备份数据。然后，通过配置生命周期策略，将对象迁移至Amazon S3 Glacier，这是一种经济高效且适合长期数据存档的服务，而不是OneZone-IA，后者通常用于需要低延迟访问的应用场景。解析部分强调了Amazon EBS的性能优势，以及如何通过合理的存储策略确保数据安全和成本效益。EBS因其易于使用和高性能，是AWS云中广泛使用的存储解决方案。然而，在处理敏感数据和合规性要求时，选择正确的归档存储服务至关重要。因此，文档详细解释了如何在AWS架构中平衡不同服务的功能，如EBS的实时性能和S3 Glacier的长期存储能力。学习这个文档不仅可以帮助考生准备AWS Certified Solutions Architect - Associate (SAA-C03)认证考试，还能加深对AWS服务在实际项目中的应用和优化的理解。通过理解这些知识点，IT专业人士可以更好地规划和管理AWS资源，提升企业的云基础设施效率和安全性。"

答案:C

解析:

Amazon CloudWatch has available Amazon EC2 Metrics for you to use for monitoring CPU utilization, Network

utilization, Disk performance, and Disk Reads/Writes. In case you need to monitor the below items, you need to prepare

a custom metric using a Perl or other shell script, as there are no ready to use metrics for:

Memory utilization

Disk swap utilization

Disk space utilization

Page file utilization

Log collection

Take note that there is a multi-platform CloudWatch agent which can be installed on both Linux and Windows-based

instances. You can use a single agent to collect both system metrics and log files from Amazon EC2 instances and

on-premises servers. This agent supports both Windows Server and Linux and enables you to select the metrics to be

collected, including sub-resource metrics such as per-CPU core. It is recommended that you use the new agent instead

of the older monitoring scripts to collect metrics and logs. Hence, the correct answer is: Install the CloudWatch agent to

all the EC2 instances that gathers the memory and disk utilization data. View the custom metrics in the Amazon

CloudWatch console. The option that says: Use the default CloudWatch configuration to EC2 instances where the

memory and disk utilization metrics are already available. Install the AWS Systems Manager (SSM) Agent to all the

EC2 instances is incorrect because, by default, CloudWatch does not automatically provide memory and disk utilization

metrics of your instances. You have to set up custom CloudWatch metrics to monitor the memory, disk swap, disk space,

and page file utilization of your instances. The option that says: Enable the Enhanced Monitoring option in EC2 and

install CloudWatch agent to all the EC2 instances to be able to view the memory and disk utilization in the CloudWatch

dashboard is incorrect because Enhanced Monitoring is a feature of Amazon RDS. By default, Enhanced Monitoring

metrics are stored for 30 days in the CloudWatch Logs. The option that says: Use Amazon Inspector and install the

Inspector agent to all EC2 instances is incorrect because Amazon Inspector is an automated security assessment

service that helps you test the network accessibility of your Amazon EC2 instances and the security state of your

applications running on the instances. It

does not provide a custom metric to track the memory and disk utilization of each and every EC2 instance in your VPC.

References:

https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/monitoring_ec2.html

https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/mon-scripts.html#using_put_script

1. Q50. A company is in the process of migrating their applications to AWS. One of their systems requires a database

that can scale globally and handle frequent schema changes. The application should not have any downtime or

performance issues whenever there is a schema change in the database. It should also provide a low latency response

to high-traffic queries.

Which is the most suitable database solution to use to achieve this requirement?

A. Redshift

B. Amazon DynamoDB

C. An Amazon RDS instance in Multi-AZ Deployments configuration

D. An Amazon Aurora database with Read Replicas

答案:B

解析:

Before we proceed in answering this question, we must first be clear with the actual definition of a "schema". Basically,

the english definition of a schema is: a representation of a plan or theory in the form of an outline or model.

Just think of a schema as the "structure" or a "model" of your data in your database. Since the scenario requires that the

schema, or the structure of your data, changes frequently, then you have to pick a database which provides a non-rigid

and flexible way of adding or removing new types of data. This is a classic example of choosing between a relational

database and non-relational (NoSQL) database. A relational database is known for having a rigid schema, with a lot of

constraints and limits as to which (and what type of ) data can be inserted or not. It is primarily used for scenarios where

you have to support complex queries which fetch data across a number of tables. It is best for scenarios where you

have complex table relationships but for use cases where you need to have a flexible schema, this is not a suitable

database to use.

For NoSQL, it is not as rigid as a relational database because you can easily add or remove rows or elements in your

table/collection entry. It also has a more flexible schema because it can store complex hierarchical data within a single

item which, unlike a relational database, does not entail changing multiple related tables. Hence, the best answer to be

used here is a NoSQL database, like DynamoDB. When your business requires a low-latency response to high-traffic

queries, taking advantage of a NoSQL system generally makes technical and economic sense.

Amazon DynamoDB helps solve the problems that limit the relational system scalability by avoiding them. In

DynamoDB, you design your schema specifically to make the most common and important queries as fast and as

inexpensive as possible. Your data structures are tailored to the specific requirements of your business use cases.

Remember that a relational database system does not scale well for the following reasons:

- It normalizes data and stores it on multiple tables that require multiple queries to write to disk.

- It generally incurs the performance costs of an ACID-compliant transaction system.

- It uses expensive joins to reassemble required views of query results.

For DynamoDB, it scales well due to these reasons:

- Its schema flexibility lets DynamoDB store complex hierarchical data within a single item. DynamoDB is not a totally

schemaless database since the very definition of a schema is just the model or structure of your data.

- Composite key design lets it store related items close together on the same table. An Amazon RDS instance in

Multi-AZ Deployments configuration and an Amazon Aurora database with Read Replicas are incorrect because both of

them are a type of relational database. Redshift is incorrect because it is primarily used for OLAP systems.

References:

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-general-nosql-design.html

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-relational-modeling.html

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/SQLtoNoSQL.html

1. Q51. A company is using a combination of API Gateway and Lambda for the web services of the online web portal

that is being accessed by hundreds of thousands of clients each day. They will be announcing a new revolutionary

product and it is expected that the web portal will receive a massive number of visitors all around the globe.

How can you protect the backend systems and applications from traffic spikes?

A. Use throttling limits in API Gateway

B. API Gateway will automatically scale and handle massive traffic spikes so you do not have to do anything.

C. Manually upgrade the EC2 instances being used by API Gateway

D. Deploy Multi-AZ in API Gateway with Read Replica

答案:A

解析:

Amazon API Gateway provides throttling at multiple levels including global and by a service call. Throttling limits can be

set for standard rates and bursts. For example, API owners can set a rate limit of 1,000 requests per second for a

specific method in their REST APIs, and also configure Amazon API Gateway to handle a burst of 2,000 requests per

second for a few seconds. Amazon API Gateway tracks the number of requests per second. Any requests over the limit

will receive a 429 HTTP response. The client SDKs generated by Amazon API Gateway retry calls automatically when

met with this response.

Hence, the correct answer is: Use throttling limits in API Gateway. The option that says: API Gateway will automatically

scale and handle massive traffic spikes so you do not have to do anything is incorrect. Although it can scale using AWS

Edge locations, you still need to configure the throttling to further manage the bursts of your APIs.

Manually upgrading the EC2 instances being used by API Gateway is incorrect because API Gateway is a fully

managed service and hence, you do not have access to its underlying resources. Deploying Multi-AZ in API Gateway

with Read Replica is incorrect because RDS has Multi-AZ and Read Replica capabilities, and not API Gateway.

Reference:

https://aws.amazon.com/api-gateway/faqs/#Throttling_and_Caching

1. Q52. A company is designing a banking portal that uses Amazon ElastiCache for Redis as its distributed session

management component. Since the other Cloud Engineers in your department have access to your ElastiCache cluster,

you have to secure the session data in the portal by requiring them to enter a password before they are granted

permission to execute Redis commands. As the Solutions Architect, which of the following should you do to meet the

above requirement?

A. Authenticate the users using Redis AUTH by creating a new Redis Cluster with both the -- transit-

encryption-enabled and --auth-token parameters enabled.

B. Set up a Redis replication group and enable the AtRestEncryptionEnabled parameter.

C. Set up an IAM Policy and MFA which requires the Cloud Engineers to enter their IAM credentials and token before

they can access the ElastiCache cluster.

D. Enable the in-transit encryption for Redis replication groups.

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