26/03/2024

To support critical production workloads that require maximum resiliency, a company wants to configure network connections between its Amazon VPC and the on-premises infrastructure. The company needs AWS Direct Connect connections with speeds greater than 1 Gbps.

As a solutions architect, which of the following will you suggest as the best architecture for this requirement?

• Opt for at least two Direct Connect connections terminating on different

  devices at a single Direct Connect location

• Opt for one Direct Connect connection at each of the multiple Direct

  Connect locations

• Use AWS Managed VPN as a backup for AWS Direct Connect

  connections to ensure maximum resiliency

• Opt for two separate Direct Connect connections terminating on

  separate devices in more than one Direct Connect location

Answer explanation

Correct option:

Opt for two separate Direct Connect connections terminating on separate devices in more than one Direct Connect location - Maximum resilience is achieved by separate connections terminating on separate devices in more than one location. This configuration offers customers maximum resilience to failure. As shown in the figure above, such a topology provides resilience to device failure, connectivity failure, and complete location failure. You can use Direct Connect Gateway to access any AWS Region (except AWS Regions in China) from any AWS Direct Connect locations.

A company has noticed several provisioned throughput exceptions on its DynamoDB database due to major spikes in the writes to the database. The development team wants to decouple the application layer from the database layer and dedicate a worker process to writing the data to DynamoDB.

Which middleware do you recommend on using that can scale infinitely and meet these requirements in the most cost effective way?

• Kinesis Data Streams

• DynamoDB DAX

• Amazon Simple Notification Service (SNS)

• Amazon Simple Queue Service (SQS)

Answer explanation

Correct option:

Amazon Simple Queue Service (SQS) - Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are processed exactly once, in the exact order that they are sent.

Using SQS as a middleware will help us sustain the write throughput during write peaks and therefore this option is the best fit for the given use-case.

Incorrect options:

DynamoDB DAX - Amazon DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second. DAX does all the heavy lifting required to add in-memory acceleration to your DynamoDB tables, without requiring developers to manage cache invalidation, data population, or cluster management.

DAX is used for caching reads, not to help with writes. So this option is ruled out.

Kinesis Data Streams - Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events. The throughput of an Amazon Kinesis data stream is designed to scale without limits via increasing the number of shards within a data stream. Kinesis is used to process consistent real-time data and does not scale as cost effectively as SQS to handle spikes in traffic.

Amazon Simple Notification Service (SNS) - Amazon Simple Notification Service (SNS) is a highly available, durable, secure, fully managed pub/sub messaging service that enables you to decouple microservices, distributed systems, and serverless applications. SNS won't keep our data if it cannot be delivered, so this option is incorrect.

The DevOps team at a major financial services company uses Multi-Availability Zone (Multi-AZ) deployment for its MySQL RDS database in order to automate its database replication and augment data durability. The DevOps team has scheduled a maintenance window for a database engine level upgrade for the coming weekend.

Which of the following is the correct outcome during the maintenance window?

• Any database engine level upgrade for an RDS DB instance with

  Multi-AZ deployment triggers both the primary and standby DB

  instances to be upgraded at the same time. This causes

  downtime until the upgrade is complete

• Any database engine level upgrade for an RDS DB instance with Multi-AZ

  deployment triggers both the primary and standby DB instances tobe

  upgraded at the same time. However, this does not cause any downtime

  until the upgrade is complete |

• Any database engine level upgrade for an RDS DB instance

  with Multi-AZ deployment triggers the standby DB instance to

  be upgraded which is then followed by the upgrade of the

  primary DB instance. This does not cause any downtime for the

  duration of the upgrade

• Any database engine level upgrade for an RDS DB instance with Multi-AZ

  deployment triggers the primary DB instance to be upgraded which is

  then followed by the upgrade of the standby DB instance. This does not

  cause any downtime for the duration of the upgrade

Answer explanation

Correct option:

Any database engine level upgrade for an RDS DB instance with Multi-AZ deployment triggers both the primary and standby DB instances to be upgraded at the same time. This causes downtime until the upgrade is complete

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching, and backups.

Upgrades to the database engine level require downtime. Even if your RDS DB instance uses a Multi-AZ deployment, both the primary and standby DB instances are upgraded at the same time. This causes downtime until the upgrade is complete, and the duration of the downtime varies based on the size of your DB instance.

https://aws.amazon.com/premiumsupport/knowledge-center/rds-required-maintenance/

A data analytics company is running a proprietary database on an EC2 instance using EBS volumes. The database is heavily I/O bound. As a solutions architect, which of the following RAID configurations would you recommend improving the I/O performance?

• Both RAID 0 and RAID 1 provide equally good 1/0 performance

• Amazon EBS does not support the standard RAID

  configurations

• Use RAID 1 when 1/0 performance is more important than fault tolerance

• Use RAID 0 when 1/0 performance is more important than fault

  tolerance

Answer explanation

Correct option:

Use RAID 0 when I/O performance is more important than fault tolerance

With Amazon EBS, you can use any of the standard RAID configurations that you can use with a traditional bare metal server, as long as that particular RAID configuration is supported by the operating system for your instance. This is because all RAID is accomplished at the software level.

Incorrect options:

Use RAID 1 when I/O performance is more important than fault tolerance - This is incorrect because you should use RAID 1 when fault tolerance is more important than I/O performance.

Both RAID 0 and RAID 1 provide equally good I/O performance - This is incorrect because RAID 0 provides better I/O performance.

Amazon EBS does not support the standard RAID configurations - This is incorrect because EBS supports the standard RAID configurations.

An e-commerce company uses RDS MySQL DB to store the data. The analytics department at the company runs its reports on the same DB. The engineering team has noticed sluggish performance on the DB when the analytics reporting process is in progress.

As an AWS Certified Solutions Architect Associate, which of the following would you suggest as the MOST cost-optimal solution to improve the performance?

• Create a standby instance in a multi-AZ configuration with the same

  compute capacity and the same storage capacity as the primary. Point the

  reporting queries to run against the standby instance

• Create a standby instance in a multi-AZ configuration with half compute

  capacity and half storage capacity as the primary. Point the reporting

  queries to run against the standby instance

• Create aread-replica with half compute capacity and halfstorage capacity as the primary. Point the reporting queries torun against the read replica

• Create a read-replica with the same compute capacity and the

  same storage capacity as the primary. Point the reporting

  queries to run against the read replica

Answer explanation

Correct option:

Create a read-replica with the same compute capacity and the same storage capacity as the primary. Point the reporting queries to run against the read replica

Amazon RDS uses the MariaDB, Microsoft SQL Server, MySQL, Oracle, and PostgreSQL DB engines' built-in replication functionality to create a special type of DB instance called a read replica from a source DB instance. The source DB instance becomes the primary DB instance. Updates made to the primary DB instance are asynchronously copied to the read replica. You can reduce the load on your primary DB instance by routing read queries from your applications to the read replica.

A Big Data company wants to optimize its daily Extract-Transform-Load (ETL) process that migrates and transforms data from its S3 based data lake to a Redshift cluster. The team wants to manage this daily job in a serverless environment.

Which AWS service is the best fit to manage this process without the need to configure or manage the underlying compute resources?

• Amazon EMR

• AWS Glue

• AWS Database Migration Service (DMS)

• AWS Data Pipeline

Answer explanation

Correct option:

AWS Glue - AWS Glue provides a managed ETL service that runs on a serverless Apache Spark environment. This allows you to focus on your ETL job and not worry about configuring and managing the underlying compute resources. AWS Glue takes a data-first approach and allows you to focus on the data properties and data manipulation to transform the data to a form where you can derive business insights. It provides an integrated data catalog that makes metadata available for ETL as well as querying via Amazon Athena and Amazon Redshift Spectrum.

AWS Glue automates much of the effort required for data integration. AWS Glue crawls your data sources, identifies data formats, and suggests schemas to store your data. It automatically generates the code to run your data transformations and loading processes. You can use AWS Glue to easily run and manage thousands of ETL jobs or to combine and replicate data across multiple data stores using SQL.

AWS Glue runs in a serverless environment. There is no infrastructure to manage, and AWS Glue provisions, configures, and scales the resources required to run your data integration jobs. You pay only for the resources your jobs use while running.

AWS Glue is the right fit since the company is looking at a managed ETL service without having the overhead of configuring, maintaining, or managing any servers.

via - https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/load-data-from-amazon-s3-to-amazon-redshift-using-aws-glue.html

Incorrect options:

AWS Data Pipeline - AWS Data Pipeline provides a managed orchestration service that gives you greater flexibility in terms of the execution environment, access and control over the compute resources that run your code, as well as the code itself that does data processing. AWS Data Pipeline launches compute resources in your account allowing you direct access to the Amazon EC2 instances or Amazon EMR clusters. As this option provides access to the underlying EC2 instances so it's not a serverless solution. Therefore this option is incorrect for the given use case.

Amazon EMR - EMR is a web service to easily and cost-effectively process vast amounts of data. EMR utilizes a hosted Hadoop framework running on the web-scale infrastructure of Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). As this option provides access to the underlying EC2 instances so it's not a serverless solution. Therefore this option is incorrect for the given use case.

AWS Database Migration Service (DMS) - AWS Database Migration Service (DMS) helps you migrate databases to AWS easily and securely. For use cases that require a database migration from on-premises to AWS or database replication between on-premises sources and sources on AWS, AWS recommends you use AWS DMS. Once your data is in AWS, you can use AWS Glue to move, combine, replicate, and transform data from your data source into another database or data warehouse, such as Amazon Redshift. As the use-case talks about data migration and transformation between AWS services, so AWS Glue is a better fit than DMS.

References:

https://aws.amazon.com/glue/faqs/

https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/load-data-from-amazon-s3-to-amazon-redshift-using-aws-glue.html