A company has a serverless application made up of AWS Amplify, Amazon API Gateway and a Lambda function. The application is connected to an Amazon RDS MySQL database instance inside a private subnet. A Lambda Function URL is also implemented as the dedicated HTTPS endpoint for the function, which has the following value:
https://12june1898pil1pinas.lambda-url.us-west-2.on.aws/
There are times during peak loads when the database throws a "too many connections" error preventing the users from accessing the application.
Which solution could the company take to resolve the issue?

• A.Increase the memory allocation of the Lambda function
• B.Provision an RDS Proxy between the Lambda function and RDS database instance
• C.Increase the concurrency limit of the Lambda function
• D.Increase the rate limit of API Gateway

Correct Answer: B

If a "Too Many Connections" error happens to a client connecting to a MySQL database, it means all available connections are in use by other clients. Opening a connection consumes resources on the database server. Since Lambda functions can scale to tens of thousands of concurrent connections, your database needs more resources to open and maintain connections instead of executing queries. The maximum number of connections a database can support is largely determined by the amount of memory allocated to it. Upgrading to a database instance with higher memory is a straightforward way of solving the problem. Another approach would be to maintain a connection pool that clients can reuse.
This is where RDS Proxy comes in.

RDS Proxy helps you manage a large number of connections from Lambda to an RDS database by establishing a warm connection pool to the database. Your Lambda functions interact with RDS Proxy instead of your database instance. It handles the connection pooling necessary for scaling many simultaneous connections created by concurrent Lambda functions. This allows your Lambda applications to reuse existing connections, rather than creating new connections for every function invocation.
Thus, the correct answer is: Provision an RDS Proxy between the Lambda function and RDS database instance format The option that says: Increase the concurrency limit of the Lambda function is incorrect. The concurrency limit refers to the maximum requests AWS Lambda can handle at the same time. Increasing the limit will allow for more requests to open a database connection, which could potentially worsen the problem.
The option that says: Increase the rate limit of API Gateway is incorrect. This won't fix the issue at all as all it does is increase the number of API requests a client can make.
The option that says: Increase the memory allocation of the Lambda function is incorrect. Increasing the Lambda function's memory would only make it run processes faster. It can help but it won't likely do any significant effect to get rid of the error. The "too many connections" error is a database-related issue.
Solutions that have to do with databases, like upgrading to a larger database instance or, in this case, creating a database connection pool using RDS Proxy have better chance of resolving the problem.
References:
https://aws.amazon.com/rds/proxy/
https://aws.amazon.com/blogs/compute/using-amazon-rds-proxy-with-aws-lambda/ Check out this Amazon RDS Cheat Sheet:
https://tutorialsdojo.com/amazon-relational-database-service-amazon-rds/

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A company has a data ingestion workflow that consists the following:
* An Amazon Simple Notification Service (Amazon SNS) topic for notifications about new data deliveries
* An AWS Lambda function to process the data and record metadata
The company observes that the ingestion workflow fails occasionally because of network connectivity issues.
When such a failure occurs, the Lambda function does not ingest the corresponding data unless the company manually reruns the job.
Which combination of actions should a solutions architect take to ensure that the Lambda function ingests all data in the future? (Select TWO.)

• A.Configure the Lambda function In multiple Availability Zones.
• B.Create an Amazon Simple Queue Service (Amazon SQS) queue, and subscribe It to me SNS topic.
• C.Increase the CPU and memory that are allocated to the Lambda function.
• D.Increase provisioned throughput for the Lambda function.
• E.Modify the Lambda function to read from an Amazon Simple Queue Service (Amazon SQS) queue

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A company has a cryptocurrency exchange portal that is hosted in an Auto Scaling group of EC2 instances behind an Application Load Balancer and is deployed across multiple AWS regions. The users can be found all around the globe, but the majority are from Japan and Sweden. Because of the compliance requirements in these two locations, you want the Japanese users to connect to the servers in the ap-northeast-1 Asia Pacific (Tokyo) region, while the Swedish users should be connected to the servers in the eu-west-1 EU (Ireland) region.
Which of the following services would allow you to easily fulfill this requirement?

• A.Use Route 53 Geolocation Routing policy.
• B.Use Route 53 Weighted Routing policy.
• C.Set up an Application Load Balancers that will automatically route the traffic to the proper AWS region.
• D.Set up a new CloudFront web distribution with the geo-restriction feature enabled.

Correct Answer: A

Geolocation routing lets you choose the resources that serve your traffic based on the geographic location of your users, meaning the location that DNS queries originate from. For example, you might want all queries from Europe to be routed to an ELB load balancer in the Frankfurt region.
When you use geolocation routing, you can localize your content and present some or all of your website in the language of your users. You can also use geolocation routing to restrict distribution of content to only the locations in which you have distribution rights. Another possible use is for balancing load across endpoints in a predictable, easy-to-manage way, so that each user location is consistently routed to the same endpoint.

Setting up an Application Load Balancers that will automatically route the traffic to the proper AWS region is incorrect because Elastic Load Balancers distribute traffic among EC2 instances across multiple Availability Zones but not across AWS regions.
Setting up a new CloudFront web distribution with the geo-restriction feature enabled is incorrect because the CloudFront geo-restriction feature is primarily used to prevent users in specific geographic locations from accessing content that you're distributing through a CloudFront web distribution. It does not let you choose the resources that serve your traffic based on the geographic location of your users, unlike the Geolocation routing policy in Route 53.
Using Route 53 Weighted Routing policy is incorrect because this is not a suitable solution to meet the requirements of this scenario. It just lets you associate multiple resources with a single domain name (tutorialsdojo.com) or subdomain name (forums.tutorialsdojo.com) and choose how much traffic is routed to each resource. You have to use a Geolocation routing policy instead. References:
https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/routing-policy.html
https://aws.amazon.com/premiumsupport/knowledge-center/geolocation-routing-policy Check out this Amazon Route 53 Cheat Sheet:
https://tutorialsdojo.com/amazon-route-53/
Latency Routing vs Geoproximity Routing vs Geolocation Routing: https://tutorialsdojo.com/latency- routing-vs-geoproximity-routing-vs-geolocation-routing/ Comparison of AWS Services Cheat Sheets:
https://tutorialsdojo.com/comparison-of-aws-services/

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A company recently launched an e-commerce application that is running in eu-east-2 region, which strictly requires six EC2 instances running at all times. In that region, there are 3 Availability Zones (AZ) that you can use - eu-east-2a, eu-east-2b, and eu-east-2c.
Which of the following deployments provide 100% fault tolerance if any single AZ in the region becomes unavailable? (Select TWO.)

• A.eu-east-2a with four EC2 instances, eu-east-2b with two EC2 instances, and eu-east-2c with two EC2 instances
• B.eu-east-2a with six EC2 instances, eu-east-2b with six EC2 instances, and eu-east-2c with no EC2 instances
• C.eu-east-2a with two EC2 instances, eu-east-2b with four EC2 instances, and eu-east-2c with two EC2 instances
• D.eu-east-2a with three EC2 instances, eu-east-2b with three EC2 instances, and eu-east-2c with three EC2 instances
• E.eu-east-2a with two EC2 instances, eu-east-2b with two EC2 instances, and eu-east-2c with two EC2 instances

Correct Answer: B,D

Fault Tolerance is the ability of a system to remain in operation even if some of the components used to build the system fail. In AWS, this means that in the event of server fault or system failures, the number of running EC2 instances should not fall below the minimum number of instances required by the system for it to work properly. So if the application requires a minimum of 6 instances, there should be at least 6 instances running in case there is an outage in one of the Availability Zones or if there are server issues.


In this scenario, you have to simulate a situation where one Availability Zone became unavailable for each option and check whether it still has 6 running instances.
Hence, the correct answers are: eu-east-2a with six EC2 instances, eu-east-2b with six EC2 instances, and eu-east-2c with no EC2 instances and eu-east-2a with three EC2 instances, eu-east-2b with three EC2 instances, and eu-east-2c with three EC2 instances because even if one of the availability zones were to go down, there would still be 6 active instances.
Reference:
https://media.amazonwebservices.com/AWS_Building_Fault_Tolerant_Applications.pdf

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A company stores call transcript files on a monthly basis. Users access the files randomly within 1 year of the call, but users access the files infrequently after 1 year. The company wants to optimize its solution by giving users the ability to query and retrieve files that are less than 1-year-old as quickly as possible. A delay in retrieving older files is acceptable.
Which solution will meet these requirements MOST cost-effectively?

• A.Store individual files in Amazon S3 Intelligent-Tiering. Use S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year. Query and retrieve the files that are in Amazon S3 by using Amazon Athena. Query and retrieve the files that are in S3 Glacier by using S3 Glacier Select.
• B.Store individual files with tags in Amazon S3 Standard storage. Store search metadata for each archive in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Instant Retrieval after 1 year. Query and retrieve the files by searching for metadata from Amazon S3.
• C.Store individual files in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Deep Archive after 1 year. Store search metadata in Amazon RDS. Query the files from Amazon RDS. Retrieve the files from S3 Glacier Deep Archive.
• D.Store individual files with tags in Amazon S3 Glacier Instant Retrieval. Query the tags to retrieve the files from S3 Glacier Instant Retrieval.

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