Correct option:

Annotations

AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components.

You can use X-Ray to collect data across AWS Accounts. The X-Ray agent can assume a role to publish data into an account different from the one in which it is running. This enables you to publish data from various components of your application into a central account.

How X-Ray Works:

via - https://aws.amazon.com/xray/

Annotations are simple key-value pairs that are indexed for use with filter expressions. Use annotations to record data that you want to use to group traces in the console, or when calling the GetTraceSummaries API.

X-Ray indexes up to 50 annotations per trace.

Incorrect options:

Metadata - Metadata are key-value pairs with values of any type, including objects and lists, but that is not indexed. Use metadata to record data you want to store in the trace but don't need to use for searching traces.

Segments - The computing resources running your application logic send data about their work as segments. A segment provides the resource's name, details about the request, and details about the work done.

Sampling - To ensure efficient tracing and provide a representative sample of the requests that your application serves, the X-Ray SDK applies a sampling algorithm to determine which requests get traced. By default, the X-Ray SDK records the first request each second, and five percent of any additional requests.

Reference:

https://docs.aws.amazon.com/xray/latest/devguide/xray-concepts.html

Correct option:

S3 Select

S3 Select enables applications to retrieve only a subset of data from an object by using simple SQL expressions. By using S3 Select to retrieve only the data needed by your application, you can achieve drastic performance increases in many cases you can get as much as a 400% improvement.

via - https://aws.amazon.com/blogs/aws/s3-glacier-select/

Incorrect options:

S3 Inventory - Amazon S3 inventory is one of the tools Amazon S3 provides to help manage your storage. You can use it to audit and report on the replication and encryption status of your objects for business, compliance, and regulatory needs.

S3 Analytics - By using Amazon S3 analytics storage class analysis you can analyze storage access patterns to help you decide when to transition the right data to the right storage class. This new Amazon S3 analytics feature observes data access patterns to help you determine when to transition less frequently accessed STANDARD storage to the STANDARD_IA (IA, for infrequent access) storage class.

S3 Access Logs - Server access logging provides detailed records for the requests that are made to a bucket. Server access logs are useful for many applications. For example, access log information can be useful in security and access audits. It can also help you learn about your customer base and understand your Amazon S3 bill.

Reference:

https://aws.amazon.com/blogs/aws/s3-glacier-select/

Correct option:

Canary Deployment

In a canary release deployment, total API traffic is separated at random into a production release and a canary release with a preconfigured ratio. Typically, the canary release receives a small percentage of API traffic and the production release takes up the rest. The updated API features are only visible to API traffic through the canary. You can adjust the canary traffic percentage to optimize test coverage or performance.

via - https://docs.aws.amazon.com/apigateway/latest/developerguide/canary-release.html

Incorrect options:

Stage Variables - They act like environment variables and can be used in your API setup.

Mapping Templates - Its a script to map the payload from a method request to the corresponding integration request and also maps the integration response to the corresponding method response.

Custom Authorizers - Used for authentication purposes and must return AWS Identity and Access Management (IAM) policies.

Reference:

https://docs.aws.amazon.com/apigateway/latest/developerguide/canary-release.html

Correct options:

--max-items

--starting-token

For commands that can return a large list of items, the AWS Command Line Interface (AWS CLI) has three options to control the number of items included in the output when the AWS CLI calls a service's API to populate the list.

--page-size

--max-items

--starting-token

By default, the AWS CLI uses a page size of 1000 and retrieves all available items. For example, if you run aws s3api list-objects on an Amazon S3 bucket that contains 3,500 objects, the AWS CLI makes four calls to Amazon S3, handling the service-specific pagination logic for you in the background and returning all 3,500 objects in the final output.

Here's an example: aws s3api list-objects --bucket my-bucket --max-items 100 --starting-token eyJNYXJrZXIiOiBudWxsLCAiYm90b190cnVuY2F0ZV9hbW91bnQiOiAxfQ==

Incorrect options:

"--page-size" - You can use the --page-size option to specify that the AWS CLI requests a smaller number of items from each call to the AWS service. The CLI still retrieves the full list but performs a larger number of service API calls in the background and retrieves a smaller number of items with each call.

"--next-token" - This is a made-up option and has been added as a distractor.

"--limit" - This is a made-up option and has been added as a distractor.

Reference:

https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-pagination.html

Correct option:

Provision EC2 instances in an Auto Scaling group to poll the messages from an SQS queue

As each message takes more than 15 minutes to process, therefore the development team cannot use Lambda for message processing. To build a scalable solution, the EC2 instances must be provisioning via an Auto Scaling group to handle variations in the message processing workload.

Amazon EC2 Auto Scaling Overview:

via - https://docs.aws.amazon.com/autoscaling/ec2/userguide/what-is-amazon-ec2-auto-scaling.html

Incorrect options:

Provision an EC2 instance to poll the messages from an SQS queue - Just using a single EC2 instance may not be sufficient to handle a sudden spike in the number of incoming messages.

Contact AWS Support to increase the Lambda timeout to 60 minutes - AWS Support cannot increase the Lambda timeout upper limit.

Use DynamoDB instead of RDS as database - This option has been added as a distractor, as changing the database would have no impact on the Lambda timeout while processing the message.

Reference:

https://docs.aws.amazon.com/autoscaling/ec2/userguide/what-is-amazon-ec2-auto-scaling.html