Exam2-Part3 Flashcards

1
Q

A company needs to ensure the safety of its employees by measuring the temperature of their facility every 5 minutes using smart sensors. They want to send the custom data metrics of their application to CloudWatch to view the data graphs visually.

Which of the below statements is true regarding the scenario above?

A

AWS CloudWatch supports uploading custom metrics.
To publish a single data point using CloudWatch for a new or existing metric, use the put-metric-data command with one value and the time stamp.

aws cloudwatch put-metric-data –metric-name PageViewCount –namespace MyService –value 2 –timestamp 2018-10-10-14T08:00:00.000Z

you can upload custom data metrics via aws CLI or API but you cannot upload custom metrics via the AWS Console.

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2
Q

unified CloudWatch Agent

A

– You can collect both logs and advanced metrics with the installation and configuration of just one agent.

– The unified agent enables the collection of logs from servers running Windows Server.

– If you are using the agent to collect CloudWatch metrics, the unified agent also enables the collection of additional system metrics, for in-guest visibility.

– The unified agent provides better performance.

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3
Q

AWS Systems Manager(SSM)

A

a management service provided by Amazon Web Services (AWS) that allows you to manage and automate operational tasks across your AWS resources. It provides a unified user interface to view and control your infrastructure, simplifying the management of servers, virtual machines, and other AWS resources. AWS SSM offers a range of features to help you maintain, configure, and monitor your resources at scale.

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4
Q

Amazon Rekognition Video

A

it can detect objects, scenes, faces, celebrities, text, and inappropriate content in videos. You can also search for faces appearing in a video using your own repository or collection of face images.

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5
Q

Object Lock

A

Amazon EBS does not support object lock. Amazon S3 is the only service capable of locking objects to prevent an object from being deleted or overwritten.

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6
Q

SQS Best Practices

A
  • Extend the message’s visibility timeout to the maximum time it takes to process and delete the message. If you don’t know how long it takes to process a message, as long as your consumer still works on the message, keep extending the visibility timeout.
  • Using the appropriate polling mode.
  • Configure a dead-letter queue to capture problematic messages.
  • To avoid inconsistent message processing by standard queues, avoid setting the number of maximum receives to 1 when you configure a dead-letter queue.
  • Don’t create reply queues per message. Instead, create reply queues on startup, per producer, and use a correlation ID message attribute to map replies to requests. Don’t let your producers share reply queues.
  • Reduce cost by batching message actions.
  • Use message deduplication IDs to monitor duplicate sent messages.
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7
Q

An insurance company plans to implement a message filtering feature in their web application. To implement this solution, they need to create separate Amazon SQS queues for each type of quote request. The entire message processing should not exceed 24 hours.

A

Create one Amazon SNS topic and configure the Amazon SQS queues to subscribe to the SNS topic. Set the filter policies in the SNS subscriptions to publish the message to the designated SQS queue based on its quote request type.

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8
Q

ALB gRPC protocol

A

ALBs can also route and load balance gRPC traffic between microservices or between gRPC-enabled clients and services. This will allow customers to seamlessly introduce gRPC traffic management in their architectures without changing any of the underlying infrastructure on their clients or services.

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9
Q

aws Snowball capacity

A

up to approximately 80 TB

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10
Q

What are the prerequisites when routing traffic using Amazon Route 53 to a website that is hosted in an Amazon S3 Bucket?

A
  • S3 bucket name must be the same as the domain name
  • A registered domain name
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11
Q

Amazon Rekognition

A

can help you streamline or automate image and video moderation workflows using machine learning. Using fully managed image and video moderation APIs, you can proactively detect inappropriate, unwanted, or offensive content containing nudity, suggestiveness, violence, and other such categories.

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