Amazon DVA-C02 Exam - Topic 7 Question 27 Discussion

Actual exam question for Amazon's DVA-C02 exam

Question #: 27
Topic #: 7

A company has installed smart motes in all Its customer locations. The smart meter's measure power usage at 1minute intervals and send the usage readings to a remote endpoint tot collection. The company needs to create an endpoint that will receive the smart meter readings and store the readings in a database. The company wants to store the location ID and timestamp information.

The company wants to give Is customers low-latency access to their current usage and historical usage on demand The company expects demand to increase significantly. The solution must not impact performance or include downtime write seeing.

When solution will meet these requirements MOST cost-effectively?

AStore the smart meter readings in an Amazon RDS database. Create an index on the location ID and timestamp columns Use the columns to filter on the customers 'data.

BStore the smart motor readings m an Amazon DynamoDB table Croato a composite Key oy using the location ID and timestamp columns. Use the columns to filter on the customers' data.

CStore the smart meter readings in Amazon EastCache for Reds Create a Sorted set key y using the location ID and timestamp columns. Use the columns to filter on the customers' data.

DStore the smart meter readings m Amazon S3 Parton the data by using the location ID and timestamp columns. Use Amazon Athena lo tiler on me customers' data.

Show Suggested Answer

Suggested Answer: D

AWS STS AssumeRole:The central operation for assuming temporary security credentials, commonly used for cross-account access.

MFA Integration:TheAssumeRolecall can include MFA information to enforce multi-factor authentication.

Credentials for S3 Access:The returned temporary credentials would provide the necessary permissions to access the S3 bucket in the other account.

AWS STS AssumeRole Documentation:https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRole.html

by Toi at May 19, 2024, 02:25 AM

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Brock

5 months ago

S3 with Athena sounds interesting, but is it really efficient for this use case?

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Ronald

5 months ago

RDS might be too slow with high demand, right?

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Arleen

5 months ago

Wait, can DynamoDB handle that much data without issues?

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Lorrine

5 months ago

I agree, DynamoDB is great for low-latency access!

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Vivienne

6 months ago

Option B seems like the best choice for scalability.

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Stephen

6 months ago

I recall that S3 with Athena is great for analytics, but I'm not convinced it's the best for low-latency access. It might be slower than the other options.

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Kati

6 months ago

I practiced a similar question where we had to choose between NoSQL and SQL databases. I think DynamoDB's composite key feature could help with filtering efficiently.

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Gerald

6 months ago

I'm not entirely sure, but I feel like using Amazon RDS could lead to performance issues with high demand. We might need to consider scalability.

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Pa

6 months ago

I remember we discussed the importance of low-latency access for real-time data. I think DynamoDB might be a good fit for that.

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Veronica

6 months ago

The Redis option with a sorted set key seems interesting, but I'm not sure how well it would scale compared to a purpose-built database service like DynamoDB. I'd want to do some performance testing to see how it handles the expected load.

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Talia

6 months ago

Based on the requirements, I think DynamoDB could be a good fit. The ability to create a composite key using location ID and timestamp would allow for efficient filtering and retrieval of customer data. And as a NoSQL database, it should be able to handle the expected increase in demand.

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Aron

6 months ago

I'm a bit confused by the options presented. It's not clear to me how each solution would address the specific requirements. I'd want to do some more research on the pros and cons of each database service before making a decision.

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Angelo

6 months ago

This seems like a classic database design problem. I'd start by considering the key requirements - low-latency access, high performance, and no downtime. A relational database like RDS might work, but I'm not sure it would be the most cost-effective solution.

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Lindsey

7 months ago

Okay, let's see here. The first thing I'd do is look at the columns being used in the queries and see if any of them could benefit from an index.

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Adelina

7 months ago

This seems straightforward, the question is asking if the VCN3020 can connect 512 channels of cameras with a total bandwidth of 1024 Mbit/s, so I'll go with TRUE.

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Jose

11 months ago

I'm leaning towards option B as well. DynamoDB seems like the most straightforward and scalable solution for this use case. Although, I wonder if they'll have to deal with any 'smart mote' puns from their customers.

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Clarinda

11 months ago

Haha, storing the data in Amazon S3 and using Athena to filter it? That's like trying to find a needle in a haystack with a toothpick!

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Lenora

10 months ago

Haha, storing the data in Amazon S3 and using Athena to filter it? That's like trying to find a needle in a haystack with a toothpick!

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Lino

10 months ago

C) Store the smart meter readings in Amazon EastCache for Reds Create a Sorted set key y using the location ID and timestamp columns. Use the columns to filter on the customers' data.

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Dallas

10 months ago

B) Store the smart motor readings m an Amazon DynamoDB table Croato a composite Key oy using the location ID and timestamp columns. Use the columns to filter on the customers' data.

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Virgina

11 months ago

A) Store the smart meter readings in an Amazon RDS database. Create an index on the location ID and timestamp columns Use the columns to filter on the customers 'data.

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Rebbecca

11 months ago

Option C with Amazon ElastiCache for Redis looks interesting, but I'm not sure if the Sorted set key approach will be as efficient as the composite key in DynamoDB for filtering the customer data.

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Margart

11 months ago

I think option B is the most cost-effective solution. DynamoDB provides low-latency access and can handle the expected increase in demand without impacting performance or causing downtime during writes.

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