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Exam AWS Certified Solutions Architect - Professional All Questions

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Exam AWS Certified Solutions Architect - Professional topic 1 question 698 discussion

A company has an on-premises monitoring solution using a PostgreSQL database for persistence of events. The database is unable to scale due to heavy ingestion and it frequently runs out of storage.
The company wants to create a hybrid solution and has already set up a VPN connection between its network and AWS. The solution should include the following attributes:
✑ Managed AWS services to minimize operational complexity.
✑ A buffer that automatically scales to match the throughput of data and requires no ongoing administration.
✑ A visualization tool to create dashboards to observe events in near-real time.
✑ Support for semi-structured JSON data and dynamic schemas.
Which combination of components will enable the company to create a monitoring solution that will satisfy these requirements? (Choose two.)

  • A. Use Amazon Kinesis Data Firehose to buffer events. Create an AWS Lambda function to process and transform events.
  • B. Create an Amazon Kinesis data stream to buffer events. Create an AWS Lambda function to process and transform events.
  • C. Configure an Amazon Aurora PostgreSQL DB cluster to receive events. Use Amazon QuickSight to read from the database and create near-real-time visualizations and dashboards.
  • D. Configure Amazon Elasticsearch Service (Amazon ES) to receive events. Use the Kibana endpoint deployed with Amazon ES to create near-real-time visualizations and dashboards.
  • E. Configure an Amazon Neptune DB instance to receive events. Use Amazon QuickSight to read from the database and create near-real-time visualizations and dashboards.
Show Suggested Answer Hide Answer
Suggested Answer: BD 🗳️

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ExtHo
Highly Voted 3 years, 6 months ago
A is correct instead B and Final answer AD. https://aws.amazon.com/kinesis/data-firehose/faqs/ Q: What is Amazon Kinesis Data Firehose? It is a fully managed service that automatically scales to match the throughput of your data and requires no ongoing administration.
upvoted 17 times
DashL
3 years, 6 months ago
Unlike some other AWS services, Kinesis does not provide a native auto-scaling solution like DynamoDB On-Demand or EC2 Auto Scaling. Therefore, there is a need for the right number of shards to be calculated for every stream based on the expected number of records and/or the size of the records. This can lead to over/under-provisioning of shards within a stream resulting in higher costs and/or data ingestion being throttled.
upvoted 3 times
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Waiweng
Highly Voted 3 years, 6 months ago
It's A&D
upvoted 9 times
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Zinnia_Wang
Most Recent 4 months, 1 week ago
Selected Answer: BD
A is wrong: You can't connect on-premise events with kinesis data firehose directly. B is fully managed and can be auto-scaling with on-demand mode. It buffers the events with retention period up to 365 days.
upvoted 1 times
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CProgrammer
10 months ago
Its A & D simply because Firehose & Streams BOTH require on going Administration but Firehose less. There is no indication that processing via Streams ( complex transforms etc) is required, and that would easily make it Streams but it implies that Lambda is doing the work so for simplicity Firehose is the easier to configure and not worry about long term - ish. I had a nice long chat with Google Gemini over it ( ha ha) -- Kinesis Firehose: Offers a simpler setup with automatic buffer scaling and basic data delivery capabilities. While it can integrate with Lambda for pre-processing, the overall administration burden is less compared to Kinesis Data Streams. However, some configuration and monitoring of delivery destinations, access controls, and Lambda functions (if used) are still required.
upvoted 1 times
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robertohyena
2 years, 4 months ago
Selected Answer: BD
A - With Amazon Kinesis Data Streams, there are no servers to manage. The on-demand mode eliminates the need to provision or manage capacity required for running applications. D - Elasticsearch Service, now OpenSearch support semi-structured JSON data and dynamic schemas
upvoted 3 times
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Andykris
2 years, 8 months ago
D because data is semi structure.
upvoted 1 times
Andykris
2 years, 8 months ago
A becase Kenisis data firehose can scale and handle data traffic
upvoted 1 times
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Anhdd
2 years, 10 months ago
I still dont understand why choose D over C. Amazon QuickSight do the same thing as Kibana isn't it?
upvoted 3 times
korn666
1 year, 5 months ago
no ongoing administration
upvoted 1 times
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Niaj
2 years, 11 months ago
Selected Answer: AD
AD for sure is the right answer here
upvoted 1 times
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jj22222
3 years, 2 months ago
a and D look right
upvoted 1 times
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shaiker
3 years, 3 months ago
Selected Answer: AD
es is the only one doing the json unstructured data in the list. Aurora is relational and requires structured schema. firehose stream near realtime into es
upvoted 1 times
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tkanmani76
3 years, 3 months ago
A is fine. C - Why not QuickSight ? As this specifically handles embeddable dashboards with visualizations on real time basis. Kibana can as well do this along with ES - but why not QuickSight - AWS solution for dashboards ?.
upvoted 2 times
Anhdd
2 years, 10 months ago
seem that Aurora is relational and requires structured schema, while the question require the json unstructured data. In my opinion
upvoted 1 times
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tkanmani76
3 years, 3 months ago
Supporting Links - Confirming Quicksight support for handling JSON Semi structured data as well ..https://docs.aws.amazon.com/quicksight/latest/user/supported-data-sources.html
upvoted 1 times
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fanq10
2 years, 6 months ago
Why C? Here is the answer: https://www.elastic.co/guide/en/elasticsearch/reference/current/near-real-time.html Therefore, Amazon ES + kibana
upvoted 1 times
fanq10
2 years, 6 months ago
Sorry, a typo - Correction -> Why NOT C? Here is the answer: https://www.elastic.co/guide/en/elasticsearch/reference/current/near-real-time.html Therefore, the Answer is D: Amazon ES + kibana
upvoted 1 times
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cldy
3 years, 4 months ago
A. Use Amazon Kinesis Data Firehose to buffer events. Create an AWS Lambda function to process and transform events. D. Configure Amazon Elasticsearch Service (Amazon ES) to receive events. Use the Kibana endpoint deployed with Amazon ES to create near-real-time visualizations and dashboards.
upvoted 1 times
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AzureDP900
3 years, 4 months ago
A & D is right
upvoted 1 times
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acloudguru
3 years, 4 months ago
Selected Answer: AD
AD, this is a pattern of AWS, simple question, hope I can have it in my exam
upvoted 1 times
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andylogan
3 years, 5 months ago
It's A D
upvoted 1 times
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icttss
3 years, 5 months ago
how about B&E ? https://aws-samples.github.io/aws-dbs-refarch-graph/src/writing-from-amazon-kinesis-data-streams/
upvoted 2 times
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DerekKey
3 years, 5 months ago
A&D correct B wrong - Kinesis Datastream will not scale automatically. You must do it manually C wrong - "dynamic schemas"
upvoted 3 times
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