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Exam AWS Certified Solutions Architect - Professional SAP-C02 All Questions

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Exam AWS Certified Solutions Architect - Professional SAP-C02 topic 1 question 80 discussion

A company runs an IoT platform on AWS. IoT sensors in various locations send data to the company’s Node.js API servers on Amazon EC2 instances running behind an Application Load Balancer. The data is stored in an Amazon RDS MySQL DB instance that uses a 4 TB General Purpose SSD volume.

The number of sensors the company has deployed in the field has increased over time, and is expected to grow significantly. The API servers are consistently overloaded and RDS metrics show high write latency.

Which of the following steps together will resolve the issues permanently and enable growth as new sensors are provisioned, while keeping this platform cost-efficient? (Choose two.)

  • A. Resize the MySQL General Purpose SSD storage to 6 TB to improve the volume’s IOPS.
  • B. Re-architect the database tier to use Amazon Aurora instead of an RDS MySQL DB instance and add read replicas.
  • C. Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data.
  • D. Use AWS X-Ray to analyze and debug application issues and add more API servers to match the load.
  • E. Re-architect the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance.
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Suggested Answer: CE 🗳️

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masetromain
Highly Voted 1 year, 10 months ago
Selected Answer: CE
C and E are the correct answers. Option C: Leveraging Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data would help to resolve the issues with the API servers being consistently overloaded. By using Kinesis, the data can be ingested and processed in real-time, allowing the API servers to handle the increased load. Using Lambda to process the data can also help to improve the overall performance and scalability of the platform. Option E: Re-architecting the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance would help to resolve the issues with high write latency. DynamoDB is a NoSQL database that is designed for high performance and scalability, making it a good fit for this use case. Additionally, DynamoDB supports auto-scaling, which can help to ensure that the database can handle the expected growth in the number of sensors.
upvoted 20 times
SuperP43
1 year, 9 months ago
I disagree with option E. Re-architecting the database tier from RDS to DynamoDB is not possible. RDS is a SQL database, and DynamoDB is a NoSQL database. The correct one should be C and B
upvoted 6 times
ajeeshb
8 months, 2 weeks ago
That is why it says to "Re-architect the DB tier".
upvoted 4 times
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tromyunpak
1 year, 5 months ago
if it was read operations yes but the issue is write latency. also rds proxy is used to handle the write operations
upvoted 2 times
tromyunpak
1 year, 5 months ago
also rds proxy is not used (sorry typo) to handle write operations properly
upvoted 1 times
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kamaro
1 year, 8 months ago
I agree with you. https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html Aurora can deliver up to five times the throughput of MySQL and up to three times the throughput of PostgreSQL without requiring changes to most of your existing applications. Aurora includes a high-performance storage subsystem. Its MySQL- and PostgreSQL-compatible database engines are customized to take advantage of that fast distributed storage. The underlying storage grows automatically as needed. An Aurora cluster volume can grow to a maximum size of 128 tebibytes (TiB).
upvoted 2 times
zejou1
1 year, 8 months ago
Naw, you can migrate: https://aws.amazon.com/blogs/big-data/near-zero-downtime-migration-from-mysql-to-dynamodb/ Plus, with DynamoDB it scales, don't need to add read replica complexity and it also supports IoT out of the box - https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/SQLtoNoSQL.WhyDynamoDB.html This is for IoT sensors that send data and I don't need to store forever so, DynamoDB for this use case is better and cheaper allowing scale
upvoted 1 times
Sarutobi
1 year, 6 months ago
I think this is the big point in this question and that DynamoDB is being position by AWS for IoT very hard. Although is technically possible to migrate with DMS from SQL to DynamoDB, is hard, but harder yet is the change of model inside the application or service.
upvoted 1 times
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OCHT
1 year, 7 months ago
While options C and E may also provide some benefits, they may not address the underlying issues with the overloaded API servers and high write latency in the database. Therefore, options B and D are the best combination for resolving the issues and enabling growth as new sensors are provisioned.
upvoted 1 times
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masetromain
1 year, 10 months ago
Option A, Resizing the MySQL General Purpose SSD storage to 6 TB to improve the volume’s IOPS will not solve the problem, as the problem is not just related to storage size but also high write latency. Option B, Re-architecting the database tier to use Amazon Aurora instead of an RDS MySQL DB instance and adding read replicas would help to improve the read performance, but it won't help in reducing write latency. Option D, Using AWS X-Ray to analyze and debug application issues and adding more API servers to match the load, would help in identifying the problem and resolving it, but it will not help in reducing the load on the servers.
upvoted 3 times
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0b43291
Most Recent 6 days, 10 hours ago
Selected Answer: BC
By combining options B and C, the company can address the current performance and scalability issues while enabling future growth as more sensors are deployed. Amazon Aurora provides a scalable and high-performance relational database, while Kinesis Data Streams and Lambda offer a serverless and cost-effective solution for ingesting and processing the raw data streams. Option A may provide temporary relief by increasing IOPS, but it doesn't address the scalability and performance limitations of RDS MySQL. Option D can help identify application issues but doesn't solve the underlying database problems. Option E is not ideal as DynamoDB is a NoSQL database, and the existing application is likely designed for a relational database like MySQL or Aurora, requiring significant changes to the application code and data modeling.
upvoted 2 times
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amministrazione
2 months, 3 weeks ago
C. Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data. E. Re-architect the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance.
upvoted 1 times
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zolthar_z
4 months, 1 week ago
Selected Answer: CE
What discards B is "Add read replicas", the problem is writing the new data in the DB, adding Read replicas will increase the cost and this is not what question requests "maintain cost"
upvoted 2 times
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Helpnosense
5 months, 1 week ago
Selected Answer: BC
Write performance will be improved by switch RDS to Aurora. RDS to Aurora is smooth transition without too much on the application side. Answer E will application side not just backend DB.
upvoted 2 times
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TonytheTiger
7 months, 3 weeks ago
Selected Answer: CE
Option CE and BC. The only reason I choose E over B because said SO. Per AWS, DynamoDB is suitable for IoT ( Sensor data and log ingestion) https://docs.aws.amazon.com/whitepapers/latest/best-practices-for-migrating-from-rdbms-to-dynamodb/suitable-workloads.html
upvoted 3 times
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gofavad926
8 months, 1 week ago
Selected Answer: CE
CE, kinesis + lambda & Dynamodb
upvoted 1 times
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a54b16f
8 months, 3 weeks ago
Selected Answer: BC
Switching from RDS mysql to aurora will improve performance, by up to 10 times, which could solve the write issue. Switching from relationship database to nosql is not practical, need re-engineering whole application. plus, the performance improvement of nosql are around data read, not data write ( creating/updating indexes is a huge effort)
upvoted 2 times
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8608f25
9 months, 2 weeks ago
Selected Answer: BC
* B. Re-architect the database tier to use Amazon Aurora instead of an RDS MySQL DB instance and add read replicas. Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. Aurora provides several benefits over standard RDS MySQL, including better performance, scalability, and availability. It automatically grows storage as needed, up to 128 TB, potentially providing better write performance. Aurora also supports up to 15 read replicas with very low replication latency, improving read performance significantly and reducing the load on the primary database instance.
upvoted 2 times
8608f25
9 months, 2 weeks ago
* C. Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data. By using Amazon Kinesis Data Streams, the company can collect, process, and analyze real-time, streaming data so that it can react to new information quickly. This service allows for the ingestion of a large amount of data generated by IoT sensors. AWS Lambda can then be used to process this data in real-time, which can help to offload the work from the API servers, reducing their load. This setup can scale automatically with the number of incoming data records, providing a more efficient and cost-effective solution to handle growth.
upvoted 1 times
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ninomfr64
10 months, 2 weeks ago
Selected Answer: CE
A = does not fix permanently (who knows that 6TB is enough?) B = going from RDS to Aurora will not fix the issue C = correct D = this could work, but it is not cost efficient (more EC2 instance along the line) E = correct
upvoted 2 times
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Pupu86
1 year ago
Selected Answer: CE
The requirement is to resolve high write latency while Aurora is a good fit for structured datasets but option B has indicated read replica as a direction for resolution against a question seeking resolution in write latency. So Option B is definitely out.
upvoted 1 times
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duriselvan
1 year, 3 months ago
Amazon RDS FeaturesAmazon RDS supports multiple database engines, including Amazon Aurora, MySQL, MariaDB, Oracle, Microsoft SQL Server, and PostgreSQL.Amazon RDS allows you to scale your database instances’ storage size and performance.Amazon RDS makes it easy to set up, operate, and scale a relational database in the cloud.Amazon RDS provides a cost-effective way to manage relational databases in the cloud.DynamoDB FeaturesPrimarily, DynamoDB features flexibility, scalability, and performance. It offers high availability out of the box with no need for setup or configuration. DynamoDB automatically replicates your data across multiple Availability Zones within a Region to give you fault tolerance and high availability.
upvoted 1 times
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duriselvan
1 year, 3 months ago
c and E ans 100 %
upvoted 1 times
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rizzu2023
1 year, 3 months ago
CE https://aws.amazon.com/dynamodb/iot/
upvoted 1 times
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easytoo
1 year, 4 months ago
b-c-b-c-b-c-b-c
upvoted 1 times
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NikkyDicky
1 year, 4 months ago
Selected Answer: CE
CE for sure. classic IoT use case
upvoted 1 times
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Asds
1 year, 5 months ago
Selected Answer: BD
Rds MySQL to Aurora to scale automatically and stay relational
upvoted 1 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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