Salesforce Exam Heroku Architect Topic 1 Question 20 Discussion

Actual exam question for Salesforce's Heroku Architect exam

Question #: 20
Topic #: 1

Universal Containers (UC)uses Apache Kafka on Heroku to stream shipment inventory data in real time throughout the world. A Kafka topic is used to send messages with updates on the shipping container GPS coordinates as they are in transit. UC is using a Heroku Kafka basic-0 plan.The topic was provisioned with 8 partitions, 1 week of retention, and no compaction. The keys for the events are being assigned by Heroku Kafka, which means that they will be randomly distributed between the partitions.

UC has a single-dyno consumer application that persists the data to their Enterprise Data Warehouse (EDW). Recently, they've been noticing data loss in the EDW.

What should an Architect with Kafka experience recommend?

AEnable compaction on the topic to drop older messages, which will drop older messages with the same key.

BUpgrade to a larger Apache Kafka for Heroku plan, which has greater data capacity.

CUse Heroku Redis to store message receipt information to account for 'at-least' once delivery, which will guarantee that messagesare never processed more than once. Scale up the consumer dynos to match the number of partitions so that there is one process for each partition.

Show Suggested Answer

Suggested Answer: D

by Rodolfo at Jul 05, 2023, 11:27 AM

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Sang

2 months ago

I like how C tackles the problem from multiple angles - the Redis store and the scaled-up consumers. That's a more robust solution.

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Lore

2 days ago

Agreed, C seems like the most comprehensive solution to prevent data loss.

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Rossana

4 days ago

I think C is the best option here. It covers all the bases.

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Junita

6 days ago

B) Upgrade to a larger Apache Kafka for Heroku plan, which has greater data capacity.

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Barabara

19 days ago

A) Enable compaction on the topic to drop older messages, which will drop older messages with the same key.

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Nan

1 months ago

C) Use Heroku Redis to store message receipt information to account for 'at-least' once delivery, which will guarantee that messages are never processed more than once. Scale up the consumer dynos to match the number of partitions so that there is one process for each partition.

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Zoila

2 months ago

Compaction might help with older messages, but it won't address the data loss issue. C is the best option to guarantee message delivery.

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Stefanie

10 days ago

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Argelia

13 days ago

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Howard

2 months ago

Option B seems like overkill. Upgrading the Kafka plan is not necessary if the issue is with the consumer application.

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Kenneth

6 days ago

Option B seems like overkill. Upgrading the Kafka plan is not necessary if the issue is with the consumer application.

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Leonida

11 days ago

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Lashawn

13 days ago

A) Enable compaction on the topic to drop older messages, which will drop older messages with the same key.

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Leoma

14 days ago

Option B seems like overkill. Upgrading the Kafka plan is not necessary if the issue is with the consumer application.

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Lashanda

22 days ago

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Whitley

1 months ago

A) Enable compaction on the topic to drop older messages, which will drop older messages with the same key.

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Amina

2 months ago

I think the correct answer is C. Using Heroku Redis to store message receipt information and scaling up the consumer dynos will help ensure at-least once delivery and prevent data loss.

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