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Amazon OA2 work simulation

Let’s have a look at the recent Amazon OA2 work simulation questions and Amazon OA work style questions.

Amazon OA2 Work Simulation Question 1

Rate the effectiveness of each action below as if it were your next step.

Amazon OA2 work simulation question 1
Reference answer

Create a proof of concept system to test.

  • Very Effective

Clarify requirements with stakeholders.

  • Extremely Effective

Write fundamental library code.

  • Moderately Effective

Create a database schema.

  • Very Effective

Schedule a meeting with the design team.

  • Slightly Effective

Amazon OA2 Work Simulation Question 2

You and other engineers on the team are tasked with developing a real-time voting service for a new Amazon Prime singing show – Amazon Voice. The final show is scheduled to take place 5 weeks from now. At the end of the show, there will be a 5-minute voting block where all votes are tabulated.

From: Ming, Product ManagerSubject: Amazon Voice – Meeting Notes
Hey team,
Thanks again for joining the meeting this morning. Based on our discussion, the system needs to operate under the following conditions:
– The voting result is updated every second within the 5-minute voting period.
– Customers are allowed to review and update their votes until the voting is closed.
– The system needs to handle millions of customers voting at the same time during the 5-minute voting block.
– The system needs to remain available during the voting period.
Ming

Question

Below are vote storage strategies you could use given the requirements from the product manager’s email. Rate the effectiveness of each strategy.

Amazon OA2 work simulation question 2
Reference answer

Key-value database – used for storing key-value pairs in a distributed manner (e.g., Amazon DynamoDB, Redis, or Cassandra).

  • Extremely Effective
  • Key-value databases are highly effective for real-time applications due to their low-latency and high-throughput capabilities. They can easily handle millions of concurrent votes and provide quick updates.

Document database – used for storing JSON documents (e.g., MongoDB, Azure CosmosDB, CouchDB).

  • Very Effective
  • Document databases are flexible and can handle complex data structures. They are also scalable and can handle high volumes of data, making them suitable for this use case.

Graph database – used for storing data with complex relationships (e.g., Amazon Neptune, Neo4J, or Tiger DB).

  • Slightly Effective
  • Graph databases are designed for managing complex relationships and are not typically optimized for high-throughput, low-latency operations needed for real-time voting.

Ledger database – store using an append-only record journal (e.g., Amazon QLDB).

  • Moderately Effective
  • Ledger databases provide an immutable record of all transactions, which is beneficial for auditability but might introduce unnecessary complexity and latency for real-time vote updates.

Distributed data processing system – Apache Hadoop/Spark to process tracking data.

  • Slightly Effective
  • Distributed data processing systems are excellent for batch processing large datasets but are not designed for real-time processing required in a voting scenario. They would add significant latency.

Amazon OA2 Work Simulation Question 3

Email 1:
From:
New Project Alert
Subject: Overview – Inventory Management System

Your team is building a new inventory management system that is going to be offered as a SaaS product (Software-as-a-Service).
Select the NEXT button to start the new project.


Email 2:
Hi, The product owner has finalized requirements for the inventory management system. We need to architect a system to support these requirements. I’m hoping you can help with this effort.

Rate the effectiveness of each action below as if it were your next step.

Amazon OA2 work simulation question 3
Reference answer

Set up time to discuss the requirements with the product owner.

  • Extremely Effective
  • Discussing the requirements ensures a clear understanding of the project scope and objectives, which is crucial for effective system design.

Sketch together a high-level diagram.

  • Very Effective
  • A high-level diagram helps visualize the system’s structure and components, providing a foundation for further detailed design and discussion.

Set up an operational dashboard of metrics, alarms, and documentation.

  • Moderately Effective
  • While important for the operational phase, setting up a dashboard is not a priority at the initial architecture stage.

Develop a proof of concept with your team and senior engineers to test the key system constructs.

  • Very Effective
  • A proof of concept can validate critical aspects of the system, identify potential issues early, and guide further development.

Prepare and host a system-level architecture review.

  • Moderately Effective
  • An architecture review is valuable but should follow the initial discussions and conceptual designs to ensure meaningful input and feedback.

Question 4

Email:
Your team is building a new inventory management system that is going to be offered as a SaaS product (Software-as-a-Service).
Kate (Software Development Engineer):
Hey – I’ve been asked to develop a solution to provide image thumbnails of inventory items. I’ve identified a few potential storage options, but I was hoping to hear your thoughts on each.

Below are image storage options you could use. Rate the effectiveness of each option.

Amazon OA2 Work Simulation Question 4
Reference answer

Flat/file store.

  • Slightly Effective
  • A flat/file store can be simple to implement but lacks scalability and performance features needed for a SaaS product.

Relational database.

  • Moderately Effective
  • Relational databases can store images as BLOBs, but this approach can lead to performance issues and isn’t as scalable as other options for handling large volumes of image data.

Key-value data store.

  • Very Effective
  • Key-value stores like Amazon DynamoDB or Redis are well-suited for storing images efficiently and retrieving them quickly, making them a good choice for this use case.

Elastic search.

  • Slightly Effective
  • Elastic search is optimized for text search and analytics rather than image storage, so it isn’t the most effective option for storing image thumbnails.

Cloud file store.

  • Extremely Effective
  • Cloud file stores like Amazon S3 or Google Cloud Storage are highly scalable, cost-effective, and designed for storing and serving large volumes of image files. They are typically the best option for this use case.

Question 5

Email 1:
From:
New Project AlertSubject: Overview – Traffic Video Service
Amazon is building a traffic video service for a large metro environment. Individual traffic cameras will send updates to the central service based on physical capabilities, limitations, and configurations. Due to variable volume, message queuing is planned, so it’s necessary to design and support an appropriate message format.
Select the NEXT button to start the new project.


Email 2:
From:
Na’imah, Software Development ManagerSubject: Welcome – system requirements
Hey,I’m happy you have joined us for this effort. Our team is responsible for developing the first version of the product for the messaging system. Here are the requirements from the product manager:
– A versioning system for message formats.
– Binary data de/serialization system for individual components within messages.
– Support for messages with different purposes.
– Message timestamps and checksums.
I am eager to hear the actions you think we should take to meet these requirements.

Below are actions you could take to meet the requirements. Rate the priority of each action.

Amazon OA2 Work Simulation Question 5
Reference answer

Identify dashboards and graphs to assess system performance.

  • Low Priority
  • While monitoring is important, it is not the immediate priority when defining the message format and system capabilities.

Determine how the queue is configured to handle the exceptions.

  • Medium Priority
  • Handling exceptions in the message queue is crucial for reliability but should follow defining the core message format and system requirements.

Research industry standard message formats.

  • Essential
  • Researching industry-standard message formats is critical to ensure the messaging system is designed using best practices and can interoperate with other systems.

List the purposes messages will serve.

  • High Priority
  • Identifying the different purposes of messages is essential to design a flexible and effective message format that meets all the system requirements.

Question 6

Email:
Amazon is building a traffic video service for a large metro environment. Individual traffic cameras will send updates to the central service based on physical capabilities, limitations, and configurations. Due to variable volume, message queuing is planned, so it’s necessary to design and support an appropriate message format.


Anne (Principal Software Development Engineer):
Hey – some of the data these traffic cameras produce can be quite large, and the customer wants to transmit these messages to the service. I have a few ideas on how we could do this, but I’m interested in hearing your thoughts.

Below are approaches you could take to transmit large messages to the service. Rate the effectiveness of each approach.

Amazon OA2 Work Simulation 6
Reference answer

Use different message types to transmit the request metadata and large data.

  • Very Effective
  • This approach can efficiently separate metadata from large data, allowing for better handling and processing of each part.

Fragment the large data into multiple messages.

  • Extremely Effective
  • Fragmenting large data into smaller, manageable chunks ensures that the system can handle large volumes without overwhelming the message queue. This is a well-known technique used in many messaging systems.

Develop a streaming protocol for large messages.

  • Extremely Effective
  • A streaming protocol can efficiently handle large messages by transmitting data in a continuous flow, which is particularly effective for real-time systems like traffic video services.

Develop a cadence to send large messages during low volume time.

  • Moderately Effective
  • This approach can be effective in reducing the load during peak times, but it depends on the predictability of traffic patterns and may not always be feasible in real-time systems.

Physically download large messages from each location.

  • Not at all Effective
  • Physically downloading data is impractical and inefficient for a real-time service, as it introduces significant delays and logistical challenges.

Question 7

Email:
Amazon is building a traffic video service for a large metro environment. Individual traffic cameras will send updates to the central service based on physical capabilities, limitations, and configurations. Due to variable volume, message queuing is planned, so it’s necessary to design and support an appropriate message format.


From: Robert, Software Development Engineer
Subject: Service IssueHey there
We were just notified that the service experienced an issue where messages were dropped. We need to monitor for message drops and make our system more resilient in the future. I’m interested in hearing your thoughts on how we can do this.
Robert

Below are options that could make the system more resilient. Rate the effectiveness of each option.

Amazon OA2 Work Simulation 7
Reference answer

Add a dead letter queue to handle failure messages.

  • Extremely Effective
  • A dead letter queue can capture and store messages that could not be processed, allowing for troubleshooting and reprocessing without data loss.

Review the retry configuration from the queue.

  • Very Effective
  • Proper retry configuration can significantly reduce message drops by attempting to reprocess messages before they are permanently discarded.

Increase message storage time as a redundancy measure.

  • Moderately Effective
  • Increasing storage time can help ensure that messages are not prematurely deleted, providing more time for retrying message processing. However, it doesn’t address the root cause of message drops.

Use a time-to-live configuration to store the successfully processed messages.

  • Slightly Effective
  • While a time-to-live configuration can help manage storage of successfully processed messages, it doesn’t directly address message drops or resilience.

Use another queue to store the successfully processed messages.

  • Slightly Effective
  • Storing successfully processed messages in another queue helps with organization but doesn’t directly contribute to preventing message drops or improving resilience.

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