Real-Time Network Outage Detection with Kinesis and Flink

DEA-C01 By islever Editorial Last updated

Automate data processing by using AWS services.

Short answer

B Use Amazon Kinesis Data Streams and Amazon Managed Service for Apache Flink to process usage data in real time for immediate drop detection.

Question

A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance. Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions. Which solution will meet this requirement with the LEAST latency?
  1. Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.
  2. Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage. Correct Answer
  3. Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.
  4. Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

Key Takeaways

The question tests real-time stream processing; the common trap is confusing database activity streams (auditing) with application data analytics, leading candidates to choose Option D.

This page analyzes the optimal architecture for detecting sudden network usage drops with the least latency using Amazon Kinesis Data Analytics (Flink). It establishes that streaming analytics is superior to polling or database auditing for real-time event detection.

Common mistake: Many learners select Option D because they assume 'Database Activity Streams' implies real-time monitoring of data changes, but it is designed for security auditing, not business logic analysis.

Expert Analysis

Why the Answer Is Correct

Option B is the correct answer because Amazon Kinesis Data Streams combined with Amazon Managed Service for Apache Flink provides a true real-time processing pipeline. The application publishes data to Kinesis, and Flink continuously processes the stream, allowing for immediate detection of anomalies like sudden usage drops without the latency introduced by periodic polling or batch storage.

Why the Other Options Are Wrong

Option A introduces unnecessary latency by querying Aurora every minute via EventBridge, which fails the 'least latency' requirement. Option C replaces Aurora with DynamoDB but still relies on Lambda polling every minute, which is not real-time. Option D leverages Database Activity Streams, which capture SQL statements for audit compliance, not application-level metrics, making it unsuitable for detecting network usage patterns.

Community Comment Notes

The community largely agrees with Option B, citing its efficiency in analyzing data before it hits the database. Some users initially considered Option D, believing it offered lower latency, but were corrected that it serves an auditing purpose rather than analytical needs. One commenter noted that Option B 'reduces latency because it is analyze before the data even gets to the Aurora DB,' highlighting the architectural advantage of stream processing.

Official Reference

https://docs.aws.amazon.com/kinesis/data-analytics/latest/dev/what-is.html

This link opens the official vendor documentation in a new tab.

Exam Strategy

Always distinguish between 'streaming data' (Kinesis/Flink) and 'database activity' (Audit Logs). When 'least latency' and 'real-time' are keywords, look for continuous stream processing solutions rather than scheduled polls or historical queries.

Frequently Asked Questions

Why isn't Aurora Database Activity Streams suitable for this?

Activity Streams capture SQL operations for security auditing, not business metrics like network usage volumes.

Does Lambda polling meet the least latency requirement?

No, polling every minute introduces significant delay compared to the near-instant processing of a Flink stream.

More DEA-C01 FAQ →

Community Votes

B
77%
D
23%

77% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 8 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 8

  1. Ja13 👍 3 Answered B
    The best solution to identify sudden drops in network usage with the least latency is: B. Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage. This approach ensures real-time processing with minimal latency and allows immediate detection and response to network usage drops.
  2. Adrifersilva 👍 3 Answered B
    Regarding D, Database Activity Streams in Aurora are primarily for auditing databases actities, not for analyzing app data.
  3. HunkyBunky 👍 3 Answered D
    I guess D. The question is which solution helps to identitfy sudden drops to take immediate actions
  4. sdas1 👍 2
    Option D https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/DBActivityStreams.Overview.html In Amazon Aurora, you start a database activity stream at the cluster level. All DB instances within your cluster have database activity streams enabled. Your Aurora DB cluster pushes activities to an Amazon Kinesis data stream in near real time. The Kinesis stream is created automatically. From Kinesis, you can configure AWS services such as Amazon Data Firehose and AWS Lambda to consume the stream and store the data.
  5. sdas1 👍 2
    Option D is the optimal choice because it leverages Aurora's Database Activity Streams to enable real-time monitoring and immediate response to changes in network usage data. This approach ensures the least latency in detecting and responding to sudden drops in network usage, crucial for the telecommunications company to take immediate remedial actions during network outages.
Show 3 more comments
  1. portland 👍 2 Answered B
    reduces latency because it is analyze before the data even gets to the Aurora DB
  2. antun3ra 👍 2 Answered B
    B is the correct answer
  3. Bmaster 👍 2
    B is good

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