How to Run 30-Minute Windowed Streaming Analytics with Least Overhead?

DEA-C01 By islever Editorial Last updated

Automate data processing by using AWS services. Analyze data by using AWS services.

Short answer

D Amazon Managed Service for Apache Flink provides fault-tolerant time-based aggregations over 30-minute windows with less operational overhead than Lambda.

Question

A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on the incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is highly fault tolerant. Which solution will meet these requirements with the LEAST operational overhead?
  1. Use an AWS Lambda function that includes both the business and the analytics logic to perform time-based aggregations over a window of up to 30 minutes for the data in Amazon Kinesis Data Streams.
  2. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data that might occasionally contain duplicates by using multiple types of aggregations.
  3. Use an AWS Lambda function that includes both the business and the analytics logic to perform aggregations for a tumbling window of up to 30 minutes, based on the event timestamp.
  4. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data by using multiple types of aggregations to perform time-based analytics over a window of up to 30 minutes. Correct Answer

Key Takeaways

The exam tests matching a stateful streaming window requirement (30 minutes, fault tolerant, low ops) to a managed Apache Flink service; the trap is choosing Lambda because it is serverless and familiar.

This DEA-C01 question asks which AWS service should power fault-tolerant real-time analytics with time-based aggregations over a 30-minute window while minimizing operational overhead. The answer is Amazon Managed Service for Apache Flink, not Lambda, because Flink provides managed stateful windowing and Lambda is capped at 15 minutes.

Common mistake: The most common wrong choice is an AWS Lambda function (A or C), because serverless looks low-overhead, but Lambda's 15-minute maximum invocation and lack of durable window state make a 30-minute aggregation unreliable.

Expert Analysis

Why the Answer Is Correct

Amazon Managed Service for Apache Flink (formerly Kinesis Data Analytics) is designed for managed, fault-tolerant stream processing with stateful operators, including time-based windows. A 30-minute window requires the service to retain state across events and recover from failures, which Flink handles with checkpoints and managed infrastructure. Option D explicitly states time-based analytics over a window of up to 30 minutes, matching the stated requirement, while keeping operational overhead low because AWS manages the cluster. This is why D is the best fit even though B also names Managed Flink.

Why the Other Options Are Wrong

Options A and C use Lambda for the entire 30-minute window, but Lambda has a 15-minute maximum invocation timeout and is not a durable stateful stream processor for long windows. Option C's tumbling window with event timestamps is conceptually closer, but it still relies on Lambda for a 30-minute stateful aggregation and does not meet fault tolerance or low-ops requirements. Option B uses Managed Flink, but its description emphasizes duplicate handling and multiple aggregation types rather than the required 30-minute time-based window, so D is more precise. The distinction between B and D is requirement matching, not service choice.

Community Comment Notes

rralucard endorsed D by focusing on Managed Flink for "performing time-based analytics over a window of up to 30 minutes" and complex event processing. div_div made the key Lambda point: "Lambda can not be used because it max processing limit of time is 15 min" and noted Flink handles window-size aggregation. DevoteamAnalytix pointed readers to the AWS Managed Flink operators documentation for aggregation behavior, while Just_Ninja asked to "Show the Docs." harrura cautioned learners with "please don't rely on them" about bot-generated answers and encouraged opening the discussion for reasoning, which is consistent with evaluating D against the requirement rather than the vote count.

Official Reference

These links open the official vendor documentation in a new tab.

Exam Strategy

When a DEA-C01 question specifies a window longer than 15 minutes, eliminate Lambda-based answers first, then choose the managed streaming service whose wording explicitly matches the time window. Read B and D closely: both mention Managed Flink, but only D states the 30-minute time-based aggregation requirement.

Frequently Asked Questions

Why can't AWS Lambda handle the 30-minute tumbling window?

Lambda has a 15-minute maximum invocation timeout and does not maintain durable state across invocations, so a 30-minute stateful aggregation is unreliable.

Why is option B wrong when it also uses Managed Service for Apache Flink?

Option B emphasizes duplicate handling and multiple aggregation types but does not explicitly deliver the required time-based 30-minute window; option D matches that requirement directly.

More DEA-C01 FAQ →

Community Votes

D
100%

100% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 6 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 6

  1. rralucard_ 👍 7 Answered D
    D. Amazon Managed Service for Apache Flink for Time-Based Analytics over 30 Minutes: This option correctly identifies the use of Amazon Managed Service for Apache Flink for performing time-based analytics over a window of up to 30 minutes. Apache Flink is adept at handling such scenarios, providing capabilities for complex event processing, time-windowed aggregations, and maintaining state over time. This option would offer high fault tolerance and minimal operational overhead due to the managed nature of the service.
  2. div_div 👍 2 Answered D
    Lambda can not be used because it max processing limit of time is 15 min and remaining two option related to flink and using flink we can perfrom time-series and window size aggregation
  3. Linuslin 👍 2
    This link is not AWS documents but I think you guys can take a look. https://amandeep-singh-johar.medium.com/real-time-stream-processing-with-apache-flink-153992840f16
  4. harrura 👍 2
    this is crazy, the answers by bot are wrong, please don't rely on them. please care to open discussions and look for reasoning
  5. DevoteamAnalytix 👍 1 Answered D
    https://docs.aws.amazon.com/managed-flink/latest/java/how-operators.html#how-operators-agg
Show 1 more comment
  1. Just_Ninja 👍 2 Answered D
    Show the Docs

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