Low Latency Real-Time Sensor Data Visualization with Flink and Grafana

DEA-C01 By islever Editorial Last updated

Automate data processing by using AWS services. Maintain and monitor data pipelines.

Short answer

A Use Amazon Managed Service for Apache Flink to process sensor data, write to Amazon Timestream, and create a Grafana dashboard for lowest latency visualization.

Question

A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket.
The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.
Which solution will meet these requirements with the LOWEST latency?
  1. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard. Correct Answer
  2. Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard.
  3. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Create a new Data Firehose delivery stream to publish data directly to an Amazon Timestream database. Use the Timestream database as a source to create an Amazon QuickSight dashboard.
  4. Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.

Key Takeaways

The main trap is prioritizing ingestion simplicity (Firehose) over visualization performance; QuickSight is too slow for real-time operational dashboards compared to Grafana.

This page explains why Option A is the correct answer for achieving the lowest latency real-time sensor data visualization using Amazon Managed Service for Apache Flink, Amazon Timestream, and Grafana.

Common mistake: Candidates often choose Option C because Data Firehose offers direct, simple ingestion to Timestream. However, they overlook that QuickSight cannot provide the sub-second refresh rates required for real-time factory floor monitoring.

Expert Analysis

Latency vs. Visualization Tooling The question demands the solution with the LOWEST latency for a real-time view. While Option C appears faster in data delivery because it uses Data Firehose to write directly to Amazon Timestream (skipping the Flink-to-Timestream connector overhead), it relies on Amazon QuickSight for visualization. QuickSight is primarily a business intelligence tool optimized for batch or near-real-time dashboards, not sub-second streaming telemetry. It introduces significant latency in refreshing visualizations against streaming sources.

Real-Time Dashboard Requirements Option A utilizes Amazon Managed Service for Apache Flink to process the stream and then writes to Amazon Timestream via a connector. Although this adds a processing step compared to Firehose, it pairs Timestream with Grafana. Grafana is specifically designed for high-frequency, low-latency operational monitoring and can query time-series databases like Timestream with minimal delay. For a large screen in a factory floor requiring immediate visibility, Grafana's refresh capabilities are far superior to QuickSight's.

Eliminating Other Options Option B relies on S3 notifications triggering Lambda, which is inherently asynchronous and high-latency, making it unsuitable for real-time requirements. Option D uses AWS Glue bookmarks, which are designed for batch ETL jobs, not real-time streaming.

Conclusion The trade-off here is between ingestion speed (C) and visualization latency (A). In exam doctrine, "real-time view" on a "large screen" implies an operational dashboard where visualization refresh rate matters most. Grafana (Options A/D) is the correct choice over QuickSight (Options B/C) for this use case. Between A and D, A provides the necessary real-time processing via Flink, whereas D is batch-oriented.

Official Reference

https://docs.aws.amazon.com/timestream/latest/developerguide/WhatIs.html

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

Exam Strategy

When questions specify 'real-time' visualization on operational screens, prioritize tools built for streaming telemetry like Grafana over BI tools like QuickSight. Evaluate the entire pipeline, including the final render/refresh layer, not just the data ingestion mechanism.

Frequently Asked Questions

Why is QuickSight not suitable for real-time factory floor monitoring?

QuickSight is optimized for business intelligence and batch analysis. Its dashboard refresh rates are generally higher latency than dedicated time-series visualization tools like Grafana, which can update frequently for operational monitoring.

Does using Flink add too much latency compared to Data Firehose?

While Data Firehose is simpler, the latency introduced by Flink's processing is negligible compared to the visualization latency of QuickSight. The end-to-end user experience is faster with Grafana's rapid refresh cycles.

More DEA-C01 FAQ →

Community Votes

A
90%
C
10%

90% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 21 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 21

  1. fceb2c1 👍 14 Answered A
    https://aws.amazon.com/blogs/database/near-real-time-processing-with-amazon-kinesis-amazon-timestream-and-grafana/ Look at the architecture diagram
  2. milofficial 👍 9 Answered A
    real time -> no Quicksight. And bookmarks to read sensor data real time is just as stupid as the flat earth theory. A it is.
  3. deepcloud 👍 8 Answered A
    Firehose cannot use Timestream as destination. Answer is A
  4. Adrifersilva 👍 5 Answered A
    Grafana: Real-time Performance: Grafana is known for its excellent real-time data visualization capabilities. It's often used for operational dashboards that require frequent updates. Integration: Works well with time-series databases and streaming data sources. [2]
  5. teo2157 👍 4 Answered A
    Amazon QuickSight is primarily designed for business intelligence and data visualization, and it can provide near real-time views depending on the data refresh rate. However, it is not typically used for real-time streaming data visualization with very low latency. For real-time dashboards with very low latency, services like Grafana are more suitable. You can use Amazon Managed Grafana to setup the dashboard so you're using an AWS service which is always preferible on these exams.
Show 16 more comments
  1. certplan 👍 2
    C. - Processing Sensor Data with Amazon Flink: Similar to option A, this approach uses Amazon Managed Service for Apache Flink to process sensor data, providing real-time analytics or transformation capabilities. - Data Firehose Delivery Stream to Timestream: Sets up a new Amazon Data Firehose delivery stream to publish processed data directly to Amazon Timestream. Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as data lakes, databases, and analytics services. - Timestream Database as a Source for QuickSight Dashboard: Similar to option B, the data stored in Amazon Timestream serves as the data source for creating an Amazon QuickSight dashboard.
  2. TonyStark0122 👍 2
    A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard. Explanation: Amazon Managed Service for Apache Flink provides real-time stream processing capabilities, which can process sensor data with low latency. By using Apache Flink connectors, the processed data can be efficiently written to Amazon Timestream, which is optimized for time-series data storage and querying.
  3. jyrajan69 👍 2
    Based on this it should be C, why use an open source app when you can an AWS Service https://community.amazonquicksight.com/t/real-time-data-visualization-capabilities-of-amazon-quicksight/24007
  4. certplan 👍 1
    Considerations: Option A utilizes Amazon Managed Service for Apache Flink to process sensor data and then writes the processed data to Amazon Timestream. From there, the Timestream database serves as a source to create a Grafana dashboard. Thus the data goes through Apache Flink for processing, then to Timestream, and finally to Grafana. "Each additional step introduces potential latency". Option C processes sensor data using Amazon Managed Service for Apache Flink and then publishes data directly to Amazon Timestream via a Data Firehose delivery stream. Finally, it uses Timestream as a source to create an Amazon QuickSight dashboard. So, in terms of latency, both options involve processing data in real-time using Apache Flink. However, Option C has a more direct data flow by publishing data directly to Timestream, potentially reducing latency compared to Option A, where the data has to go through an additional step of writing to Timestream.
  5. certplan 👍 1
    A. - Processing Sensor Data: Utilizes Amazon Managed Service for Apache Flink, a fully managed service for real-time data processing. This service is used to process the sensor data, which likely involves real-time analysis or transformation of incoming data streams. - Connector for Apache Flink to Amazon Timestream: Integrates a connector for Apache Flink to write processed data into Amazon Timestream, a fully managed time-series database. Timestream is optimized for IoT and time-series data. - Timestream Database as a Source for Grafana Dashboard: The data stored in Timestream serves as the data source for creating a Grafana dashboard. Grafana is a popular open-source analytics and monitoring platform that visualizes time-series data.
  6. samadal 👍 1
    Option A is for processing data in Flink and then sending it to Timestream. This is advantageous when complex data processing is required in Flink, but the processing step where complex analytics are processed can handle additional latency. Option C performs data processing in Flink, sends the data directly to Timestream without any additional steps, and provides dashboards via QuickSight. Since data can be started immediately after arriving in Timestream, latency is likely to be higher. Therefore, option C is preferable because it can handle latency by performing data processing, publishing data directly to Timestream, and provides fast dashboards using QuickSight.
  7. certplan 👍 1
    Option A: - Involves additional steps: Option A requires writing data to Amazon Timestream after processing with Apache Flink, potentially introducing additional latency compared to a more direct approach like Option C. - Grafana integration: While Grafana is a powerful visualization tool, setting up and configuring Grafana dashboards might require additional effort compared to using Amazon QuickSight, which offers more straightforward integration with AWS services like Amazon Timestream.
  8. V0811 👍 1
    No! :-) Because: The company needs to display a REAL-TIME view of operational efficiency on a large screen in the manufacturing facility. So it's for sure C
  9. ambikamma 👍 1 Answered A
    Use Managed Apache Flink to process Kinesis streams in real time and write to Timestream. Timestream + Grafana provides the lowest-latency live dashboard.
  10. Just_Ninja 👍 1
    The Question is: Which solution will meet these requirements with the LOWEST latency? So just A can be the right answer "lowest latency!!!!"
  11. V0811 👍 1 Answered C
    Because: The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.
  12. LanoraMoe 👍 1
    I go with Option A. Kinesis Data Firehose can connect to 3 AWS destinations so far S3, Redshift and OpenSearch.
  13. Tiger4Code 👍 1 Answered A
    A: Kinesis data stream --> kinesis data analytics (Flink) --> Timestream --> Quicksight/Graphana
  14. Udyan 👍 1
    V0811 - and new firehose, ofc decrease latency, khomon man
  15. Deno_Dennis 👍 1 Answered A
    A is correct.
  16. Scotty_Nguyen 👍 1 Answered A
    A is correct

Reader comments & corrections

No reader corrections yet — spotted an error or have a note? Share it below.

Log in to comment, report an error, or add a note about this question.

Amazon Redshift Compound Sort Key Query Optimization

S-grade

Secure Redshift Spectrum Access with VPC Endpoints

S-grade

Least Operational Overhead for Kinesis to Redshift Ingestion

S-grade

Athena Federated Query for Multi-Source Iceberg Pipelines

S-grade

Practice All DEA-C01 Questions

Access 100 questions with complete answers and detailed explanations.

View Full DEA-C01 Practice Test →

← Back to DEA-C01 Study Guide