Real-Time Visibility and Analysis with Time Series Insights (TSI)

Achieving Real-Time Visibility and On-the-Fly Analysis with Time Series Insights (TSI)

Question

As part of your industrial IoT solution, you have 10 wind turbines equipped with many sensors.

All these sensors send thousands of telemetry data to an IoT hub.

You need to build a solution that can provide real-time visibility and on-the-fly analysis of key data streams.

You decide to use Time Series Insights (TSI)

While creating the TSI environment, what should you configure to achieve your goal?

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Correct Answer: B.

Option A is incorrect because the consumer group must be created in the IoT Hub and the event source must be configured in TSI.

Option B is CORRECT because you need to have a consumer group in your IoT Hub, exclusively for the TSI environment, which can use this as an event source.

Because of the requirement for real-time analysis, enabling warm storage is recommended.

Although it is optional, for this scenario adding cold storage is recommended.

Option C is incorrect because you need to use IoT Hub's built-in endpoints to create a consumer group that TSI can use for ingesting data.

Custom endpoints are not available for this purpose.

Option D is incorrect because due to the requirement for on-the-fly analysis, enabling warm storage is recommended.

Although it is optional, for this scenario adding cold storage is recommended.

Diagram:

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° Series Insights Cold Store

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Event Hubs

Warm Store

Reference:

The correct answer is option B: IoT Hub consumer group; TSI event source; warm storage, cold storage.

Explanation:

Time Series Insights (TSI) is a fully managed analytics, storage, and visualization service for managing time-series data in the cloud. It allows you to analyze and visualize large amounts of time-stamped data from various sources in real-time.

In this scenario, you have 10 wind turbines with many sensors sending thousands of telemetry data to an IoT hub. To achieve real-time visibility and on-the-fly analysis of key data streams, you can use TSI to analyze and visualize the data.

To create a TSI environment, you need to configure the following:

  1. IoT Hub consumer group: This is a named view of the data stream in the IoT hub that allows you to read the data from the IoT hub. A consumer group allows multiple applications to consume data from the same IoT hub without interfering with each other.

  2. TSI event source: An event source is a stream of data from a specific source, such as an IoT hub, that TSI can use to analyze and visualize time-series data. In this case, you need to configure the TSI event source to read data from the IoT hub using the consumer group you created earlier.

  3. Warm storage: Warm storage is a type of storage that allows you to store and query data that is frequently accessed. It provides fast access to data that is less than 30 days old. In this scenario, you need to configure warm storage to store the telemetry data from the wind turbines for real-time analysis.

  4. Cold storage: Cold storage is a type of storage that allows you to store and query data that is infrequently accessed. It provides a cost-effective way to store data that is more than 30 days old. In this scenario, you need to configure cold storage to store the telemetry data from the wind turbines for long-term analysis.

Option A is incorrect because it suggests using an IoT Hub event source instead of an IoT Hub consumer group. An event source is a stream of data from a specific source, such as an IoT hub, that TSI can use to analyze and visualize time-series data. However, it is recommended to use a consumer group instead of an event source for reading data from the IoT hub.

Option C is incorrect because it suggests using a custom endpoint instead of an IoT Hub consumer group. A custom endpoint is a webhook that receives a copy of the telemetry data from the IoT hub. However, it is recommended to use a consumer group instead of a custom endpoint for reading data from the IoT hub.

Option D is incorrect because it suggests using cold storage only. While cold storage is required for long-term storage and analysis of the telemetry data, warm storage is also required for real-time analysis of the data.