Microsoft AZ-220 - Questions & Answers

IoT Hub is one of the first Azure services to support distributed tracing. As more Azure services support distributed tracing, you'll be able trace IoT messages throughout the Azure services involved in your solution.

Note:
Enabling distributed tracing for IoT Hub gives you the ability to: Precisely monitor the flow of each message through IoT Hub using trace context. This trace context includes correlation IDs that allow you to correlate events from one component with events from another component. It can be applied for a subset or all IoT device messages using device twin.
Automatically log the trace context to Azure Monitor diagnostic logs.
Measure and understand message flow and latency from devices to IoT Hub and routing endpoints.
Start considering how you want to implement distributed tracing for the non-Azure services in your IoT solution.

References:
https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-distributed-tracing

Scenario: You discover connectivity issues between the IoT gateway devices and iothub1, which cause IoT devices to lose connectivity and messages.

To log device connection events and errors, turn on diagnostics for IoT Hub. We recommend turning on these logs as early as possible, because if diagnostic logs aren't enabled, when device disconnects occur, you won't have any information to troubleshoot the problem with.
Step 1:
Sign in to the Azure portal.
Browse to your IoT hub.
Select Diagnostics settings.
Select Turn on diagnostics.
Enable Connections logs to be collected.
For easier analysis, turn on Send to Log Analytics (see pricing).

Step 2:
Set up alerts for device disconnect at scale

To get alerts when devices disconnect, configure alerts on the Connected devices (preview) metric.

References:
https://docs.microsoft.com/bs-cyrl-ba/azure/iot-hub/iot-hub-troubleshoot-connectivity

Create a dedicated consumer group in the IoT hub for the Time Series Insights environment to consume from. Each Time Series Insights event source must have its own dedicated consumer group that isn't shared with any other consumer. If multiple readers consume events from the same consumer group, all readers are likely to exhibit failures.
References:
https://docs.microsoft.com/en-us/azure/time-series-insights/time-series-insights-how-toadd-an-event-source-iothub

Scenario: You discover connectivity issues between the IoT gateway devices and iothub1, which cause IoT devices to lose connectivity and messages.

To synchronize state information between a device and an IoT hub, you use device twins. A device twin is a JSON document, associated with a specific device, and stored by IoT Hub in the cloud where you can query them. A device twin contains desired properties, reported properties, and tags.

References:
https://docs.microsoft.com/en-us/azure/iot-hub/tutorial-device-twins

Scenario: You plan to use a 30-second period to calculate the average temperature reading of the sensors.

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

Incorrect Answers:
A: Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap, so events can belong to more than one Hopping window result set.

References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

When you create a Time Series Insights Preview pay-as-you-go (PAYG) SKU environment, you create two Azure resources: An Azure Storage general-purpose V1 blob account for cold data storage.
An Azure Time Series Insights Preview environment that can be configured for warm data storage.

References:
https://docs.microsoft.com/en-us/azure/time-series-insights/time-series-insights-update-storage-ingress