Which storage solution will be an ideal storage solution at the edge when the data (images and videos) is required to be stored locally at the edge until the data (images and video) is processed?
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A. B. C. D.Correct Answer: A.
Option A is CORRECT.
Azure Blob Storage on IoT Edge is useful for many scenarios including below:
-When local data storage is needed until either processing of data is done or the data is transferred to the cloud.
-If the devices are located at locations with limited connectivity.
-In scenarios when latency is to be minimized and hence the data is to be processed locally.
-In the scenarios when bandwidth costs are to be reduced and transferring huge data to the cloud is to be avoided.
Option B is INCORRECT.
Azure IoT edge stream device is an invalid choice.
Option C is INCORRECT.Apache Spark is a Parallel processing framework supporting in-memory processing for boosting big-data analytic applications performance.
Microsoft's implementation of Apache Spark in Azure is “Apache Spark in Azure HDInsight.”
Option D is INCORRECT.Azure IoT Edge parallel storage is an invalid option.
References:
When it comes to storing data at the edge, where data is generated, and processing is done locally, there are a few options available in Azure.
Azure Blob Storage on IoT Edge (Option A) is an ideal storage solution for storing data (images and videos) at the edge. This solution provides a consistent, secure, and scalable way to store unstructured data at the edge, while also being able to access and process the data remotely. Azure Blob Storage on IoT Edge can be used to store data in containers, which can then be accessed by other IoT Edge modules or sent to the cloud for further processing.
Azure IoT edge stream device (Option B) is not a storage solution but a way to capture video or audio streams from cameras or microphones and forward them to downstream modules or the cloud for processing. Therefore, it is not the ideal solution for storing data locally at the edge.
Apache Spark (Option C) is a distributed computing framework designed to process large amounts of data in parallel across a cluster of computers. While Apache Spark can be used to process data at the edge, it is not an ideal storage solution for storing data (images and videos) locally at the edge.
Azure IoT Edge parallel storage (Option D) is a preview feature that allows you to store data locally at the edge in a distributed and fault-tolerant manner. It provides a way to replicate data across multiple devices, which can help to ensure data availability and reliability. However, this feature is not yet generally available and may not be the best option for all use cases.
In summary, Azure Blob Storage on IoT Edge is the ideal storage solution for storing data (images and videos) locally at the edge until the data is processed. It provides a reliable and scalable way to store unstructured data at the edge, which can then be accessed by other modules or sent to the cloud for further processing.