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Difficulty: HardData Integration and Analytical Storage

A manufacturing enterprise is designing an Azure data platform to collect and analyze telemetry from industrial wind turbines. The turbines emit continuous sensor readings totaling 20,00020,000 events per second with an ingestion volume of 3 GB3\text{ GB} per minute. The raw data must be preserved indefinitely in a cost-effective storage account that provides resilience against a datacenter outage in the primary region. Business analysts require the ability to run ad-hoc, exploratory SQL queries on the raw turbine data. These queries are executed sporadically, and a query latency of up to 45 seconds45\text{ seconds} is acceptable. Which data integration and analytical storage architecture should you recommend to meet the requirements while minimizing cost and operational overhead?

  1. Configure Azure Event Hubs with the Capture feature enabled to write the streaming telemetry to an Azure Data Lake Storage Gen2 account configured with Geo-Redundant Storage (GRS). Query the captured data using an Azure Synapse Analytics serverless SQL pool.Answer
  2. B
    Configure Azure Event Hubs to stream data to Azure Stream Analytics, which writes to an Azure Data Lake Storage Gen2 account configured with Locally Redundant Storage (LRS). Query the data using an Azure Synapse Analytics serverless SQL pool.
  3. C
    Configure Azure Event Hubs with the Capture feature enabled to write the streaming telemetry to an Azure Data Lake Storage Gen2 account configured with Geo-Redundant Storage (GRS). Provision an Azure Synapse Analytics dedicated SQL pool to load and query the telemetry data.
  4. D
    Configure Azure Event Hubs with the Capture feature enabled to write the streaming telemetry to an Azure Data Lake Storage Gen2 account. Generate Shared Access Signature (SAS) tokens with a five-year expiration to grant the query tools direct access to the files.

Answer

Configure Azure Event Hubs with the Capture feature enabled to write the streaming telemetry to an Azure Data Lake Storage Gen2 account configured with Geo-Redundant Storage (GRS), and query the captured data using an Azure Synapse Analytics serverless SQL pool.
The configuration of Azure Event Hubs with the Capture feature, Geo-Redundant Storage (GRS) for Azure Data Lake Storage Gen2, and Azure Synapse Analytics serverless SQL pools meets all criteria. Event Hubs Capture handles the ingestion of 20,00020,000 events per second (3 GB/min3\text{ GB/min}) with minimal operational effort. GRS ensures that the historical telemetry is preserved even during a primary region outage. The serverless SQL pool provides a cost-effective, on-demand query engine for sporadic ad-hoc queries, charging only for the data processed, which avoids paying for idle compute resources.

Step-by-Step Solution

1
Determine the ingestion mechanism.
Azure Event Hubs Capture is selected.
It automatically captures streaming data from Event Hubs and writes it to Azure Data Lake Storage Gen2 with minimal configuration and zero compute management overhead.
2
Select the storage redundancy tier.
Geo-Redundant Storage (GRS) is selected.
GRS replicates data to a secondary region, providing resilience against primary region outages, which satisfies the regional disaster recovery requirement.
3
Select the query engine for ad-hoc analysis.
Azure Synapse Analytics serverless SQL pool is selected.
It allows querying data directly in the data lake using T-SQL with a pay-per-query model, which is highly cost-effective and reduces operational overhead for sporadic queries.

Key Concept

Designing a cost-effective real-time ingestion and ad-hoc analytical query architecture using serverless pools and redundant storage.
Estimated Time:2m 0s
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Topics

Data Integration and Analytical Storage

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