A manufacturing enterprise operates globally and needs to design a data platform on Azure … — Microsoft Azure Solutions Architect (AZ-305)

A manufacturing enterprise operates globally and needs to design a data platform on Azure to process and analyze telemetry data from industrial IoT sensors. The platform must meet the following technical specifications:
- Ingestion rate: A continuous stream of $15{}000$ events per second.
- Volume: A total storage capacity of $200\text{ TB}$ of historical sensor data stored in Parquet format.
- Query patterns: Data analysts execute ad-hoc, exploratory SQL queries on the historical Parquet files approximately $8$ to $12$ times per week. The query latency must be under $45\text{ seconds}$ .
- Resilience: The storage solution must remain available and readable in a secondary region in the event of a primary region outage.
- Cost and Operations: You must minimize operational overhead and ensure you do not pay for idle compute resources.

Which combination of Azure compute and storage configurations should you recommend?

A
Azure Synapse Analytics dedicated SQL pools querying an Azure Data Lake Storage Gen2 account configured with Read-Access Geo-Redundant Storage (RA-GRS)
B
Azure Synapse Analytics serverless SQL pools querying an Azure Data Lake Storage Gen2 account configured with Locally Redundant Storage (LRS)
Azure Synapse Analytics serverless SQL pools querying an Azure Data Lake Storage Gen2 account configured with Read-Access Geo-Redundant Storage (RA-GRS)Answer
D
Azure Synapse Analytics serverless SQL pools querying an Azure Data Lake Storage Gen2 account configured with Read-Access Geo-Redundant Storage (RA-GRS) using an ad-hoc Shared Access Signature (SAS) token configured with a three-year lifetime

Answer

Azure Synapse Analytics serverless SQL pools querying an Azure Data Lake Storage Gen2 account configured with Read-Access Geo-Redundant Storage (RA-GRS)

The configuration utilizing Azure Synapse Analytics serverless SQL pools and Azure Data Lake Storage Gen2 with Read-Access Geo-Redundant Storage (RA-GRS) satisfies all requirements. Serverless SQL pools charge on an on-demand basis per TB of data processed, aligning perfectly with low-frequency, ad-hoc queries (

8

12

times per week) and eliminating compute idle costs. RA-GRS provides the necessary regional disaster resilience by making data readable in the secondary region in the event of a primary region outage.

Step-by-Step Solution

Analyze the query frequency and compute model requirements.

An on-demand serverless SQL pool is selected instead of a dedicated SQL pool.

Queries are run infrequently (

8

12

times per week). Dedicated SQL pools would incur continuous costs for idle compute, whereas serverless SQL pools only charge per query, minimizing cost and operational overhead.

Analyze the storage redundancy and resilience requirements.

Read-Access Geo-Redundant Storage (RA-GRS) is selected instead of Locally Redundant Storage (LRS).

LRS is not resilient to regional outages. RA-GRS copies the data to a secondary region and ensures it remains readable even if the primary region fails.

Evaluate security and credentials constraints.

Direct long-lived ad-hoc SAS tokens are rejected.

Using a

3\text{-year}

ad-hoc SAS token introduces security risks and fails to utilize secure integration practices such as managed identities.

Key Concept

Selecting the optimal serverless query compute and geo-redundant storage integration to support cost-effective ad-hoc analytics with regional resilience.

Estimated Time:2m 30s

Question

Answer

Step-by-Step Solution

Key Concept

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