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Difficulty: MediumData Integration and Analytical Storage

A gaming company is designing an analytical data platform to analyze multiplayer match telemetry logs. The solution must meet the following requirements:
- Volume: 500 GB of telemetry data is generated daily.
- Ingestion: Logs are uploaded as Parquet files to Azure Data Lake Storage Gen2 (ADLS Gen2) every 6 hours.
- Query Latency: Analysts run ad-hoc exploratory queries that must return results within 2 minutes.
- Cost: The compute solution must not incur charges when no queries are running.
- Resiliency: The storage solution must survive a primary datacenter outage.

Which design should you recommend?

  1. An Azure Synapse Analytics serverless SQL pool querying data stored in an ADLS Gen2 account configured with Geo-Redundant Storage (GRS)Answer
  2. B
    An Azure Synapse Analytics dedicated SQL pool querying data stored in an ADLS Gen2 account configured with Geo-Redundant Storage (GRS)
  3. C
    An Azure Synapse Analytics serverless SQL pool querying data stored in an ADLS Gen2 account configured with Locally Redundant Storage (LRS)
  4. D
    An Azure Function running on a Consumption plan querying data stored in an ADLS Gen2 account configured with Geo-Redundant Storage (GRS)

Answer

An Azure Synapse Analytics serverless SQL pool querying data stored in an ADLS Gen2 account configured with Geo-Redundant Storage (GRS)
The correct solution uses Azure Synapse Analytics serverless SQL pool to query data stored in a Geo-Redundant Storage (GRS) enabled Azure Data Lake Storage Gen2 account. Synapse serverless SQL pool is designed for ad-hoc, exploratory queries on file-based data lakes, scaling compute automatically and charging only for the query data processed (with zero idle cost). GRS replicates data to a secondary region, protecting against primary datacenter failure.

Step-by-Step Solution

1
Evaluate the compute requirement for ad-hoc exploratory queries with zero idle cost.
Identify Azure Synapse Analytics serverless SQL pool as the optimal compute choice because it charges only for data processed and incurs no costs when idle, unlike dedicated SQL pools.
Meets the requirement for ad-hoc querying without persistent compute overhead.
2
Evaluate the resiliency requirement of surviving a primary datacenter outage.
Select Geo-Redundant Storage (GRS) over Locally Redundant Storage (LRS) for the Azure Data Lake Storage Gen2 account.
LRS is vulnerable to a single datacenter outage, whereas GRS replicates data to a paired secondary region.
3
Assess alternate compute solutions like Azure Functions on Consumption plan.
Rule out Azure Functions due to potential execution timeouts (max 10 minutes) when scanning large datasets.
Ensures query execution reliability and avoids serverless timeouts.

Key Concept

Selecting serverless SQL pools for ad-hoc queries on data lakes and configuring Geo-Redundant Storage for resiliency.
Estimated Time:1m 30s
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Topics

Data Integration and Analytical Storage

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