Examkin

Soru

Zorluk: OrtaData Integration and Analytical Storage

A logistics company is designing an analytical data platform to track fleet vehicles in real time. The platform must meet the following requirements:
- Ingest GPS telemetry from 50,00050,000 vehicles transmitting data every 55 seconds (approximately 10,00010,000 events per second).
- Store all raw telemetry data in Azure Data Lake Storage (ADLS) Gen2 in Parquet format for long-term historical analysis.
- Perform near-real-time analysis of the incoming streams to detect route deviations, with an end-to-end latency of under 22 seconds.
- Minimize administrative and operational overhead.
- Ensure the data platform can survive a primary datacenter outage.

Which two Azure services or configurations should you recommend to meet these requirements?

  1. Azure Event Hubs to ingest the streaming vehicle telemetryCevap
  2. Azure Stream Analytics to analyze the telemetry stream and output data to Azure Data Lake Storage (ADLS) Gen2Cevap
  3. C
    A dedicated Synapse SQL pool to process and store the incoming telemetry stream in real time
  4. D
    Locally Redundant Storage (LRS) replication for the Azure Data Lake Storage (ADLS) Gen2 account
  5. E
    A Shared Access Signature (SAS) token configured with a 33-year lifetime and no stored access policy for device authentication

Cevap

The logistics company should use Azure Event Hubs to ingest the streaming vehicle telemetry and Azure Stream Analytics to analyze the telemetry stream and output data to Azure Data Lake Storage (ADLS) Gen2.
Azure Event Hubs is designed for high-throughput streaming ingestion from millions of devices, while Azure Stream Analytics offers a serverless engine to analyze streams and write to storage with sub-second latency, satisfying the business requirements.

Adım Adım Çözüm

1
Determine the ingestion requirements.
Azure Event Hubs is identified as the optimal ingestion service due to its ability to ingest millions of events per second with minimal latency and low operational overhead.
The platform needs to ingest 10,00010,000 events per second with low latency.
2
Select the stream processing and storage integration service.
Azure Stream Analytics is selected to process the stream with sub-second latency and write to ADLS Gen2 in Parquet format.
Stream Analytics is fully managed, serverless, and satisfies the sub-22-second end-to-end latency constraint while outputting raw data to ADLS Gen2.
3
Evaluate storage redundancy and security constraints.
Identify that Locally Redundant Storage (LRS) is insufficient for regional outages, and long-lived SAS tokens without access policies pose a significant security risk.
The system must survive a datacenter outage and maintain a secure authentication mechanism.

Anahtar Kavram

Selecting streaming ingestion and analytical storage components matching throughput, latency, redundancy, and security requirements.
Tahmini Süre:2m 0s
Bu soruyu puanla

Konular

Data Integration and Analytical Storage

Bu konudan daha fazla soru