A rapidly growing company is planning a new Cribl Stream deployment. They expect to ingest 10 TB of data per day, with peaks of 5x the average. They need to ensure the pipeline can handle this load and remain available. What is the most important design consideration?

Ensuring the data lake can handle the ingest volume.

Selecting a single, powerful Cribl Stream node with maximum CPU and memory.

Choosing the right storage for the persistent queue.

Designing for horizontal scalability by using multiple Cribl Stream nodes.

Why is audit logging important in a security data pipeline?

To automatically block malicious data from entering the pipeline

To reduce the volume of data stored in the pipeline

To provide a record of data flow and access for compliance and investigation

To improve the performance of the pipeline

What is the purpose of buffering in a data pipeline?

To permanently store all data for compliance purposes

To transform data into a different format

To temporarily store data when a destination is unavailable or slow

A SOC team notices that the number of events in the SIEM is lower than expected for the past hour. They suspect the Cribl pipeline is dropping data. What is the first step to troubleshoot this issue?

Restart the Cribl Stream service.

Immediately increase the worker processes to improve throughput.

Check the Cribl Stream monitoring dashboard for errors and queue depth.

Check the SIEM's ingestion API for errors.

Palo Alto NetworksCertified Security Operations Architect

Domain 2Objective 1

2.1 Plan Data Pipeline Architecture Using Data Pipeline Tools (e.g., Cribl) SECURITY-OPERATIONS-ARCHITECT Practice Questions (Page 4)

Part of the Platform and Data Architecture domain, which accounts for 49% of the SECURITY-OPERATIONS-ARCHITECT exam.

39questions here

8free pages

12concepts

49%of the exam

12 Concepts in This Objective

Data Pipeline Architecture Fundamentals
Cribl Overview and Capabilities
Data Sources and Destinations
Data Ingestion and Collection
Data Transformation and Normalization
Data Routing and Load Balancing
Data Filtering and Reduction
Data Pipeline Scalability and Performance
Data Pipeline Reliability and Fault Tolerance
Data Pipeline Security and Compliance
Integration with Security Operations Workflows
Monitoring and Troubleshooting Data Pipelines

Questions 16–20

16expert · hard
A rapidly growing company is planning a new Cribl Stream deployment. They expect to ingest 10 TB of data per day, with peaks of 5x the average. They need to ensure the pipeline can handle this load and remain available. What is the most important design consideration?
Select an answer first
17foundation · easy
Why is audit logging important in a security data pipeline?
Select an answer first
18application · medium
A team is evaluating Cribl Stream to reduce the cost of their SIEM. They currently send all raw logs to the SIEM. They want to use Cribl to reduce the volume and enrich the data before it reaches the SIEM. Which two Cribl features directly address these goals?
Select an answer first
19foundation · easy
What is the purpose of buffering in a data pipeline?
Select an answer first
20application · medium
A SOC team notices that the number of events in the SIEM is lower than expected for the past hour. They suspect the Cribl pipeline is dropping data. What is the first step to troubleshoot this issue?
Select an answer first

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