hardMultiple ChoiceObjective-mapped
DP-203 Practice Question: Monitoring an Azure Data Lake Storage Gen2…
You are monitoring an Azure Data Lake Storage Gen2 account using Metrics and Audit logs. You notice that the 'Ingress' metric shows a sudden spike but the 'Egress' metric remains stable. There are no new storage events in the audit log. What is the most likely cause?
⚠ Common exam trap
Test-takers frequently confuse 'Ingress' with 'Egress' or assume any write operation must generate a storage event, but Azure Storage events are opt-in and not all write operations (e.g., Data Factory intermediate writes) are configured to emit them.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
An Azure Data Factory pipeline is writing intermediate results to the storage account.
An Azure Data Factory pipeline writing intermediate results to the storage account would cause a spike in 'Ingress' (data written into the account) without a corresponding increase in 'Egress' (data read from the account). The absence of new storage events in the audit log suggests the writes are not triggering blob-level events (e.g., BlobCreated events), which is consistent with Data Factory writing intermediate files using the Azure Blob Storage REST API or SDK without enabling event grid notifications for those specific operations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The storage account is configured with geo-redundant storage (GRS) and data is being replicated to the secondary region.
Why it's wrong here
ADLS Gen2 does not support GRS; replication is managed at the storage account level and would not cause ingress spikes without corresponding egress.
- ✗
A Spark job is reading large amounts of data in parallel.
Why it's wrong here
Reading data increases egress, not ingress.
- ✓
An Azure Data Factory pipeline is writing intermediate results to the storage account.
Why this is correct
Writes increase ingress, and if the pipeline is using staging or intermediate storage, it may not log each write as a separate storage event.
- ✗
An Azure Function is triggered by blob creation events and writes logs to the same account.
Why it's wrong here
Blob creation events would appear in audit logs, contradicting the observation.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
Key term
Data Transformation Pipelines
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.