easyMultiple ChoiceObjective-mapped

DP-203 Practice Question: Analyzing the exhibit from an Azure Monitor…

Exhibit

Refer to the exhibit.
```json
{
  "metric": "BlobCount",
  "aggregation": "Average",
  "timeGrain": "PT1H",
  "filter": {
    "dimension": "BlobType",
    "operator": "equals",
    "values": ["BlockBlob"]
  }
}
```

You are analyzing the exhibit from an Azure Monitor metric query for a storage account. What is the primary purpose of this query?

⚠ Common exam trap

A common mix-up: candidates confuse 'avg' with 'sum' or 'max', leading them to incorrectly think the query calculates total blob count or identifies peak periods, rather than recognizing that 'avg' specifically computes the average value over the time granularity.

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

✓

To retrieve the average count of block blobs per hour.

The query uses the 'avg' aggregation on the 'BlobCount' metric, which calculates the average number of blobs over the specified time granularity (e.g., per hour). The result shows the average count of block blobs per hour, not the total count or the count in a specific tier. This aligns with option D, as the query is designed to retrieve the average count of block blobs per hour.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
To calculate the average number of block blobs in the hot tier.
Why it's wrong here
No filter on access tier is applied.
✗
To identify the time period with the highest blob count.
Why it's wrong here
Query returns average per hour, not max over time.
✗
To measure the total size of all block blobs in the account.
Why it's wrong here
Metric is BlobCount, not BlobSize.
✓
To retrieve the average count of block blobs per hour.
Why this is correct
Metric BlobCount with aggregation Average and filter on BlobType equals BlockBlob.

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

DP-203 Practice Question: Analyzing the exhibit from an Azure Monitor…

Exhibit

Why each option matters

Option-by-option breakdown

Azure Blob Storage Tier Comparison

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