DP-300 Practice Question: Monitor, configure, and optimize database resources
You are optimizing an Azure SQL Database that uses the Business Critical tier. Which TWO factors affect the maximum log rate?
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
✓
Service level objective (SLO)
The maximum log rate for an Azure SQL Database in the Business Critical tier is determined by the service level objective (SLO) and the number of vCores. Option A is correct because the SLO defines the performance tier and hardware configuration, which directly caps the log generation rate (e.g., Business Critical with 4 vCores has a specific log rate limit). Option B is correct because within a given SLO, the log rate scales with the number of vCores—more vCores allow a higher maximum log rate. Option C is incorrect because backup retention period affects storage and recovery, not log throughput. Option D is incorrect because Azure SQL Database manages log files automatically; the number of log files is not a user-configurable factor affecting log rate. Option E is incorrect because page compression reduces data size and I/O but does not directly determine the maximum log generation rate.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Service level objective (SLO)
Why this is correct
The service level objective sets the provisioned compute and storage limits, which directly cap the transaction log generation rate for Business Critical databases. Higher SLOs provision more log throughput, so the SLO determines the ceiling on log rate independent of workload tuning.
- ✓
Number of vCores
Why this is correct
More vCores directly raise the transaction log throughput ceiling on Business Critical, because each vCore contributes its own log write capacity. The tier's local SSD and in-memory OLTP design means log rate scales with compute, so vCore count is a genuine determinant of the maximum log rate.
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Backup retention period
Why it's wrong here
Backup retention determines how long copies are kept, not how quickly log records are generated or hardened, so it cannot influence the maximum log rate. It is tempting because retention is a core business continuity setting, and it would be the right consideration when sizing storage for backup history rather than tuning log throughput.
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Number of log files
Why it's wrong here
The number of log files is not a tunable factor; Azure SQL Database manages log file structure internally. Maximum log rate depends on service tier, vCore count, and transaction size. Log file count would matter only for on-premises SQL Server where DBAs add files manually.
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Page compression level
Why it's wrong here
Page compression affects data page storage and buffer pool usage, not the transaction log generation rate, which is governed by log records written per transaction. It is tempting because compression is a genuine performance and storage tuning lever, and it would be the correct factor when optimising data page IO rather than log throughput.
Go deeper
Related to this question
Learn chapter
Monitoring Database Performance with Azure Tools
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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