1. What is the Azure Cosmos DB Capacity Calculator?

The Azure Cosmos DB Capacity Calculator estimates request units per second (RU/s) required for Azure Cosmos DB throughput. It helps determine the appropriate provisioned throughput for your database operations.

2. How Does the Calculator Work?

The calculator uses the RU/s formula:

Where:

• \( Reads\ per\ Second \) — Number of read operations per second
• \( Read\ RU\ Cost \) — Request unit cost for each read operation
• \( Writes\ per\ Second \) — Number of write operations per second
• \( Write\ RU\ Cost \) — Request unit cost for each write operation

Explanation: The equation calculates the total request units needed per second by summing the cost of all read and write operations.

3. Importance of RU/s Calculation

Details: Accurate RU/s estimation is crucial for Azure Cosmos DB performance planning and cost optimization. Proper provisioning ensures your database meets performance requirements while minimizing costs.

4. Using the Calculator

Tips: Enter the number of read and write operations per second along with their respective RU costs. All values must be non-negative numbers.

5. Frequently Asked Questions (FAQ)

Q1: What are Request Units (RUs) in Azure Cosmos DB?
A: Request Units represent the cost of database operations in Azure Cosmos DB, abstracting CPU, memory, and IO costs into a single measure.

Q2: How do I determine the RU cost of my operations?
A: RU costs vary based on operation complexity, item size, and indexing. You can measure actual RU consumption using Azure Monitor or the Cosmos DB SDK.

Q3: What happens if I provision too few RUs?
A: If provisioned RUs are insufficient, requests may be rate-limited (HTTP 429 errors) and performance will degrade.

Q4: Can I adjust provisioned RU/s after deployment?
A: Yes, Azure Cosmos DB allows you to scale provisioned RU/s up or down at any time, with changes typically taking effect within minutes.

Q5: What's the difference between provisioned and serverless capacity?
A: Provisioned throughput guarantees capacity but requires upfront planning, while serverless charges per operation but may have performance variability.