Skip to content

DTU_EDTU

1. What is the problem of mapping work load with Azure configuration ?

Problem of Mapping Workload with Azure Configuration

Mapping workloads correctly with Azure configurations is critical to ensure optimal performance, cost-efficiency, and reliability. However, there are several challenges and problems that organizations face during this process:

⚠️ Common Problems

1. Incorrect Sizing of Resources

  • Issue: Choosing VM sizes or App Service plans that are too small or too large.
  • Impact: Under-provisioning leads to performance bottlenecks; over-provisioning causes unnecessary costs.

2. Lack of Understanding of Workload Characteristics

  • Issue: Not analyzing CPU, memory, I/O, and scaling behavior of the workload.
  • Impact: Results in misaligned service selection, such as using an App Service when a Function App would be more cost-effective.

3. Improper Use of Service Tiers

  • Issue: Selecting wrong pricing tiers (e.g., Basic instead of Premium).
  • Impact: Missing out on features like auto-scaling, staging slots, or high availability.

4. Ignoring Network and Storage Needs

  • Issue: Workload requires specific networking or storage configurations not accounted for.
  • Impact: Leads to network bottlenecks or data latency issues.

5. Overlooking Compliance and Security Requirements

  • Issue: Not mapping workloads to services that meet regulatory or security needs.
  • Impact: Non-compliance with industry standards (e.g., HIPAA, GDPR).

🛠 Best Practices for Mapping

  • Use Azure Advisor: Get real-time suggestions for performance and cost optimizations.
  • Perform Workload Assessment: Analyze workload behavior using tools like Azure Migrate.
  • Right-size Continuously: Use autoscaling and cost monitoring tools to adjust as usage changes.
  • Align with Business SLAs: Choose configurations that support your uptime, latency, and DR requirements.
  • Leverage Azure Well-Architected Framework: Follow guidelines to optimize reliability, performance, and cost.

✅ Conclusion

Mapping workloads with the correct Azure configurations is not a one-time task. It requires continuous assessment and alignment with workload behavior, business goals, and cost considerations. Failure to do so can lead to degraded performance, security issues, and increased cloud bills.

2. Explain DTU and EDTU ?

Understanding DTU and eDTU in Azure SQL Database

When using Azure SQL Database, it's important to understand how Microsoft defines and allocates performance using DTUs and eDTUs. These units simplify resource management but can be confusing without proper context.

💡 What is a DTU?

DTU (Database Transaction Unit) is a blended measure of:

  • CPU
  • Memory
  • Reads and Writes (I/O)

It represents the overall performance level for a single Azure SQL database in the DTU-based purchasing model.

💬 Think of it as a performance "package" that wraps CPU, memory, and storage IOPS into one simplified number.

🔢 Example DTU Tiers:

Tier DTUs Max Storage
Basic 5 2 GB
Standard 10–300 250 GB
Premium 125–4000 1 TB

📘 What is an eDTU?

eDTU (Elastic DTU) is the equivalent of DTU but applied to Elastic Pools.

  • Elastic Pools are collections of databases that share resources.
  • eDTUs are the total pooled performance capacity available to all databases within the pool.

🧠 eDTU = Shared DTU capacity across all databases in a pool

🔄 Key Difference:

  • DTU = For single database
  • eDTU = For elastic pool of databases

🆚 DTU vs vCore Model

Feature DTU Model vCore Model
Unit of measure DTU (bundled) vCore (CPU + memory separately)
Flexibility Less granular More control over resources
Use case Simpler workloads, cost limits Enterprise workloads, predictable scaling
Transparency Lower Higher (you know exact CPU/memory)

✅ When to Use

Scenario Choose
You want simple pricing and don't need fine-grained control DTU model
You want transparency, control, and scalability vCore model
You have multiple databases with unpredictable usage patterns eDTU with Elastic Pool

📌 Summary

  • DTU: Performance metric for a single database, combining CPU, memory, and I/O.
  • eDTU: Shared DTU performance metric for elastic pools (multiple databases).
  • Useful for simplified performance planning, but less flexible than vCore-based pricing.

3. On which factors does DTU depend ?

🔍 Factors on Which DTU Depends

A DTU (Database Transaction Unit) in Azure SQL Database is a pre-configured blend of three core resources:

  1. CPU (Compute Power)

  2. Represents the processing capability of the database engine.

  3. DTU includes CPU cycles for:
  4. Query execution
  5. Indexing
  6. Stored procedure processing
  7. Complex joins or calculations

⚠️ CPU-bound queries can max out DTUs quickly.

  1. Memory (RAM)

  2. Used for:

  3. Query caching
  4. Data buffering
  5. Sorting and hashing operations
  6. Execution plans

💡 Efficient use of memory can significantly reduce I/O and boost performance. 3. Disk I/O (Reads and Writes)

  • Includes:
  • Transaction log writes
  • Data page reads/writes
  • TempDB usage
  • I/O-heavy operations (bulk inserts, frequent reads) consume more DTUs.

📉 Poor indexing or large table scans increase I/O load and DTU usage. 🔁 DTU = Blended Metric

The DTU is essentially a performance throttle that balances: DTU = f(CPU, Memory, Disk I/O) If any one of the three resources hits its threshold, your DTU usage approaches 100%, throttling further performance.

📊 What Affects DTU Consumption?

Factor Impact on DTU
Complex or nested queries High CPU usage
Missing indexes Increased I/O
Large result sets More memory and I/O
High transaction volume CPU + I/O
Long-running or blocking queries CPU + Memory
Poor query design All 3 (CPU, Mem, I/O)

🛠 Tools to Monitor DTU Usage

  • Azure Portal → SQL Database → Monitoring → DTU %
  • Query Performance Insight
  • Extended Events or Query Store

✅ Optimization Tips

  • Use proper indexing and query tuning
  • Reduce I/O operations by filtering and batching
  • Enable automatic tuning in Azure SQL
  • Consider scaling to a higher DTU or switch to vCore model for more control

📌 Summary

DTU depends on:

  • CPU usage
  • Memory pressure
  • Disk I/O operations

Understanding workload behavior helps you choose the right DTU tier and optimize performance effectively.

4. How to calculate DTU ?

📐 How to Calculate DTU (Database Transaction Units)

Azure does not provide a direct formula to calculate DTUs because they are abstract performance units, blending CPU, memory, and I/O. However, Microsoft offers tools and guidance to help estimate DTU requirements based on your on-premise or existing workloads.

⚙️ What is DTU?

DTU = A blended measure of CPU + Memory + IOPS
It helps you choose the right Azure SQL Database performance level (Basic, Standard, Premium)

🧮 How to Calculate or Estimate DTU Requirements

✅ Option 1: Use Microsoft DTU Calculator (Recommended)

Microsoft provides a tool:
👉 DTU Calculator

📋 Steps:

  1. Run a workload on your existing SQL Server (on-premise or VM).
  2. Collect performance metrics using Performance Monitor (PerfMon) for:
  3. Processor: % Processor Time
  4. Logical Disk: Disk Reads/sec, Disk Writes/sec
  5. SQL Server: Batch Requests/sec
  6. Export the data to a CSV.
  7. Upload to the DTU Calculator.
  8. The tool estimates the minimum DTU tier needed for Azure SQL Database.

📊 Example Metrics Collected

Metric Description
% Processor Time CPU utilization
Disk Reads/sec Read I/O load
Disk Writes/sec Write I/O load
Batch Requests/sec Workload intensity

✅ Option 2: Use Azure SQL Query Performance Insight

If you're already in Azure:

  • Go to SQL Database → Monitoring → Query Performance Insight
  • Check DTU usage over time
  • Analyze top-consuming queries

⚠️ Notes

  • DTUs are only relevant in the DTU-based pricing model.
  • For vCore-based models, resource estimation is done separately (vCPU, RAM, IOPS).
  • DTUs do not map 1:1 with any physical resource; they are relative units.

📌 Summary

Method Use When
DTU Calculator Migrating from on-prem or VM to Azure SQL
Azure Monitor & Insights Already in Azure environment
Manual Estimation (not recommended) Lacks precision without real metrics

🧠 DTU calculation is estimative, not exact. Always monitor after deployment to adjust tier if needed.

5. How to measure the five factors which derive DTU ?

📏 How to Measure the Five Factors That Drive DTU

DTU (Database Transaction Unit) is a composite measure of five core performance metrics related to:

  1. CPU
  2. Memory
  3. Data Reads
  4. Data Writes
  5. Transaction Log Writes

These metrics help estimate the workload intensity and choose the correct DTU tier. 🧠 Why Measure These?

Azure bundles CPU, memory, and I/O into DTUs. Understanding the individual contributors lets you:

  • Right-size your Azure SQL tier
  • Optimize queries and performance
  • Migrate on-prem workloads accurately using the DTU Calculator

🖥️ Tools to Use

  • Performance Monitor (PerfMon) for on-prem SQL Server
  • Azure Monitor / Query Performance Insight for Azure SQL
  • SQL Server Management Studio (SSMS) for DMVs

🔍 Factor-by-Factor Measurement

1. CPU Usage

Metric: % Processor Time (instance-wide)

How to Measure:

  • PerfMon counter: Processor(_Total)\% Processor Time
  • DMV: sql SELECT record_id, SQLProcessUtilization FROM sys.dm_os_ring_buffers

2. Memory Usage

Metric: Buffer cache usage / memory grants

How to Measure:

  • PerfMon counter: SQLServer:Memory Manager\Target Server Memory & Total Server Memory
  • DMV: sql SELECT total_physical_memory_kb, available_physical_memory_kb FROM sys.dm_os_sys_memory;

3. Data Reads (Logical/Physical)

Metric: Disk Reads/sec, Page Reads/sec

How to Measure:

  • PerfMon counter: LogicalDisk(_Total)\Disk Reads/sec
  • DMV: sql SELECT * FROM sys.dm_io_virtual_file_stats(NULL, NULL);

4. Data Writes

Metric: Disk Writes/sec

How to Measure:

  • PerfMon counter: LogicalDisk(_Total)\Disk Writes/sec
  • DMV: sql SELECT * FROM sys.dm_io_virtual_file_stats(NULL, NULL);

5. Transaction Log Writes

Metric: Log I/O throughput

How to Measure:

  • PerfMon: SQLServer:Databases\Log Bytes Flushed/sec
  • DMV: sql SELECT database_id, log_write_percent, log_bytes_flushed FROM sys.dm_db_log_space_usage; 📊 Suggested PerfMon Counters for DTU Estimation
Category Counter
CPU % Processor Time
Memory Total Server Memory (KB)
Data Read I/O Disk Reads/sec
Data Write I/O Disk Writes/sec
Log Writes Log Bytes Flushed/sec
Workload Intensity Batch Requests/sec

🧪 Using the DTU Calculator

  1. Collect PerfMon logs with above counters over typical workload.
  2. Export the data to CSV.
  3. Upload to Azure DTU Calculator
  4. View estimated DTU requirements and recommended pricing tier.

✅ Summary

Factor Measurement Tool PerfMon Counter / DMV
CPU PerfMon, DMV % Processor Time, SQLProcessUtilization
Memory PerfMon, DMV Total/Target Server Memory, dm_os_sys_memory
Data Reads PerfMon, DMV Disk Reads/sec, dm_io_virtual_file_stats
Data Writes PerfMon, DMV Disk Writes/sec, dm_io_virtual_file_stats
Log Writes PerfMon, DMV Log Bytes Flushed/sec, dm_db_log_space_usage

💡 Tip: Monitor during peak usage periods to get the most accurate DTU estimation.

6. How can you create SQL Server DB on Azure ?

🛠️ How to Create a SQL Server Database on Azure

You can create an Azure SQL Database (PaaS) via the Azure Portal, Azure CLI, ARM Templates, or PowerShell. Below is the most common and beginner-friendly method: Azure Portal.

🌐 Option 1: Create via Azure Portal (GUI) ✅ Step-by-Step

1. Sign in to Azure Portal

Go to 👉 https://portal.azure.com

Create a SQL Server (Logical Server)

-Search for SQL Server in the search bar.

  • Click Create > SQL Server.

1. Fill in the following:

  • Server Name: globally unique
  • Admin Username & Password

  • Region: where the server will reside

  • Click Review + Create → Create

Create SQL Database

  • Go to the SQL databases service.

  • Click Create → SQL Database.

Fill in:

  • Database Name
  • Subscription and Resource Group
  • Select SQL Server (use the one you just created)
  • Compute + Storage: choose DTU or vCore model

  • Backup and Geo-redundancy options

  • Click Review + Create → Create

Configure Firewall & Networking

  • After creation, go to the SQL Server resource.

  • Open Networking > Firewalls and virtual networks.

  • Add your client IP address to allow external access.

  • Save changes.

Connect to the Database

  • Use SQL Server Management Studio (SSMS) or Azure Data Studio
  • Server name format: .database.windows.net
  • Use the admin username/password you provided.

⚙️ Option 2: Create via Azure CLI

 Create Resource Group
az group create --name myResourceGroup --location eastus

 Create SQL Server
az sql server create \
--name my-sql-server \
--resource-group myResourceGroup \
--location eastus \
--admin-user myadmin \
--admin-password MyP@ssword123

 Create SQL Database
az sql db create \
--resource-group myResourceGroup \
--server my-sql-server \
--name mySampleDatabase \
--service-objective S0

7. Error while connecting to the azure database from SSMS

ERROR

An instance-specific error occurred while establishing a connection to SQL Server.
Connection was denied since Deny Public Network Access is set to
Yes (https://docs.microsoft.com/azure/azure-sql/database/connectivity-settings#deny-public-network-access).
To connect to this server, use the Private Endpoint from inside your virtual network (https://docs.microsoft.com/azure/sql-database/sql-database-private-endpoint-overview#how-to-set-up-private-link-for-azure-sql-database). (Microsoft SQL Server, Error: 47073)

Azure SQL Connectivity Setup

This document outlines how to configure connectivity to an Azure SQL Server for Production and Development/Test environments.

🔒 Production: Secure Access via Private Endpoint

✅ Use Case: For production environments where public access is not permitted.

🔧 Steps:

1. Create a Private Endpoint

  • Go to the Azure Portal → SQL Server (not database).
  • Navigate to Networking → Private endpoint connections.
  • Click + Private endpoint and follow the wizard.
  • Associate it with the correct Virtual Network (VNet) and subnet.

2. Configure Private DNS

  • Use Azure Private DNS Zone: privatelink.database.windows.net
  • Link it to your VNet.
  • Ensure the DNS resolves the SQL Server name to the private IP.

3. Access from Azure Resources

  • Ensure clients (VMs, App Services, Functions) are in the same VNet or peered VNet.
  • Use the regular server name (e.g., yourserver.database.windows.net) — it will resolve to the private IP.

4. Test Connection

  • RDP into a VM within the VNet (or use VNet-integrated app).
  • Use SSMS or app connection string to verify access.

5. Ensure Public Access is Disabled

  • Navigate to SQL Server → Networking.
  • Set Public network access to Deny.

📘 Private Link Setup Guide

🧪 Development/Test: Controlled Public Access

⚠️ Use Case: For local development or testing scenarios where secure access is relaxed.

🔧 Steps:

1. Allow Public Network Access

  • Go to SQL Server → Networking.
  • Set Public network access to Yes.

3. Add Client IP to Firewall Rules

  • Under Firewall and virtual networks, add your current IP address.
  • Use 0.0.0.0 - 255.255.255.255 only for testing (not recommended).

3. Test SQL Connection

  • Use SSMS, Azure Data Studio, or your application with:
  • Server: yourserver.database.windows.net
  • Authentication: SQL Auth / Azure AD / Managed Identity

4. Restrict When Done

  • Remove test IPs and reset Public network access to Deny when testing is complete.

📘 Firewall Configuration Guide

🧠 Best Practices

  • ✅ Always use Private Endpoints in production.
  • ✅ Monitor and alert on unexpected public access attempts.
  • ✅ Periodically review firewall rules and audit access.
  • 🚫 Never use Allow All IP range in production.