AZ-305 Designing Microsoft Azure Infrastructure Solutions Exam

Recommend a Solution for Database Scalability

Evaluate Azure Relational Database Scaling Patterns

When planning for database scalability, it's crucial to understand and differentiate between vertical scaling and horizontal scaling techniques in Azure SQL Database and Azure Database for PostgreSQL.

Vertical Scaling

Vertical scaling, also known as scaling up/down, involves increasing or decreasing the compute size of an individual database. In Azure, this can be achieved by upgrading service tiers or adjusting vCores.

• Service Tiers: Databases can move between different service tiers such as General Purpose, Business Critical, and Hyperscale.
  • General Purpose: Balances cost and performance.
  • Business Critical: Provides low-latency storage and high transaction rates.
  • Hyperscale: Allows for extensive storage scaling.
• vCore Adjustments: vCores can be adjusted to meet workload demands. Higher vCores offer more CPU, memory, and faster IOPS.

Advantages of vertical scaling include:

• Efficiency: Dynamic scaling matches resource allocation with current demand.
• Minimal Change: No changes to database architecture or application logic.

Horizontal Scaling

Horizontal scaling, also known as scaling out/in, involves adding or removing database instances to distribute the load. This technique is particularly useful for handling high throughput and scaling read or write operations.

• Elastic Pools: A group of databases sharing resources to balance cost and performance.
  • Resource Sharing: Helps manage varying workloads efficiently.
• Sharding: Distributing large datasets across multiple databases to improve performance.
  • Shard management: Handle data partitions and routing in the application layer.
• Read Scale-Out: Creating read replicas to handle read-heavy workloads without affecting write performance.

Advantages of horizontal scaling include:

• Scalability: Can handle larger workloads by adding more instances.
• Performance: Distributes the load across multiple databases to improve efficiency.

Dynamic Scaling

Azure supports dynamic scaling, which can be manual or automatic:

• Manual Scaling: Adjusting resources through the Azure portal, PowerShell, or CLI.
• Automatic Scaling (Serverless): Automatically adjusts compute resources based on workload demand. Available in the serverless compute tier for Azure SQL Database.

Conclusion

To evaluate Azure relational database scaling patterns:

• Vertical Scaling: Ideal for applications needing performance boosts without architecture changes.
• Horizontal Scaling: Suitable for applications requiring extensive scalability and load distribution.

Both scaling techniques can be dynamically managed to optimize performance, cost, and resource allocation, ensuring databases meet the demands of varying workloads.