Use case
A valuable feature would be an AI-assisted prompt focused on Azure SQL sizing and production readiness. The prompt could allow developers to describe their workload, including expected concurrency, query patterns, execution frequency, and estimated data volume. Based on this information, the assistant could recommend an initial sizing strategy, suggest the most appropriate Azure SQL tier, highlight potential performance risks, and provide basic query or indexing recommendations. This would help development teams understand the expected consumption before deployment and choose the best path to move their applications to production on Azure.
Current workaround
No response
Proposed behavior
This feature should work as a guided prompt for production readiness and Azure SQL sizing. The assistant would collect workload information from the developer, including query patterns, expected concurrency, execution frequency, estimated data size, and read/write behavior. After analyzing this input, it would return an initial recommendation covering Azure SQL tier considerations, estimated consumption, potential bottlenecks, query tuning suggestions, and indexing opportunities.
The expected behavior is to provide practical and actionable guidance during the development phase. It should help developers identify whether their workload is likely to require adjustments before deployment and whether the selected Azure SQL tier is aligned with the expected usage.
This would give teams an early sizing perspective before production, helping reduce performance issues, avoid under-provisioning or over-provisioning, and improve the confidence of moving applications to Azure.
Who benefits
All developers
Urgency
Nice to have
Additional context
No response
Use case
A valuable feature would be an AI-assisted prompt focused on Azure SQL sizing and production readiness. The prompt could allow developers to describe their workload, including expected concurrency, query patterns, execution frequency, and estimated data volume. Based on this information, the assistant could recommend an initial sizing strategy, suggest the most appropriate Azure SQL tier, highlight potential performance risks, and provide basic query or indexing recommendations. This would help development teams understand the expected consumption before deployment and choose the best path to move their applications to production on Azure.
Current workaround
No response
Proposed behavior
This feature should work as a guided prompt for production readiness and Azure SQL sizing. The assistant would collect workload information from the developer, including query patterns, expected concurrency, execution frequency, estimated data size, and read/write behavior. After analyzing this input, it would return an initial recommendation covering Azure SQL tier considerations, estimated consumption, potential bottlenecks, query tuning suggestions, and indexing opportunities.
The expected behavior is to provide practical and actionable guidance during the development phase. It should help developers identify whether their workload is likely to require adjustments before deployment and whether the selected Azure SQL tier is aligned with the expected usage.
This would give teams an early sizing perspective before production, helping reduce performance issues, avoid under-provisioning or over-provisioning, and improve the confidence of moving applications to Azure.
Who benefits
All developers
Urgency
Nice to have
Additional context
No response