First thing first, check statistics and update if needed. Second check slowest running queries and current and missing indexes. Rewrite query or amend existing indexes to cover required columns. Review query plan. Check blocking queries. Check current load vs server vcores.

To resolve database performance issues, I’d first gather metrics and identify root causes (e.g., slow queries, resource bottlenecks). Then, I'd engage the team to align on goals and solutions. We’d prioritize quick fixes (like query optimization) versus long-term solutions (e.g., schema redesign). Next, I'd test changes incrementally, measuring performance to assess impact. Best practices like proper indexing, query optimization, and scalability considerations would guide fixes. By approaching the problem methodically, focusing on collaboration and data-driven decisions, I can help the team reach a consensus on the best solution while ensuring the database’s performance is optimized effectively.

To resolve a team disagreement on database performance issues: Understand All Perspectives: Hear everyone’s viewpoints. Define the Problem Clearly: Use objective data to identify the issue. Make Data-Driven Decisions: Use metrics to evaluate solutions. Brainstorm Collaboratively: Discuss and assess ideas openly. Test Solutions: Use small-scale tests or PoCs to validate options. Seek Expertise: Consult external experts if needed. Build Consensus: Align decisions with team and project goals. Document and Reflect: Record the process for clarity and future learning. Focus on collaboration, analysis, and communication to find the best solution.

If my team works on the performance issue from the database side, I will split the team into two parts. The first team will analyze the tables and functions, while the second team will analyze the stored procedures. Once I receive the analysis from both teams, I will cross-check their findings and discuss with both teams which areas of optimization will be most helpful for performance improvement. I will start work on that area.

From my experience, disagreements begins with aligning the team on a clear definition of the problem and understanding the root causes. I’ve found that focusing on data-driven insights is critical to identifying bottlenecks, such as inefficient queries, missing indexes, etc. Leveraging data early helps mitigate disagreements and provides a clear path forward. For example, using performance metrics can resolve disputes about whether to prioritize adding indexes or increasing resources. Establishing criteria like prioritizing low-effort, high-impact solutions further streamlines decision-making. By keeping discussions focused on measurable outcomes and fostering collaboration, the team can effectively resolve issues while staying aligned.