Database Consistency Checks After a database recovery, data consistency is a priority. Running consistency checks ensures that no data corruption or discrepancies have occurred during the recovery process. Tools like DBCC CHECKDB for SQL Server or ORACLE DBMS_REPAIR for Oracle are useful for identifying issues that might not be immediately visible but could cause performance problems later. My experience: Running consistency checks immediately after recovery gives confidence that the data is intact and prevents performance issues from arising due to corrupted or mismatched records.

1. Closely observe CPU, memory, disk usage, and query performance to identify bottlenecks. 2. Verify DB consistency. 3. Confirm that backups are complete, valid, & restorable. Short-Term 1. Run UPDATE STATISTICS. 2. Rebuild indexes to improve query performance. 3. Review DB conf,memory allocation, connection settings, & query timeout values. Long-Term Improvements 1. Identify & optimize resource-intensive queries using query analysis tools. 3. Schedule regular maintenance tasks, such as backups, integrity checks, and statistics updates. 5. Utilize tools like SQL Server Profiler, Query Store, or TP software to track performance metrics. 6. Create a performance baseline to compare post-recovery performance vs pre-recovery metrics.

I always say that everyone has their place, if I am a programmer I don't know everything about disks or backups, of course I use programs for all that and more, so you have to look for a backup program that works well and that does not create more problems when restoring, in case the problem is already done, there is no other option than to review the tables, the indexes, see if there is a good program that corrects any error automatically if possible.

Here’s my approach to maintaining performance after database recovery: 📂 Index Rebuild/Reorganize: Rebuild fragmented indexes to enhance query performance post-recovery. 📊 Statistics Update: Use UPDATE STATISTICS or enable AUTO_UPDATE_STATISTICS to keep the query optimizer effective. 💡 Resource Monitoring: Leverage tools like Azure Monitor or SQL Profiler to identify bottlenecks and adjust resources dynamically. 🔄 Query Optimization: Analyze execution plans and refactor inefficient queries where needed. 🛠️ Baseline Comparisons: To identify anomalies, compare current performance metrics with pre-incident baselines.

Verify Database Integrity: Run consistency checks to confirm data integrity and consistency. Rebuild Indexes: Rebuild or reorganize indexes to improve query performance. Update Statistics: Ensure up-to-date statistics for the query optimizer to function efficiently. Analyze Resource Utilization: Monitor CPU, memory, and disk usage to ensure there are no bottlenecks. Optimize Queries: Review slow-running queries and optimize them using proper indexing, rewriting, or tuning. Check Configuration Settings: Ensure that database and server configurations (e.g., cache size, parallel processing) are optimal. Run Full Backup: Perform a full backup after recovery to ensure data security.