What do you do if your database is riddled with errors?

- Error logs are your best friend in this case, go through error logs and identify unique errors you are encountering. - Make necessary changes in queries /procedures/functions once you identify the root cause, Test whatever changes you are making first on the staging server and then implement it on production. and always monitor after making any major changes in the system. - Deploy proper monitoring solutions to avoid similar future scenarios, there are plenty of open-source tools you can use depending on your DB and use case. - Set alerts, proactively set alerts for issues/errors note them down, and resolve them as soon as you encounter them.

In my experience, we must go to the Database alert.log (error log) and search about the most recently error. Then search about the root cause of it and analysis the reasons. In the worst case we can aid by restoring the backup.

Errors are evening coffee for database developers. If there is any error then 1. Find the exact error and Root Cause. Check the logs, error tables or reports where the 2. Impact analysis: What is the business impact. How many other reports or system will have impacted due to this.

When errors occur in your database, take a moment to assess the damage by reviewing error logs for insights into the issue's scope and pattern. By understanding the scope and impact of the problem, you can develop an action plan and communicate clearly with stakeholders.

Determine the exact error, find a fix for it, test the fix, implement it, validate it and go on to the next error. Depending on when the errors started, you may have to restore the database to a point-in-time and rerun the transactions.

Backup is like a golden key to save your database and your job too. Make sure to backup before any change and also after change.

A recent backup of your database is crucial for restoring it if repair attempts lead to further issues. Testing backups regularly ensures data safety and provides confidence for future issues.

Create a test or integration database from your DB backup and test solutions in that environment before executing in your production DB.

Before backing up the database ensure that performing the backup will not destroy or corrupt any previous backups. I.E. don’t overwrite a good backup with a bad backup, as this may cause potentially further loss of data. Ideally ensure that additional Adhoc backups taken are secured separately to normal backups.

Identify specific errors in your database using query tools or diagnostic functions. For example, you can check the integrity of an object using the CHECKDB command in a SQL database. This step helps pinpoint error locations, whether in the data, schema, or underlying system, guiding subsequent troubleshooting efforts.

Review the relevant activity, alert and error logs. Go back to a known good position in the logs where the database was error free / working so you can baseline what the working system looks like. Move forward through the logs to identify when the errors first occurred. Review if there were any other known activities around the time of the initial errors which could have contributed to the impact on the database. Review if there were any initial errors that could have had a ripple effect and caused subsequent errors flooding logs. Common causes may include: Out of Space, Out of Memory, Loss of network connectivity. Check underlying Operating System / Infrastructure does not have issues.

Use appropriate commands or scripts to fix the database after identifying errors. For example, in SQL databases, consider using REPAIR_ALLOW_DATA_LOSS commands to resolve index corruption. Be careful as some repairs can cause data loss, so be sure to have a backup in place before proceeding.

To mitigate future issues, focus on optimizing database performance after error repairs. By updating statistics, defragmenting indexes, and refining maintenance plans, you can prevent potential errors from occurring and ensure efficient database operation. Maintaining long-term database health and performance requires consistent maintenance.

In order to prevent future errors, deploy proactive measures such as automated error alerts, enhanced backup protocols, or software and hardware upgrades. Education on data management best practices is equally important. By taking these proactive measures, recurring issues are less likely to occur, enhancing database stability and reliability.