Oracle Indexes: Fix Slow SQL Without Overdoing It

A SQL query running for 8 seconds may not create panic during testing. In production, the same query can become a real incident when it runs thousands of times from an application, report, or batch process.

I have seen queries drop from seconds to milliseconds after adding one correct index. I have also seen OLTP systems become slower because every column was indexed without understanding the workload. Both situations are common.

Indexes are powerful, but they are not free. They reduce unnecessary reads for SELECT queries, but they add cost to INSERT, UPDATE, DELETE, storage, statistics gathering, and maintenance. A good DBA does not create indexes blindly. A good DBA checks the SQL pattern, data volume, selectivity, execution plan, and write workload before touching production.

The Oracle DBA Role in the AI Era - See how Oracle AI Database 26ai, Autonomous AI Database and MAA are reshaping the DBA role across reliability, security and enterprise AI

Database automation has removed plenty of manual effort, but it has not removed operational accountability. Oracle can now automate provisioning, patching, backup, scaling, and parts of performance management. At the same time, applications are becoming more distributed, security boundaries are expanding, and AI workloads are placing new demands on enterprise data.

Oracle Key Vault: DBA Guide for TDE Keys and scenarios

A database backup can finish successfully and still fail during recovery.

That usually sounds strange until encryption enters the picture. RMAN backup is available, archive logs are available, Data Guard is in sync, but during restore someone asks the real question: where is the TDE wallet or master key?

This is where many production environments become risky. TDE wallets are present on database servers, Java keystores are owned by middleware teams, SSH keys are copied between hosts, certificates are renewed manually, and old wallet backups are kept in folders nobody wants to touch.

Sometimes It Is Not One Big Problem. It Is Everything Running in the Background.

After more than 12 years of working with production databases, I have learned that performance problems do not always begin with one terrible query.

Sometimes it is several smaller things happening together. One session is using slightly more CPU, another is holding a lock, a background job is running longer than expected, and storage latency has quietly increased. None of them looks disastrous alone, but together they make the whole system struggle.

Oracle Redo Logs: Sizing Without Guesswork

Redo log problems rarely start with a clean error message. They usually show up as slow commits, archive destinations filling faster than expected, Data Guard apply lag, or batch jobs that suddenly take longer during month-end. By the time someone checks the alert log, the database may already be switching logs too frequently, checkpointing aggressively, or waiting for archiving to catch up.

A common reaction is to increase redo log size and move on. Sometimes that is required, but it is not always the real fix. Redo log sizing controls how frequently Oracle switches logs. It does not reduce the amount of redo generated by bad SQL, unnecessary indexes, row-by-row commits, or poorly designed batch jobs.

This post looks at Oracle redo log sizing from a production DBA angle. We will check log switch frequency, estimate redo generation rate, review MTTR guidance, discuss common failure scenarios, and compare the idea briefly with PostgreSQL WAL pressure.

Oracle 26ai AWR Enhancements for DBAs

 AWR used to be simple when most databases were single-instance, single-tenant, and all important workload stayed on the primary database.

That world is mostly gone.

Today, one CDB may host multiple PDBs. Reporting may run on Active Data Guard. Read traffic may be pushed toward True Cache. Replication may be handled through GoldenGate or XStream. When performance breaks, the first question is no longer just “what was the top wait event on the database?”