Oracle Performance Engineering Guide: AWR, ASH and SQL Monitor in 19c and 23ai

Master the essential tools for diagnosing and resolving real-world performance issues

Date: Tuesday, March 10, 2026

Author: Chetan Yadav

Read Time: 20-24 minutes

Estimated Reading Time: 20-24 minutes

Real-World Performance Diagnostics - From Baseline Metrics to SQL Execution Plans

Production Environment Context

Oracle Database 19.18.21 with Oracle Grid Infrastructure 19.18 | 3-Node RAC Cluster | 8.5 TB OLTP Database | 3,200+ concurrent sessions | Peak TPS: 2,100 | 24/7 mission-critical

It's 3 AM on a Tuesday. The monitoring dashboard lights up red. Response times have jumped from 200ms to 5+ seconds. Users are reporting timeouts on critical batch jobs. Your manager's Slack message is already waiting: "Database issue?" You log into the database, check CPU utilization (45%), memory (78% used), disk I/O latency (120ms). Everything looks elevated but not catastrophically bad. Where do you even start investigating?

This is where AWR (Automatic Workload Repository), ASH (Active Session History), and SQL Monitor become your diagnostic lifeline. Over the past 15+ years managing large-scale Oracle databases in production, I have debugged thousands of performance incidents—from runaway SQL queries consuming 800GB of I/O in 10 minutes, to massive lock contention blocking 400+ sessions, to redo log I/O stalls freezing the entire database. These three tools have never failed me. They transform performance troubleshooting from educated guessing into data-driven root cause analysis.

In this guide, you will learn the exact methodology I use in production: how to leverage AWR, ASH, and SQL Monitor to identify root causes in under 15 minutes, pinpoint the exact problematic SQL statements, analyze their execution plans, and implement fixes. Whether you're managing a 3-node RAC cluster running Oracle 19c or a cloud-native 23ai environment, the diagnostic principles remain constant.

Let's dig into real production scenarios and techniques.

Oracle Database 26ai: New Features DBAs Should Test First in 2026

Oracle Database 26ai: New Features DBAs Should Test First

AI-Powered Automation, Vector Search, and Production-Critical Features

📅 February 26, 2026

👤 Chetan Yadav - Senior Oracle & Cloud DBA

⏱️ 12-13 min read

⏱️ Estimated Reading Time: 12–13 minutes

🤖 Oracle 26ai - The Database That Tunes Itself While You Sleep

The Oracle Database 26ai beta went live last week. My manager sent the email: "Download it. Test it. Report back on Monday with what breaks."

I spent 72 hours testing every major feature Oracle advertised. Some lived up to the hype. Others... didn't. Here's what you actually need to test first, based on what will impact production databases most.

Oracle 26ai isn't just another version bump with minor bug fixes. This release introduces AI-driven query optimization, native vector search for machine learning workloads, property graph enhancements, and automated schema evolution. If your organization is considering adopting any of these features, this guide shows you exactly what to test and what production gotchas to watch for.

This isn't marketing hype—it's a DBA's practical testing roadmap based on early access to 26ai. If you're evaluating whether to upgrade, these are the features that matter most and the tests that separate real value from vendor promises.

⏱️ Reading Time: 10–12 minutes

Top-10 Wait Events Query (Universal Database Performance Tuning)

It’s a peak business hour. Users complain the application is “slow,” dashboards look normal, CPU is not maxed out, and storage graphs look fine. Someone asks the classic question:

“The database is up… so why is everything waiting?”

This is the exact moment where strong DBAs look at wait events instead of guessing. Understanding the top-10 wait events is not just a tuning skill —it’s a career-defining mindset.