Advanced Database Administration & Performance Engineering

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Duration 5 days – 35 hrs

 

Overview

 

This advanced, hands-on training equips database administrators, engineers, and support teams with the skills to diagnose and optimize database performance, design high availability (HA) setups, implement backup & recovery, and apply security best practices for both PostgreSQL and Microsoft SQL Server.

 

Participants will work through real production scenarios: slow queries, index bloat, blocking/deadlocks, replication lag, storage/IO bottlenecks, and recovery drills. The course emphasizes repeatable troubleshooting playbooks and practical tuning techniques aligned with enterprise operations.

 

Objectives

 

  • Establish performance baselines and identify bottlenecks (CPU, memory, IO, locks, network).
  • Analyze query execution plans and apply systematic query optimization techniques.
  • Design and validate effective indexing strategies (including composite/covering indexes).
  • Tune database configuration parameters safely (PostgreSQL + SQL Server best practices).
  • Detect and resolve blocking, deadlocks, and concurrency-related slowdowns.
  • Implement HA and replication approach appropriate to enterprise requirements.
  • Execute backup, restore, and point-in-time recovery (PITR) / disaster recovery drills.
  • Apply security best practices: roles/permissions, encryption options, auditing, hardening.
  • Troubleshoot production incidents using a structured playbook and evidence-driven approach.
  • Create operational runbooks/checklists for monitoring, maintenance, and recovery readiness.

Target Audience

 

  • Database Administrators (DBAs)
  • Platform/Infrastructure Engineers supporting databases
  • DevOps/SRE teams managing database reliability
  • Application Developers responsible for performance-sensitive systems
  • L2/L3 Support Engineers handling production incidents

 

Prerequisites

  • Working knowledge of SQL (SELECT/JOIN/GROUP BY, basic DDL/DML)
  • Basic understanding of database concepts (transactions, locks, indexes)
  • Familiarity with either PostgreSQL or SQL Server administration basics (recommended)
  • Comfortable with command-line and basic OS concepts (Windows/Linux)

 

Course Outline

 

Day 1 — Performance Tuning Foundations + Baseline & Observability

  • Performance tuning mindset: measure → hypothesize → change → validate
  • Key bottleneck categories: CPU, memory, IO, locks, network, connection pools
  • Workload profiling: OLTP vs reporting vs mixed workloads
  • Baseline creation: KPIs, throughput, latency, wait events

 

PostgreSQL Focus

  • Collecting performance signals (pg_stat views, slow query logging)
  • Intro to explain/analyze, buffers, timing interpretation

 

SQL Server Focus

  • DMVs for performance diagnostics
  • Query Store overview and practical usage patterns

 

Labs

  • Build a baseline and identify top wait/lock/query contributors
  • Turn on appropriate logging/telemetry without “killing” production performance

 

Day 2 — Query Optimization & Execution Plan Analysis (Both Platforms)

  • Reading execution plans: scans vs seeks, joins, cardinality estimation
  • Common anti-patterns: non-sargable predicates, implicit conversions, RBAR, OR conditions
  • Parameter sensitivity / plan regression concepts

 

PostgreSQL

  • EXPLAIN (ANALYZE, BUFFERS), planner behavior, work_mem implications

 

SQL Server

  • Actual vs estimated plans, stats usage, parameter sniffing mitigation patterns

 

Labs

  • Optimize slow queries using plan analysis
  • Fix plan regressions and validate improvements with repeatable tests

 

Day 3 — Indexing Strategies, Statistics & Maintenance

  • Index design principles: selectivity, composite order, covering strategies
  • When NOT to index; write-heavy vs read-heavy tradeoffs
  • Statistics and histogram concepts; stale stats impact
  • Maintenance: bloat, fragmentation, vacuum/reindex, index rebuild/reorg

 

PostgreSQL

  • Bloat detection, VACUUM/ANALYZE strategy, autovacuum tuning basics

 

SQL Server

  • Index fragmentation management, stats update strategies, fill factor concepts

 

Labs

  • Design indexes for real query patterns
  • Fix performance caused by bloat/fragmentation and validate gains

 

Day 4 — High Availability, Replication, Backup & Recovery (Drill Day)

  • HA vs DR vs backups: what each solves
  • RPO/RTO design considerations
  • Replication models and failure modes; detecting replication lag

 

PostgreSQL

  • Streaming replication concepts
  • Backup types and PITR concepts (WAL); recovery verification

 

SQL Server

  • HA/replication options overview (enterprise patterns)
  • Backup chain (full/diff/log), restore strategies, point-in-time restore concepts

 

Labs

  • Simulate failure, perform controlled failover (lab scenario)
  • Execute restore + recovery drill and validate application functionality

 

Day 5 — Security Best Practices + Real-World Troubleshooting Capstone

  • Security hardening checklist
    • Roles/least privilege, separation of duties
    • Connection security, secrets handling, auditing basics
  • Common production incidents
    • Lock storms, deadlocks, runaway queries
    • Connection saturation, memory pressure, tempdb/temp spills
    • Disk full, corruption signals (what to do first)

 

Capstone Lab (Scenario-Based)

  • “Production outage” simulation:
    • Diagnose symptoms → collect evidence → apply fixes → validate → document root cause
  • Create a team runbook:
    • Monitoring checklist, escalation flow, recovery steps, preventative maintenance plan

 

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