--- title: "postgresql-dba-mastery-track-3" id: "4534" type: "post" slug: "postgresql-dba-mastery-track-3" published_at: "2026-06-26T17:02:19+00:00" modified_at: "2026-06-26T19:11:46+00:00" url: "https://labs.postgreshelp.com/postgresql-dba-mastery-track-3/" markdown_url: "https://labs.postgreshelp.com/postgresql-dba-mastery-track-3.md" excerpt: "Track 3: Platform Engineering — PostgreSQL Production Labs Track 3 of 4 · Standalone PlatformEngineering Track Design, automate, and scale […]" taxonomy_category: - "Uncategorized" --- Track 3: Platform Engineering — PostgreSQL Production LabsTrack 3 of 4 · Standalone # Platform Engineering *Track* Design, automate, and scale modern database platforms using cloud, infrastructure as code, CI/CD, observability, and advanced engineering practices. **Built for:** "I want to build and own the database platform — not just operate it." 🏗️ Standalone 30-day track — take it independently or add it to any other track [Enrol Now — ₹20,000](#enroll) [View Full Curriculum](#curriculum) Track at a Glance 30 Days of Content 10 Technology Modules K8s Kubernetes Included E2E End-to-End Project Track Investment ₹20,000 Add-on pricing for existing students Who is this for ## This Track is For You If… #### 🏭 Senior DBA Moving to Platform Role You manage databases well but want to own the platform — Kubernetes, Terraform, CI/CD, and cloud-native infrastructure. #### ☁️ Engineer Handling Oracle → PostgreSQL Migrations You need a structured, hands-on approach to migrating Oracle schemas, data, and PL/SQL to PostgreSQL using ora2pg and AWS DMS. #### 🔧 DevOps Engineer Owning Database Infrastructure You manage infrastructure but database-specific platform work (K8s operators, Terraform modules, observability) needs a dedicated track. #### 📈 DBA Targeting Staff or Principal Level You want to expand your scope beyond operations — own the architecture, drive migrations, and build platforms at scale. What You'll Achieve ## Outcomes After This Track 30 days of hands-on advanced platform engineering. #### 🔀 Oracle → PostgreSQL Migrations Run complete schema conversions and data migrations using ora2pg, AWS DMS, and PL/SQL-to-PL/pgSQL conversion techniques. #### ☁️ AWS Aurora at Scale Deploy, configure, and operate Aurora PostgreSQL with Multi-AZ, read replicas, and automated failover in a real AWS environment. #### 🏗️ Infrastructure as Code with Terraform Build reusable Terraform modules for VPC, RDS, Aurora, parameter groups, and security configurations. #### 🐳 Docker & Kubernetes for PostgreSQL Deploy and manage PostgreSQL in containers and Kubernetes using operators, Helm charts, and persistent storage. #### 📊 Grafana Observability Build production-grade monitoring dashboards, alerting rules, and SLO tracking for PostgreSQL environments. #### 🎯 End-to-End Portfolio Project Ship a complete project — from architecture to cloud deployment to monitoring — that you own and can demonstrate. Full Curriculum ## 10 Modules · 30 Days Every module is hands-on. No theory without labs. 5 Days ### Oracle → PostgreSQL Migration - Schema conversion with ora2pg - PL/SQL to PL/pgSQL conversion patterns - Data migration using AWS DMS - Data type mapping and handling exceptions - Validation, cutover, and post-migration tuning 5 Days ### AWS Aurora PostgreSQL - Aurora architecture vs RDS PostgreSQL - Cluster setup, parameter groups, endpoints - Multi-AZ and read replica configuration - Automated backups, PITR, and snapshot restore - Performance Insights and monitoring 3 Days ### Terraform for Database Infrastructure - Terraform modules for VPC, subnets, security groups - RDS and Aurora provisioning with Terraform - Parameter groups, IAM, and secrets management 3 Days ### End-to-End Project - Architecture design and planning - Deploy full stack: app + PostgreSQL + cloud - Documentation, runbook, and portfolio delivery 2 Days ### Python for DBAs - psycopg2: connecting and querying PostgreSQL - Automation scripts: backup, maintenance, alerts - Monitoring performance metrics with Python 2 Days ### Grafana Observability - Prometheus + Grafana stack for PostgreSQL - Custom dashboards: connections, replication, bloat - Alerting rules and on-call notification setup 3 Days ### Engineering Case Studies - Uber MVCC — why they migrated away from PostgreSQL - OpenAI + PgBouncer — scaling connection management - Real production outages: replication failures & storage exhaustion 2 Days ### Docker for PostgreSQL - Containerizing PostgreSQL with Docker - Docker Compose for multi-container setups - Persistent storage, networking, and backup strategies 2 Days ### Kubernetes for PostgreSQL - Deploying PostgreSQL on Kubernetes - StatefulSets, persistent volumes, and storage classes - PostgreSQL operators (Zalando, CloudNativePG) 3 Days ### Advanced Architecture Setup - Multi-region HA architecture design - Connection pooling at scale with PgBouncer - Disaster recovery planning and runbooks Combining Tracks ## When to Take Platform Engineering This track is standalone — but it pairs powerfully with other tracks. #### ✅ Take it standalone You already know PostgreSQL operations (from work or elsewhere) and specifically want platform, cloud, and automation skills. #### ✅ Add it after Track 2 You've completed Production Engineering and want to level up to Kubernetes, Terraform, and cloud-native deployments. ~46 days combined. #### ✅ All 4 tracks together The complete transformation from foundations to staff-level platform engineer. ~70 days total. Contact us for combined pricing. #### ⚠️ Not recommended as your first track If you don't have PostgreSQL administration basics, start with Track 1 or Track 2 first. Platform Engineering assumes you can operate a PostgreSQL cluster. Investment ## Enrol in Track 3: Platform Engineering ₹20,000 ≈ $240 USD · 30 days of content - Oracle → PostgreSQL migration (5 days) — ora2pg, AWS DMS, PL/SQL conversion - AWS Aurora (5 days) — Multi-AZ, read replicas, Performance Insights - Terraform (3 days) — infrastructure as code for database environments - End-to-end project (3 days) — architecture, deploy, document - Python for DBAs (2 days) — automation and monitoring scripts - Grafana observability (2 days) — dashboards and alerting - Engineering case studies (3 days) — real-world platform decisions - Docker + Kubernetes (4 days) — containerized PostgreSQL operations - Advanced architecture (3 days) — multi-region, DR, scaling 💬 **Track 3 add-on pricing:** If you're already enrolled in another track, ask about combined pricing. Oral discount available for multi-track students. [Enquire & Enrol in Track 3](#contact)