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."
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.
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.
10 Modules · 30 Days
Every module is hands-on. No theory without labs.
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
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
Terraform for Database Infrastructure
- Terraform modules for VPC, subnets, security groups
- RDS and Aurora provisioning with Terraform
- Parameter groups, IAM, and secrets management
End-to-End Project
- Architecture design and planning
- Deploy full stack: app + PostgreSQL + cloud
- Documentation, runbook, and portfolio delivery
Python for DBAs
- psycopg2: connecting and querying PostgreSQL
- Automation scripts: backup, maintenance, alerts
- Monitoring performance metrics with Python
Grafana Observability
- Prometheus + Grafana stack for PostgreSQL
- Custom dashboards: connections, replication, bloat
- Alerting rules and on-call notification setup
Engineering Case Studies
- Uber MVCC — why they migrated away from PostgreSQL
- OpenAI + PgBouncer — scaling connection management
- Real production outages: replication failures & storage exhaustion
Docker for PostgreSQL
- Containerizing PostgreSQL with Docker
- Docker Compose for multi-container setups
- Persistent storage, networking, and backup strategies
Kubernetes for PostgreSQL
- Deploying PostgreSQL on Kubernetes
- StatefulSets, persistent volumes, and storage classes
- PostgreSQL operators (Zalando, CloudNativePG)
Advanced Architecture Setup
- Multi-region HA architecture design
- Connection pooling at scale with PgBouncer
- Disaster recovery planning and runbooks
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.
Enrol in Track 3: Platform Engineering
- 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