Database Reliability Engineering

Principal Database Engineer | Cloud Data Architect | SRE

Production-grade platform for building self-healing, high-scale, and resilient database systems

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Key Highlights

• VLDB systems (>100TB)
• 99.99% uptime architectures
• Autonomous failover systems
• Zero-downtime migrations
• Performance governance (CI/CD enforced)
• 30–70% performance improvements
• 30–50% cost optimization

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Why This Repository Stands Out

Most repositories show pipelines.

This repository demonstrates system-level engineering:

• Preventing failures (DDL Guardrails)
• Detecting failures (Observability + Monitoring)
• Recovering automatically (Failover Systems)
• Enforcing performance (CI/CD Governance)
• Migrating at scale (100TB+ workloads)

This is a production blueprint, not a tutorial.

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Architecture Overview

flowchart LR
A[Sources / APIs] --> B[Bronze Layer]
B --> C[Silver Layer]
C --> D[Gold Layer]
D --> E[Analytics]
E --> F[Monitoring]
F --> G[Alerts]

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Autonomous Failover Architecture

flowchart LR
A[Health Check] --> B[Heartbeat Logic]
B --> C[Event Emitter]
C --> D[Dispatcher]
D --> E[Execution Layer]
E --> F[Recovery Action]

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System Layers

Layer	Capability
Data Platform	ETL, Medallion Architecture
Database Engineering	Query tuning, partitioning
Reliability	Failover, monitoring
Governance	Performance budgets, DDL guardrails
Migration	100TB+ enterprise workflows

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Quick Start

git clone https://github.com/nitish120789/database-reliability-engineering.git
cd database-reliability-engineering
docker-compose up

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Repository Navigation (Start Here)

Use this map to quickly find the right content by objective:

• Day-2 DBA/DBRE operations:
  • database_admin/
• Data platform and ETL engineering:
  • data-platform/, data_engineering/, pipelines/
• HA/DR and failover automation:
  • ha-failover/, cloud-migration/, infrastructure/
• Architecture and reference guides:
  • docs/
• Performance and guardrails:
  • db-optimization/, db-guardrails/

Canonical governance documents:

• Gap analysis and roadmap:
  • docs/repository-gaps-and-improvement-plan.md
• Taxonomy and naming conventions:
  • docs/repository-taxonomy.md
• Standard runbook template:
  • database_admin/templates/runbook_template.md

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Runbooks and Reliability Standards

Operational runbooks are the primary resource for incident response and operational procedures. Each follows a standardized format (Summary, Impact, Preparation, Procedure, Verification, Rollback, Communication, Evidence).

Critical Path Runbooks (Sev-1 Incidents)

• Incident Response - PostgreSQL - stabilize service degradation; <10 min target
• Lock/Deadlock Triage & Resolution - resolve blocking/deadlock; <5 min target
• Failover Procedure - promote replica; <15 min target
• Disaster Recovery - major failure recovery; <60 min target (Tier-1)

Operational Procedures

• Change Management & Release - safe schema/config changes with risk gates
• Backup Verification & Restore Drill - prove RTO/RPO; monthly cadence
• Symptom-Driven Troubleshooting Decision Tree - diagnostic triage by symptom

Complete runbook index: database_admin/sre/runbooks/README.md

Operating Standards (Cross-Platform)

• Security & Compliance Operating Standard - mandatory controls, access, encryption, audit, patch SLAs
• Capacity & FinOps Operating Standard - forecasting, optimization, cost governance
• Alerting & Monitoring Configuration - alert hierarchy, SLO thresholds, operationalization

Minimum reliability controls expected:

• SLO/RTO/RPO context and targets
• Safety gates and approval requirements
• Preconditions and risk gates
• Verification criteria and success conditions
• Rollback or fallback path
• Evidence collection for audit and postmortems
• Automation opportunities identified

Learning and Interview Path

Suggested progression for structured learning and interview preparation:

1. Foundation:
   • database_admin/estate_operations/00_governance/
   • database_admin/estate_operations/02_observability/
2. Reliability operations:
   • database_admin/sre/runbooks/
   • database_admin/backup/
   • database_admin/replication/
3. Performance and scaling:
   • db-optimization/
   • database_admin/indexing/
   • database_admin/performance/
4. Architecture and migration design:
   • docs/architecture/
   • cloud-migration/
   • migrations/

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Core Capabilities

Data Engineering

• Medallion architecture (dbt + dlt)
• End-to-end pipelines

Database Engineering

• Partitioning strategies
• Query optimization
• HA/DR replication

Platform Engineering

• Terraform modules
• Kubernetes deployment
• Docker sandbox

Observability

• Pipeline freshness
• Schema drift
• Data contracts

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Performance Governance (CI/CD Gate)

• Every pull request triggers benchmark execution
• Query performance compared against baseline

• 10% regression automatically fails pipeline

Outcome

• Prevents performance degradation
• Enforces database SLAs
• Aligns engineering with cost efficiency

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Autonomous Failover System (Azure SQL)

• Health checks monitor availability
• Heartbeat detects repeated failures
• Event-driven architecture triggers recovery
• Dispatcher routes execution

Outcome

• Zero manual intervention
• Faster recovery response
• Reduced operational risk

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DDL Guardrails (Safe Schema Changes)

• Pre-check policies validate system load
• Guardrails prevent risky schema changes
• Shadow migrations for large tables
• Threshold-based monitoring

Outcome

• Eliminates lock-related outages
• Enables safe schema evolution
• Engineered deployment safety

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Key Projects

• Retail ETL Pipeline → Batch + streaming ingestion with validation
• Oracle → PostgreSQL Migration → 100TB+ with ora2pg + CDC
• SQL Server → Azure SQL → Data Box + Parquet + ADF
• Autonomous Failover System → Event-driven recovery pipeline

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Real-World Use Cases

• Financial transaction systems (low latency + HA)
• Retail analytics pipelines (batch + streaming)
• IoT ingestion systems (high throughput)
• Enterprise cloud migrations (100TB+ data)

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Benchmark Snapshot

Format	Query Time	Storage
Parquet	1.2s	1.0x
Avro	2.0s	1.3x
Delta	1.3s	1.1x

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Why Engineers Star This Repo

• Production-grade architecture patterns
• Covers Data + DBA + SRE together
• Includes failure scenarios and solutions
• Shows automation, not just scripts
• Designed for scale, not demos

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CI/CD

GitHub Actions enabled

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Contributing

Pull requests are welcome