Site Reliability Engineer architecting infrastructure for social intelligence platform serving Fortune 500 brands. Processing billions of tweets faster than Elon can post them.

Business Challenge #

Scale infrastructure to process billions of social media profiles while maintaining sub-second response times and 99.9% uptime for business-critical analytics.

Technical Implementation #

Infrastructure Excellence

• GitOps workflows with Terraform enabling zero-downtime deployments
• Multi-region AWS architecture with automated failover
• Self-healing systems reducing manual intervention by 80%

Database Optimization

• MongoDB clusters optimized for 100K+ writes/second
• MySQL analytics layer with sub-second query performance
• Automated backup strategies with 15-minute RPO Observability & Automation
• Prometheus/Grafana stack with predictive alerting
• Automated incident response for common failure scenarios
• CI/CD pipelines reducing deployment time from hours to minutes

Measurable Impact #

• Reliability: Consistent 99.9% uptime SLA achievement
• Performance: 40% improvement in database response times
• Efficiency: 20+ hours/week saved through automation
• Scalability: Infrastructure auto-scales to handle 10x traffic spikes

Key Takeaways #

1. GitOps is non-negotiable: Version-controlled infrastructure prevents configuration drift
2. Monitoring predicts failures: Proper SLIs catch issues before customer impact
3. Database design determines scale: Correct architecture beats hardware upgrades
4. Automation compounds value: Every automated task multiplies team capacity
5. Coffee scales linearly: More coffee = more uptime (correlation proven)