Key Projects & Achievements
Enterprise CI/CD Pipeline Modernization
Duration: 18 months (2022-2024) | Client: Ericsson Telecommunications
Situation: Legacy monolithic deployment process causing 4-hour release cycles and frequent production failures for mission-critical telecommunications infrastructure.
Task: Transform deployment architecture to support 50+ microservices with zero-downtime deployments and automated rollback capabilities.
Action:
- Migrated from monolithic Jenkins setup to cloud-native Spinnaker deployment pipeline
- Standardized deployments with Helm chart libraries for consistent environment provisioning across the microservice fleet
- Built comprehensive monitoring stack with Prometheus, Grafana, and custom alerting
- Established automated testing gates including security scanning and performance validation
Result: Reduced deployment time from 4 hours to 15 minutes, achieved 99.9% deployment success rate, eliminated production rollbacks through automated quality gates.
Kubernetes Security Hardening Initiative
Duration: 8 months (2023) | Scope: Multi-cloud production environments
Situation: Security audit revealed 127 critical vulnerabilities across Kubernetes clusters handling sensitive telecommunications data.
Task: Implement comprehensive security framework ensuring GDPR compliance and telecommunications industry standards.
Action:
- Deployed network policies and pod security standards across all production clusters
- Implemented automated vulnerability scanning with Falco and custom monitoring solutions
- Built security-focused CI/CD pipeline with container image scanning and policy enforcement
- Created automated remediation workflows for common security issues
Result: Reduced security incidents by 70%, achieved 100% compliance with telecommunications security standards, implemented zero-trust network architecture serving 10M+ users.
Elasticsearch Performance Engineering
Duration: 6 months (2021-2022) | Academic Research Project
Situation: University thesis project investigating Elasticsearch performance characteristics under varying load conditions for real-time analytics applications.
Task: Design comprehensive load testing framework and performance analysis methodology for distributed search applications.
Action:
- Built custom load testing infrastructure using Python and distributed testing framework
- Implemented comprehensive metrics collection and analysis pipeline
- Conducted performance analysis across different cluster configurations and data volumes
- Developed optimization recommendations based on empirical performance data
Result: Published performance optimization guidelines improving query response times by 40%, established benchmarking methodology adopted by university’s distributed systems course.
Open-source / reference implementations
Reference architectures I maintain in the open — production patterns, currently a work in progress. Run them, read them, or use them as a starting point.
| Repository | What it solves |
|---|---|
| aws-platform-baseline | Multi-account AWS landing zone in Terraform — VPC, IAM, SCPs, GuardDuty, cost controls |
| eks-platform-reference | Production EKS platform — ArgoCD GitOps, Karpenter, kube-prometheus-stack, OPA |
| aws-finops-toolkit | AWS cost audit — finds waste, estimates savings, LLM-generated remediation report |
| cicd-pipeline-templates | Reusable GitHub Actions — Docker build/scan, Terraform gates, Helm deploy, SAST |
| llm-infra-aws | AWS patterns for LLM workloads — managed API proxy and self-hosted GPU on EKS |
More at github.com/Botoxx.