Henrik Jess

2023 - Present

LRU A/S: Enterprise Azure-to-Kubernetes Migration

Lead DevOps Engineer / Solutions Architect

The Challenge:

Migrate 50+ legacy Azure Web Apps to a modern Kubernetes platform while maintaining zero downtime and improving operational efficiency. The existing infrastructure had manual deployment processes, limited observability, and complex dependency management.

The Solution:

• Designed phased migration strategy with parallel operation capability
• Built reusable Bicep module library for Azure AKS and supporting services
• Implemented GitOps workflows with Argo CD for declarative deployments
• Created Python automation tooling for migration validation and rollback
• Established comprehensive monitoring with Prometheus and Grafana
• Implemented automated testing and staged environment promotion

Technologies Used:

Azure AKS, Bicep IaC, Terraform, Docker, Kubernetes, Argo CD, Helm, Azure DevOps, Python automation, Prometheus, Grafana, Azure Monitor, Redis, PostgreSQL

Measurable Outcomes:

• 70% reduction in deployment time (hours → minutes)
• 50+ applications successfully migrated with zero downtime
• Enhanced security posture with RBAC and network policies
• Improved observability with centralized logging and metrics
• Cost optimization through resource right-sizing and autoscaling

Key Learnings:

Phased migrations with parallel operation reduce risk significantly. Reusable IaC modules accelerate subsequent migrations. Comprehensive monitoring before cutover prevents surprises. Team collaboration across engineering, security, and business stakeholders is critical for success.

1994 - Present (30+ Years)

Enterprise-Grade Self-Hosted Infrastructure

Infrastructure Architect & Systems Administrator

The Challenge:

Operating production-grade infrastructure continuously since 1994, evolving from bare-metal Unix servers to modern cloud-native architecture. This 30-year journey demonstrates deep understanding of infrastructure fundamentals and ability to adopt new technologies while maintaining operational excellence.

Infrastructure Evolution:

• 1994-2000: Bare-metal Unix servers, BIND9 DNS, Sendmail, NFS
• 2000-2010: Virtualization (Xen, KVM), PostgreSQL clusters, Postfix
• 2010-2020: Containerization (Docker), configuration management (Ansible, Chef)
• 2020-Present: Kubernetes orchestration, service mesh, GitOps, IaC

Current Production Services (10+):

• DNS Infrastructure: PowerDNS authoritative + BIND9 recursive, automated zone management, DNSSEC
• Container Platform: Kubernetes with service mesh (Traefik/Consul)
• Databases: PostgreSQL clusters, MariaDB, Redis caching
• Communication: Postfix mail server, SMTP relay with SPF/DKIM/DMARC
• Version Control: Gitea self-hosted Git server with CI/CD integration
• Secrets Management: HashiCorp Vault for credentials and certificates
• Business Applications: Odoo ERP (self-hosted and customized)
• Monitoring: Prometheus metrics, Grafana dashboards, custom alerting
• Storage: NFS file servers, automated backup systems
• Operating Systems: Debian/Ubuntu Linux fleet management

Technologies Used:

Kubernetes, Docker, PowerDNS, BIND9, PostgreSQL, MariaDB, Redis, Postfix, Gitea, Vault, Odoo ERP, Prometheus, Grafana, NFS, Debian/Ubuntu Linux, Ansible, Traefik, Consul

Measurable Outcomes:

• 99.9% uptime over multiple years
• 10+ production services running 24/7
• Zero data loss through automated backup strategies
• Cost-effective self-hosted infrastructure vs cloud
• Full control over entire technology stack

Key Learnings:

Long-term infrastructure operation teaches patience and planning. Automation is essential but must be maintainable. Documentation saves future-you countless hours. Understanding fundamentals (networking, storage, OS internals) never goes out of style. The best infrastructure is the one you don't notice - it just works.

2024

RefactorMCP: Python Code Quality Platform

Creator & Lead Developer

The Challenge:

Modern Python projects need automated code quality improvements beyond basic linting. Existing tools require manual intervention and don't integrate with modern AI workflows.

The Solution:

• Built MCP (Model Context Protocol) server for AI-assisted refactoring
• Implemented automated complexity analysis and refactoring suggestions
• Created type hint inference using MyPy integration
• Developed docstring generation with multiple style support (Google, NumPy, Sphinx)
• Added design pattern detection and application
• Integrated with Claude AI for intelligent code improvements

Technologies Used:

Python, MCP Protocol, MyPy, AST parsing, Radon complexity, FastMCP framework

Measurable Outcomes:

• Open source available on GitHub
• 15+ refactoring tools in single platform
• AI-ready integrates with Claude/LLM workflows
• Type-safe MyPy-powered type inference
• Production-ready used in real projects

Key Learnings:

Building developer tools requires understanding real workflow pain points. The MCP protocol enables new AI-human collaboration patterns. Type systems catch bugs early but need good tooling. Good documentation is as important as good code. Open source contributions create learning opportunities for everyone.

2005-2012

FLSmidth: International Industrial Automation

Automation Engineer

The Challenge:

Commission and optimize cement production facilities in challenging international environments (Qatar, Egypt, Nigeria). Work with multi-cultural teams under tight deadlines and harsh conditions.

The Solution:

• Implemented LEAN methodology for systematic problem-solving
• Coordinated multi-cultural teams across different time zones
• Systematic troubleshooting of industrial control systems
• On-site commissioning and training of local staff

Technologies Used:

Industrial automation systems, PLC programming, Electrical engineering, SCADA systems, LEAN methodology

Measurable Outcomes:

• Successful international project delivery in challenging environments
• Cross-cultural collaboration with teams in Qatar, Egypt, Nigeria
• Operational resilience under challenging conditions
• Systems thinking applied to complex industrial processes

Key Learnings:

Electrical engineering background provides systematic approach to troubleshooting. LEAN methodology applies to any complex project. International experience builds cultural awareness and adaptability. Industrial systems taught me the importance of reliability and fault tolerance - lessons that carry directly into modern DevOps.