I build and operate reliable systems — then automate the repetitive parts.
Operations-focused engineer working across Linux, cloud infrastructure, automation, CI/CD, observability, production support, and reliability engineering.
I’m most effective where development meets operations: troubleshooting systems, improving deployment and monitoring workflows, automating manual work, integrating APIs, and turning operational knowledge into repeatable tooling and documentation.
Current focus: Cloud Operations · DevOps · Platform Engineering · Site Reliability · Production Support · Infrastructure Automation
Production-minded Python automation and decision-support system built around real-time data processing, state management, operational controls, monitoring, and Linux service deployment.
Python · Linux · systemd · APIs · Automation · Monitoring · State Machines · CI/CD · Reliability
Explore the project · See it in the portfolio
The public repository presents the architecture, engineering approach, and operational design while keeping sensitive runtime components private.
| Area | Tools & Technologies |
|---|---|
| Cloud & Infrastructure | AWS, EC2, Azure, Linux, VPS, systemd, SSH |
| Automation | Python, Bash, PowerShell, REST APIs, Webhooks, n8n |
| Containers & Platforms | Docker, OpenShift, Kubernetes |
| CI/CD & GitOps | GitHub Actions, Jenkins, GitLab CI, Azure DevOps, Argo CD, Git |
| Observability | Grafana, Prometheus, Dynatrace, CloudWatch, ELK, Splunk |
| Operations | Incident response, troubleshooting, RCA, production support |
| AI-assisted workflows | AI agents, LLM integrations, API-driven automation |
- Reliability first — systems should be understandable, observable, and recoverable.
- Automate repeatable work — use scripts, APIs, and workflows to reduce operational friction.
- Operate what you build — deployment, monitoring, troubleshooting, and documentation are part of engineering.
- Keep humans in control — especially where automation touches high-impact actions.