Frankfurt am Main, Germany

David Zhorzholiani

System Engineer · DevOps & Infrastructure Automation

System Engineer with 4+ years of experience in DevOps automation, infrastructure management, and cloud technologies. Hands-on with large-scale server environments, Infrastructure as Code, container orchestration, and CI/CD pipeline automation.

Python

Usage

Automation scripts, backend development, and system monitoring tools.

Optimization

Implemented efficient data processing algorithms for faster execution times.

Rust

Usage

High-performance network analyzers and systems-level tooling.

Optimization

Zero-cost abstractions for near-native performance in containerized environments.

Docker

Usage

Containerizing applications for consistent deployment across environments.

Optimization

Optimized Docker images through multi-stage builds for faster deployment.

Terraform

Usage

Infrastructure as Code for reproducible and version-controlled deployments.

Optimization

Created modular Terraform modules for faster and more reliable deployments.

Ansible

Usage

Configuration management and automated deployment across Linux/Windows servers.

Optimization

Developed idempotent playbooks ensuring consistent server states.

VMware

Usage

Provisioning new VMs, applying standardized configurations, orchestrating network and security settings, and integrating backup/snapshot routines into IaC automated workflows.

Optimization

High availability, performance tuning, and observability for hybrid setups running on VMware and public cloud.

Linux

Usage

Server administration, security hardening, and performance tuning.

Optimization

Custom kernel optimizations for improved system performance.

Networking

Usage

Network configuration, proxy setup, firewall management, and security monitoring.

Optimization

Implemented network segmentation and security policies to reduce attack surface.

Shell Scripting

Usage

Automating routine tasks, system monitoring, and deployment pipelines.

Optimization

Created comprehensive monitoring scripts to reduce manual intervention.

Experience

System Engineer(Part-time)

September 2025 -- Present

Vinci Energies · Frankfurt am Main, Germany

  • Manage enterprise server infrastructure with health monitoring (Checkmk) and vulnerability scanning (Rapid7).
  • Configure networking, proxy settings, and handle SSL/TLS certificate management and renewal.
  • Administer Windows and Linux environments using Microsoft Intune for endpoint management.
  • Automate configuration management with Ansible and provision infrastructure with Terraform.
  • Optimize system performance and ensure high availability across hybrid infrastructure.
AnsibleTerraformLinuxWindows ServerCheckmkRapid7Microsoft IntuneSSL/TLSVMware Aria Automation

System Engineer Intern

June 2024 -- June 2025

Stonebranch · Frankfurt am Main, Germany

  • Investigated system/application logs (Linux,Windows,z/OS) to diagnose failures and breaches.
  • Used VMware VM to recreate client environments for troubleshooting and testing purposes.
  • Automated routine system tasks and monitoring workflows with Bash and Python.
  • Streamlined client workflows (deployment, configuration, and monitoring) using Stonebranch Universal Automation Center.
Multi-OS administrationVMware ESXi/vSphereBashPythonSQLStonebranch Universal Automation Center

Software Engineer

November 2021 -- April 2022

Brandergate · Tbilisi, Georgia

  • Developed features for an Artificial Branding Intelligence platform using Next.js and Django REST Framework.
  • Built REST APIs, managed SQL databases, and collaborated with cross-functional teams.
Next.jsDjangoDjango REST FrameworkSQLPython

Python Developer

February 2021 -- June 2021

Propertify · Tbilisi, Georgia

  • Developed a property investment platform with Python and Django.
  • Integrated payment gateways and databases, deployed on AWS.
  • Improved code efficiency through reviews and adherence to best practices.
PythonDjangoAWSPostgreSQL

Skills

Languages

PythonJavaScriptJavaRustC++BashPowerShell

DevOps & IaC

TerraformAnsibleDockerKubernetesJenkinsGitLab CIAWXIaC

Infrastructure

Linux (yum, dnf, apt)Windows ServerVMware ESXi/vSphereVMware Aria AutomationHyper-V

Cloud

AWSAzureCloudflare

Monitoring & Security

CheckmkRapid7Microsoft IntuneSSL/TLS ManagementPrometheusGrafana

Backend & Data

DjangoNode.jsSQLitePostgreSQLInfluxDBSupabase

Networking

ProxyVPNFirewall ManagementNetwork TroubleshootingNetwork Segmentation

Some of my projects

see more on github

ayaFlow

A high-performance, eBPF-based network traffic analyzer written in Rust. Designed to run as a sidecarless DaemonSet in Kubernetes.

  • eBPF-native capture -- hooks directly into the kernel's traffic control subsystem using Aya, no libpcap or privileged sidecar required.
  • Sidecarless DaemonSet -- one pod per node instead of one per application pod.
  • Real-time monitoring via REST API + WebSocket streaming, with SQLite persistence and configurable data retention.
  • Native Prometheus /metrics exporter and IP allowlist for API/dashboard access.
RusteBPFAyaKubernetesPrometheus
View on GitHub

LightShark

Network traffic analysis suite in two flavors.

Full edition

Captures packets with TShark, stores metadata in InfluxDB, and visualizes through Grafana dashboards.

PythonTSharkInfluxDBGrafanaDocker
View Full on GitHub

Mini edition

Rust-based sidecar with near-zero overhead for real-time traffic inspection in Docker and Kubernetes.

RustDockerKubernetesNetworking
View Mini on GitHub

SimpleAutomatica

A simple, secure, lightweight web interface for triggering existing Ansible playbooks on a Linux server.

  • Safe server-side automation workflows with minimal UI overhead.
  • Security-conscious design with role-based access and audit logging.
AnsibleLinuxDevOpsAutomation
View on GitHub

eigenFaces

Interactive Streamlit application that visualizes the Eigenfaces facial recognition algorithm and demonstrates PCA-based dimensionality reduction.

  • Educational tool for classical machine learning and linear algebra concepts.
  • Step-by-step visualization of training, projection, and recognition.
PythonStreamlitPCAMachine Learning
View on GitHub
InterestsData Center Engineering/Quantum Computing/Cloud Architecture/DevOps Best Practices/Fitness & Strength Training/Cooking/Gaming/Emerging Technologies