GitOps Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used GitOps
Ljubomir Obrenovic
Last position:
Senior Software Test Engineer at Keil KTM GmbH
Temporary employment
- System black-box integration tests (BBIT, IVVQ): Execution of regression, release, acceptance, and compliance tests for safety-critical brake control units in the rail industry
- Software test application & integration: Runtime configuration of software components and libraries, validation of interfaces, configuration dependencies, and component interactions
- Test automation (FEAT framework): Co-development and further development of an automated test framework for test execution, reporting, and result analysis
- Functional safety (SiL4, FuSi): Ensuring compliance with safety requirements, traceability and coverage, as well as standards compliance according to EN50126/28/29
- Test automation for communication components: Configuration and validation of fieldbus (CAN) and Ethernet-based TCMS data communication interfaces (TRDP and CIP)
- Requirements analysis & shift-left (PTC Windchill ALM): Analysis of software and system artifacts to identify gaps, ambiguities, and redundancies early in the SDLC
- Test design & test case development: Derivation of test conditions, coverage strategies, and implementation of data-driven test cases (DDT), including reusable test data fixtures
- CI/CD & automation (Python, PowerShell, Jenkins, SVN): Automation of build, test, and HIL deployment processes as well as integration into CI/CD pipelines
- Test data & configuration management (XML): Maintenance and adaptation of XML test vectors and system configurations with automated integration into test environments
- Non-functional testing: Execution of performance and load tests to assess stability and system behavior
- Agile development & defect management (JIRA, Confluence): Participation in Scrum teams, test coordination, review of test artifacts, as well as defect tracking and root-cause analysis
- Error analysis & debugging (CANoe, CANalyzer): Analysis of errors and message flows across multiple system layers (application to bus)
- Model-based analysis (UML, Enterprise Architect): Specification of SUT/SOW and support for systematic test control
- Process & test documentation: Creation of integration and test documentation according to internal quality and certification requirements
Thomas Hoefkens
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
- Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
- Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
- Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
- Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
- Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
- Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integration of RESTHeart to create a REST API for MongoDB.
- Build an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).
Vitaliy Ryumshyn
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
Teemu Suvanto
Last position:
SRE at E.On SE
- Maintained a SaaS billing platform on AWS as part of the Site Reliability Engineering (SRE) team.
- Played a key role in an AWS cloud migration project, implementing Terraform (IaC), creating CI/CD processes and pipelines, hardening images, upgrading tool versions, and developing scripts.
- Wrote documentation.
AWS Cloud migration:
- Design and implement CI/CD for deploying AWS resources using GitLab CI, Terraform, and GitOps.
- Create and configure DevOps toolchain including Jenkins, Harbor, and Vault.
- Deploy billing application, microservices, and supporting infrastructure services to Nomad clusters.
- Re-designed TLS/mTLS certificate management using Vault and Lambda.
Security (Infrastructure Hardening & Patch Management & Vulnerability Scanning):
- Managed multiple AWS accounts for Consul/Nomad/Traefik clusters (10–20 EC2 instances/account, ASG) and DevOps toolchain accounts (Harbor, Jenkins, Vault).
- Created hardened AMIs via Packer based on CIS benchmarks for Nomad, Jenkins, Harbor, and Vault; deployed using Terraform.
- Integrated Trivy via Harbor plugin for container image scanning.
- Implemented strict AWS VPC security group rules.
- Developed and maintained patching process across environments using Qualys and Wiz.
- Deployed Qualys Cloud Agent to all EC2 instances, tracked CVEs and tested patches in lower environments before rollout.
- Automated patch deployment across all AWS accounts using Terraform and GitLab CI and verified patch compliance via Qualys/Wiz dashboards.
Ales Loncar
Last position:
Senior DevOps Consultant (Freelance) at European Union Agency (via IBM)
- Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
- Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
- Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
- Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
- Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
- Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
- Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
- Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
- Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
- Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.
Alexandru Gunescu
Last position:
Head of Cloud Infrastructure at BP
- Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
- Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
- Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
- Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
- Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
- Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
- Supported development and maintenance of IT strategy aligned with business requirements
- Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
- Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
- Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
- Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
- Developed a two-year infrastructure technology roadmap yielding 25% cost savings
- Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics
Daniel Carton
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Max Ritter
Last position:
Cloud (AWS) | AI | DevOps | Data at Boehringer Ingelheim
- Architected and implemented an enterprise-grade AI Agent Platform leveraging Retrieval Augmented Generation (RAG) architecture to enhance clinical data insights.
- Established robust CI/CD pipelines for LLM applications using CDK and Jenkins, significantly reducing deployment times.
- Implemented comprehensive observability solutions that increased agent reliability across pharmaceutical environments.
- Designed scalable AI workflows with advanced orchestration that optimized context handling for enterprise data sources.
- Technologies: AI Agents (LangChain, LangGraph, Bedrock, Smolagents, Streamlit); LLM Operations (Tracing, Testing, Evaluation, LangSmith, LangFuse); Infrastructure-As-Code (AWS CDK, Terraform, Typescript, Jenkins); Vectors, Embeddings, RAG (OpenSearch, pgvector, PDF Extraction)
Frank Eppink
Last position:
DevOps at Lauck-IT
Operations and extensions of Azure DevOps pipelines
Operations and extensions of AWS services
Citrix (Windows 10, Bitwarden)
AWS: ECR, EKS, CloudFront CDN, Route 53, VPC peering and CNI upgrade, Atlas MongoDB, S3 buckets, static website hosting
Azure: build and deploy with DevOps pipelines
Bela Bocsak
Last position:
Full Stack Lead Developer, Backend Architect at Telefonica (O2)
The software supports the complete planning and approval of antennas for mobile telephony.
The system was implemented using an event-driven microservice architecture for cloud-native deployment with Quarkus on the backend, Kafka for communication, and Angular for the frontend. Services run on Kubernetes in Google Cloud. A special challenge was synchronizing with the legacy system still used by some users.
Christian Trutz
Last position:
JEE Software Engineer, DevOps Engineer at AKDB
- JEE Software Engineer
- DevOps Engineer
- Java, JEE, JBoss/WildFly, Vaadin, CI/CD Pipelines, Jenkins, Maven, Git, Oracle database, MSSQL Server database
Janusz Mazurek
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Discover over 15,000 top freelancers
Statistics of experts using GitOps
Aggregated from the professional profiles of matched freelancers.
Experience
26 years (Germany: 18 years)
Position duration
2.4 years (Germany: 2 years)
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Manufacturing, Automotive
Certification focus areas
Information Technology, Operations, Product Development
Bachelor's degree or higher
100% (Germany: 87%)
Master's degree or higher
70% (Germany: 47%)
Doctorate
20% (Germany: 8%)
Certifications per freelancer
4
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Munich using GitOps
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it does
GitOps is a way to run infrastructure and application delivery from Git as the source of truth. Teams use it to keep Kubernetes changes reviewable, repeatable, and easy to roll back. It fits release flows where control and traceability matter.
Common tools
- Argo CD for continuous delivery and sync
- Flux for automated reconciliation
- Helm or Kustomize for environment overlays
- Kubernetes manifests, policies, and secrets handling
Strong specialists know how these parts work together and where drift appears. They can keep deployment rules clear without turning the pipeline into a maze.
Where it helps
GitOps is a good fit for platform teams, regulated environments, and multi-cluster operations. It is also useful when several specialists touch the same release process and the team needs clear change history. In Munich, it often comes up in enterprise IT, SaaS, and industrial software teams.
When to bring in help
Bring in freelance expertise when deployments are flaky, cluster config has drifted, or a move to Argo CD or Flux needs a clean setup. Companies also hire specialists for policy design, repo structure, secret management, and recovery planning. Short-term help is common when the internal team needs a fast, low-risk reset.
What good specialists do
- Set up clear repo and environment layouts
- Define safe promotion and rollback flows
- Reduce manual changes outside Git
- Document how teams review and approve changes
Good GitOps professionals work carefully with app, platform, and security teams. They know how to keep delivery simple while protecting compliance and uptime.
Skills that matter
A strong GitOps specialist understands Kubernetes, YAML, CI/CD, and access control. They also need good judgment around branching, secrets, policy checks, and sync strategy. The best ones explain trade-offs in plain language and leave behind a setup the team can run without guesswork.
Frequently asked questions
Everything clients usually want to know about GitOps, in one place.
GitOps is used to manage infrastructure and application delivery through Git changes. Teams rely on it for Kubernetes deployments, configuration drift control, and safer promotions between environments. It is especially useful when several specialists need a shared, auditable process.
GitOps still uses CI/CD, but it shifts deployment decisions into Git and a reconciler such as Argo CD or Flux. Classic pipelines often push changes directly into targets, while GitOps keeps the desired state in repositories. That makes review, rollback, and audit trails easier to manage.
A GitOps setup often includes Kubernetes, Argo CD, Flux, Helm, and Kustomize. Many projects also need secret handling, policy checks, and container registry integration. A good specialist can explain which pieces are essential and which ones are optional.
A strong GitOps freelancer should be comfortable with Kubernetes manifests, YAML, CI/CD, and release workflows. Familiarity with cloud networking, access control, and policy enforcement also helps. If the project is in Munich and the team works on-site, clear communication in English or German can matter as much as the tooling.
A GitOps project needs enough expertise to avoid bad repo structure, unsafe sync rules, and confusing approval paths. Smaller setups may only need a focused specialist for design and handover, while complex environments benefit from deeper platform knowledge. The right fit depends on how many clusters, teams, and release paths are involved.
Yes, GitOps is often a good match for remote collaboration because most work happens in repositories, pull requests, and configuration reviews. A remote specialist can usually set up the process, clean up manifests, and document operating rules without being on-site. On-site time only becomes important when the team needs hands-on alignment with local stakeholders or legacy systems.
A solid GitOps implementation has a clear source of truth, predictable sync behavior, and a rollback path the team trusts. Look for clean separation of environments, sensible use of Argo CD or Flux, and minimal manual changes outside Git. Good documentation is a strong sign that the setup will survive after handover.
Choose GitOps when you need traceability, repeatability, and strong control over Kubernetes changes. It is a strong fit for teams that manage many environments or need consistent approval steps. If the main need is simple, one-off deployment automation, a lighter CI/CD flow may be enough.
The average hourly rate of freelancers in Munich, Germany who have used GitOps in their recent projects is 105 €, which corresponds to a daily rate of about 840 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used GitOps in their recent projects, 100% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Munich, Germany who have used GitOps in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Munich, Germany who have used GitOps in their recent projects are German (100%), English (92%), and Spanish (17%).
The most common industries among freelancers in Munich, Germany who have used GitOps in their recent projects are Information Technology (100%), Manufacturing (75%), and Automotive (67%).
The most common business areas among freelancers in Munich, Germany who have used GitOps in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (67%).
Main locations of FRATCH Experts, who have recently used GitOps
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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