Minikube Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Minikube
Tan Pham
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Patrick Waldschmitt
Last position:
AI Software Engineer at IppenMedia
- Analysis
- Consulting
- Software design
- Development
- Automation
- Testing
- Deployment
- Architecture, development and deployment of various proof-of-concept applications around the integration of current AI interfaces including conversational, realtime voice, images and videos
- Developed best practices for working with agentic systems and AI in practice
- Created code templates
Martin Grambauer
Last position:
SAP Test Data Management Consultant at Siemens AG
End-to-end quality assurance in a global S/4HANA transformation program.
Automated test data setup, evaluation of search and generation solutions, and PoC execution (K2View, EPI-USE).
Coordination between Siemens teams and external partners, and structured knowledge transfer to internal stakeholders.
Created a basis for PoC decisions and sped up tool selection.
Standardized test data provisioning and noticeably reduced lead times.
Established governance for test data processes (policies, roles, KPIs).
Sustainable know-how transfer: empowered internal teams to operate solutions on their own.
Methods & technologies: S/4HANA, SAP, K2View, EPI-USE, test data management, data masking, data provisioning, test strategy, test management, coaching & enablement, Azure DevOps, Microsoft Office 365, Gemini.
Gabriel Kaufmann
Last position:
NewMedia at TYPOworx GmbH
- Media designer for digital and print media, focus: digital media, PHP development, TYPO3
- PHP, MySQL programming
- Full-stack (frontend & backend development)
- IT consulting
- Web hosting, consulting, and IT services
- Software and internet projects
- IT system administration
- Linux and Mac system administration
Boris Nicolai
Last position:
Fullstack Developer & DevOps Engineer at EnBW Energie Baden-Württemberg
- Further development of the internal "ECockpit" platform with an Angular 17 frontend and .NET (C#) backend
- Maintenance and further development of Azure DevOps pipelines
- Introduction of technical improvements in build & release processes
- Collaboration on a modular architecture approach (Clean Architecture & DDD)
- Focus on scalability and secure data processing
- Tech stack: Angular 17, .NET / C#, Azure, Azure DevOps, Git, CI/CD, Clean Architecture, Domain Driven Design
Dimitry Kirschner
Last position:
Rollout Expert at Everience Germany GmbH
- Project: Mazars Windows 11 rollout: responsible for the Windows 11 rollout at the Mazars client
- Understanding customer-specific requirements (hardware compatibility, application dependencies, Microsoft AD group policies)
- Implementing hardware logistics at customer sites
- Coordinating IT, business unit, security, and compliance teams
- Updating infrastructure
- Performing driver and firmware updates
- Automating the rollout using scripts
- Notifying users, providing FAQs, change logs, and support contacts
- Technologies: Baramundi Management Center, AD, Azure AD, Intune, Office 365, OpenProject, RDP, Topdesk, MS Teams, PowerShell
Anton Klonov
Last position:
Head of Technical Overall Integration NSC / Hadoop Cloud Development at IABG
Head of technical overall integration NSC (National Secure Cloud project with about 60 employees).
Technical integration of all subprojects into one product, definition of interfaces, basic components of a cloud including hardware, technical architecture of the IABG base.
Development of a Cloud Management Platform (CMP) that can create a private/mixed cloud of any complexity based on a textual description with one click or interactively.
CMP also includes the complete hardware management cycle.
As a foundation, it uses Kubernetes, OpenStack, and Hadoop.
The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are automatically configured.
The private cloud can run any customer workloads, including a full Hadoop stack with HDFS, Spark, MapReduce, Mesos, HBase and around 20 other ML/DL technologies.
Hadoop worker clusters can also be automatically installed on bare metal or commodity hardware without Kubernetes.
OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.
Development of a Java application Rudi: SOAP, REST, containers, database.
Technologies: Kubernetes (K3s, RKE2, Minikube, Harbor, Gitea, Jenkins, Longhorn, Keycloak, Rancher), OpenStack (Nova, Neutron, Keystone, Swift, Ceph, Cinder, Sahara, Magnum, Kayobe, Kolla, Bigrost, Ironic), Hadoop (HDFS, Ambari, Solr, Livy, Ranger, YARN, Tez, HBase, Kafka, Hive, Zookeeper, MapReduce, Spark, Oozie, Flink), virtualization (Kubernetes (K3s), VMware, Oracle), scripting (Ansible, Puppet, Juju, Shell, Groovy, Gradle, Maven).
Yasin Yildiz
Last position:
DevOps Architect & Backend Developer at Schweizerische National Bank
- Architecting and enhancing the DevOps infrastructure in a regulated environment
- Migration, planning, and development from a monolith to microservices (ASP.NET Core)
- Building and maintaining CI/CD pipelines (GitLab, Jenkins) to support agile development
- Managing artifact repositories with JFrog Artifactory and security scans via Xray
- Migrating and integrating source code repositories (SVN → GitLab)
- Operating and configuring a container platform with OpenShift
- Automating deployments with Ansible, Helm, and the Ansible Automation Platform
- Implementing monitoring and alerting solutions with Prometheus
- Collaborating closely with the frontend development team to optimize build, test, and release processes
- Supporting the establishment of secure and scalable infrastructure processes (Secure SDLC)
- Documenting and sharing knowledge within the team
- Leading refinements and designing the backend architecture
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))
Thomas Hieber
Last position:
AR App
- Development of an AR app for iOS for a sports company.
- Development of mobile application and augmented reality features.
- Technologies: objective-c, iOS, metaio, rest, json, php, Xcode.
Discover over 15,000 top freelancers
Statistics of experts using Minikube
Aggregated from the professional profiles of matched freelancers.
Experience
23 years
Position duration
1.1 years
Positions per freelancer
22
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
75%
Master's degree or higher
63%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100%
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 Germany 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 Germany using Minikube
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
Local Kubernetes
Minikube lets specialists run a local Kubernetes cluster on a laptop or workstation. It is used to test manifests, Helm charts, and basic cluster behavior without changing shared environments. That makes it a practical tool for day-to-day delivery work.
Common use cases
- Validate Deployments, Services, and ConfigMaps before release
- Check ingress rules and service discovery in a safe setup
- Reproduce issues from CI or staging on a local cluster
- Try add-ons, storage classes, and simple autoscaling flows
Tooling around it
Strong professionals use Minikube with kubectl, Helm, Docker or another container runtime, and Kubernetes manifests stored in Git. They often pair it with YAML linting, local registries, and test automation. The value is not just starting a cluster, but keeping the workflow repeatable.
When to bring in help
Companies usually look for freelance expertise when local Kubernetes work is slowing releases, cluster behavior differs across machines, or a team needs reliable setup guidance. In Germany, this often comes up in product teams, SaaS companies, and enterprise environments that want fast feedback without changing the main cluster.
What good specialists do
Good Minikube specialists focus on reproducible environments, not quick fixes. They know how to tune drivers, expose services, set resource limits, and keep cluster configuration close to the real target environment. They also spot when local testing is enough and when a shared Kubernetes environment is the better choice.
Practical deliverables
A freelance expert can help with local cluster setup, developer onboarding notes, Helm chart checks, and issue reproduction steps. They can also support on-site or remote teams in Germany by aligning local Minikube workflows with CI pipelines and the target Kubernetes version. The result is less guesswork during implementation and testing.
Frequently asked questions
Key details about Minikube, drawn from the questions we get asked most.
Minikube is used to run a local Kubernetes cluster for development and testing. Teams use it to validate manifests, try add-ons, and reproduce issues without touching shared infrastructure. It is especially useful when a change needs quick feedback before it reaches staging or production.
Minikube is a strong choice when you want a simple local cluster that behaves like Kubernetes on a laptop. kind is often chosen for container-native testing, while a managed cluster is better for shared integration work and production-like checks. A good specialist knows which option fits the task, instead of forcing one tool everywhere.
A strong Minikube professional usually knows kubectl, Helm, YAML, Docker, and core Kubernetes objects. Storage, networking, ingress, and basic troubleshooting are also important because many local cluster issues sit in those layers. Familiarity with CI pipelines helps when the local setup must match delivery workflows.
Minikube expertise matters when teams need reliable local testing, but the setup is inconsistent or too slow to use. It is also valuable when onboarding new specialists, validating charts, or debugging a cluster issue that only shows up in local work. If the team just needs a quick demo, lighter guidance may be enough.
Yes, Minikube works well for remote collaboration because each specialist can run the same local cluster setup on their own machine. For teams in Germany, this can reduce time lost to shared environment access and make debugging easier across locations. Clear setup notes matter more than being in the same office.
Look for someone who can explain cluster setup, add-ons, networking, and service exposure in plain terms. A good Minikube specialist leaves behind repeatable steps, not just a one-time fix. Ask for examples of how they reproduced a bug locally and how they aligned the setup with the target Kubernetes environment.
No. Minikube is often the fastest way to test Kubernetes behavior locally, even for experienced teams. Skilled professionals use it to inspect manifests, isolate problems, and verify assumptions before changes reach shared environments.
Before bringing in a Minikube specialist, collect the manifests, cluster version, expected workflow, and any error messages or screenshots. It also helps to share whether the goal is developer onboarding, issue reproduction, or chart validation. The clearer the target, the faster the expert can help.
The average hourly rate of freelancers in Germany who have used Minikube in their recent projects is 92 €, which corresponds to a daily rate of about 740 € based on an 8-hour working day.
Of the freelancers in Germany who have used Minikube in their recent projects, 75% hold at least a Bachelor's degree and 63% hold at least a Master's degree.
On average, freelancers in Germany who have used Minikube in their recent projects have 23 years of professional experience, with a single engagement typically lasting around 1.1 years.
The most common languages among freelancers in Germany who have used Minikube in their recent projects are German (100%), English (100%), and French (20%).
The most common industries among freelancers in Germany who have used Minikube in their recent projects are Information Technology (100%), Automotive (60%), and Banking and Finance (60%).
The most common business areas among freelancers in Germany who have used Minikube in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (90%).
Main locations of FRATCH Experts, who have recently used Minikube
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.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
