Longhorn Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Longhorn
Ivan Vetoskin
Last position:
Senior DevOps Engineer at 58agents
- Provision Kubernetes infrastructure on Azure, GCP, or bare-metal at the hosting provider
- Design and implementation of REST and GraphQL APIs
- Cloud governance (cost, compliance, security)
- Infrastructure-as-Code and CI/CD as code (Terraform, Ansible)
- Container technologies (Docker, Helm)
- Maintain and improve CI/CD pipelines (GitLab CI, GitHub Actions), Argo CD
- Deployment, scaling, and monitoring of microservices
- Distributed event streaming (Kafka)
- Message brokers RabbitMQ, MQTT
- Software development from scratch or further development of existing projects using PHP, Python, Go, C#, and Bash
Karl-Heinz Gille
Last position:
DevOps Engineer / JEE Developer at EnBW
Further development of an existing microservice architecture (REST) for asset model management and runtime environment in the cloud.
Java development (BE) in the SCRUM team.
Java (Spring Boot/Security)
PostgreSQL
Docker
AWS Services (Lambda, Cognito, ECS, SQS)
IntelliJ
Marcus Wiederstein
Last position:
Administrator, DevOps at KZVB
- Planned and implemented new network infrastructure (VLAN, LACP, DMZ, structured cabling)
- Migrated from VMware to KVM using Oracle Linux Virtualization Manager (OLVM), including CPU pinning
- Hardened the entire environment using SELinux (KVM hosts, container hosts, database servers)
- Configured and operated the virtualization platform with OLVM and Ansible-based provisioning
- Containerized and redeployed critical services: WordPress, Jenkins, PostgreSQL, MariaDB, Subversion with Apache + AD integration
- Developed Ansible playbooks for automated deployment and configuration management
- Integrated Foreman for repository and security management in the DMZ
- Produced technical documentation in Markdown; organized in Bookstack
- Coordinated with external vendors (e.g. HPE) for hardware installation and setup
- Delivered all contributions documented and reproducible in Markdown
Michael Rudl
Last position:
Software Developer
- Automatic report generation based on log data from the Senstar surveillance camera software, tracking access times of different camera systems
- Gathering requirements and translating them into a suitable technical solution
- Implementing Python scripts to read, process, and convert Senstar log data into PDF reports
- Reading configuration files to control the scripts
- Packaging the Python scripts and all dependencies into an executable .cmd for offline installation on Windows Server
- Providing a --help parameter to list and explain the script options
- Creating documentation for installing, configuring, and running the scripts
- Technical environment: Python 3, SQL, Senstar, Windows Server, Python setuptools, fpdf
Kai Held
Last position:
Backend Python Engineer at Rohde & Schwarz SIT
- Conceptualizing & developing a need-to-know, domain-based identity and access management system in a high-security environment
- Backend development (Python): API & microservice development
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).
Discover over 15,000 top freelancers
Statistics of experts using Longhorn
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
1.7 years
Positions per freelancer
15
Top business areas
Information Technology, Project Management, Business Intelligence
Top industries
Information Technology, Energy, Banking and Finance
Certification focus areas
Information Technology, Product Development, Research and Development
Bachelor's degree or higher
100%
Master's degree or higher
60%
Certifications per freelancer
2
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 Longhorn
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
Persistent storage
Longhorn is a cloud-native storage system for Kubernetes. It gives workloads persistent volumes that stay available when pods move, restart, or fail. Companies use it for stateful services, internal tools, and test environments that need storage without extra storage hardware complexity.
Where it fits
- Persistent volumes for Kubernetes apps
- Backup and restore for cluster data
- Disaster recovery for stateful services
- Storage for dev, staging, and production clusters
It is often compared with other Kubernetes storage options when teams want simpler operations and clear volume management.
What experts handle
Strong Longhorn specialists configure replica counts, node placement, backups, and retention policies. They also work with storage classes, snapshots, engine images, and upgrade planning. In Germany, they are often brought in for hybrid teams that need practical help across cloud and on-premises clusters.
Ecosystem skills
Longhorn work usually sits close to Kubernetes, Helm, CSI, container networking, and backup targets such as S3-compatible storage. Experts should read cluster events, check storage health, and spot issues in node scheduling or disk capacity before they turn into outages.
When to bring help
- A cluster needs reliable persistent storage
- Volumes are slow, detached, or unhealthy
- Backups or restores do not behave as expected
- A team is rolling out Longhorn for the first time
Freelance expertise helps when internal teams know Kubernetes but need deeper storage knowledge for a live system or migration.
What good work looks like
Good Longhorn professionals keep volume setup simple, document recovery steps, and test failure cases instead of assuming them. They know how to balance availability, performance, and operational effort. They also explain trade-offs clearly so platform and application teams can support the system with confidence.
Frequently asked questions
Not sure where to start with Longhorn? These answers cover the essentials.
Longhorn is used to provide persistent storage for Kubernetes workloads that cannot lose their data when pods are rescheduled or a node fails. It is a good fit for stateful services, internal applications, and environments that need simple volume management, snapshots, and restore options.
Longhorn is often chosen when teams want cloud-native storage with a simpler operating model than many traditional storage stacks. Compared with more complex enterprise storage or storage provisioned outside the cluster, it is easier to manage inside Kubernetes, but it still needs careful planning around replicas, backups, and node health.
Yes. Longhorn is commonly searched as Rancher Longhorn because of its roots in the Rancher ecosystem, and many teams still use that name. The product is now known as Longhorn, but both terms appear in real project discussions and hiring needs.
A strong Longhorn specialist usually brings Kubernetes storage knowledge, CSI familiarity, and hands-on experience with backups and restore workflows. Helpful adjacent skills include Helm, S3-compatible backup targets, Linux storage basics, and cluster troubleshooting.
You do not need a large or complicated environment to benefit from Longhorn expertise. Teams often bring in a specialist when they are introducing persistent volumes, planning a migration, or trying to stabilize an existing cluster with storage issues.
Yes. Longhorn work is often done remotely because most tasks involve cluster access, configuration review, and testing. For Germany-based teams, remote collaboration usually works well, as long as there is clear access to the cluster and a shared way to review incidents and changes.
A good Longhorn freelancer explains why a setting matters, not just how to change it. Look for clear recovery planning, clean backup validation, careful use of snapshots, and practical advice on replica placement, node failures, and storage capacity.
Ask the specialist what they have done with Longhorn in real Kubernetes environments, especially around backups, restores, upgrades, and failure handling. It also helps to ask how they would assess your current storage design and what they would test first in your cluster.
The average hourly rate of freelancers in Germany who have used Longhorn in their recent projects is 101 €, which corresponds to a daily rate of about 810 € based on an 8-hour working day.
Of the freelancers in Germany who have used Longhorn in their recent projects, 100% hold at least a Bachelor's degree and 60% hold at least a Master's degree.
On average, freelancers in Germany who have used Longhorn in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Germany who have used Longhorn in their recent projects are German (100%), English (100%), and French (50%).
The most common industries among freelancers in Germany who have used Longhorn in their recent projects are Information Technology (100%), Energy (67%), and Banking and Finance (67%).
The most common business areas among freelancers in Germany who have used Longhorn in their recent projects are Information Technology (100%), Project Management (83%), and Business Intelligence (67%).
Main locations of FRATCH Experts, who have recently used Longhorn
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
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Philipp Thomaschewski
FRATCH CEO
