GlassFish Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used GlassFish
Ronald Mazelisz
Last position:
DevOps Consultant at M.it services & systems GmbH
- Adjusting, optimizing, configuring, and administering a multi-stage GitLab instance with over 250 users
- Building, adjusting, expanding, and optimizing infrastructure, configuration, and monitoring
- Providing services and handing them over to production
- System environment: DependencyTrack, GitLab, Grafana, Hedgedoc, Kubernetes, OAuth2 Proxy, Openstack, Prometheus, Syseleven
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.
Celso Kurrle
Last position:
SAP Commerce Cloud FullStack Developer at Spar
- Implementation of a GitLab CI/CD pipeline based on SAP Commerce Cloud 2211
- Development of a new B2C shop with Vue, Node and TypeScript to ensure scalability, extensibility and performance optimization
- Integration of Microsoft Azure Event Grid with SAP Hybris
- Implementation of BDD with Cucumber using Gherkin syntax to promote collaboration between development and business teams
- Support and customization of a Spartacus shop
- Technologies/Languages: Java, REST, OData, Behavior Driven Development (BDD), Cucumber, Node, Vue, TypeScript, Spartacus, GitLab CI/CD, Gradle, Maven, Ant, SonarQube
Werner Anderschitz
Last position:
IT Architecture, Business and Process Consulting at BMW
- Business and technical consulting for master data provisioning and process management
- Support for transition management
- Process optimization
- Interface definition
Syamala Himabindu
Last position:
Fullstack Developer at BLG Logistics Group
As part of developing this project, various apps were developed for an IBM portal environment based on portlets and Spring Boot services, as well as the setup of a BI platform based on QlikView
Full-stack development of applications, technical analysis, refinement of requirements with the business department, coordination with the customer, DevOps
Team size: 8 people
Technology: Java 11.0, Maven, Git, Spring, Hibernate, JUNIT, Mockito, React, Jira, SQL, Spring Boot, CD/CI Jenkins, Kanban, Rest Api, Oracle
Environment: Eclipse, IBM Rational Application Developer
David Cole
Last position:
Scrum Master, Agile Coach at Steadforce
Agile coaching at BMW – 8 coaching projects
Advised BMW department on introducing agile software development
Coaching product owners, Scrum Masters, managers and teams
Trainer for product owner workshops
Consulting firm project (Jan 2017 to present): Steadforce was the main partner in developing products that consultants used on client sites
As Scrum Master, supported scaling the project from six developers to three distributed Scrum teams with developers in Germany, Poland, Romania and Ukraine as well as stakeholders in Germany, US and India
Agile values evangelist
Organizing Scrum meetings
Facilitating retrospectives
Co-organizing team workshops
Working on code quality and test coverage for almost daily releases
UMS at BMW (Sept 2016 to present): Scrum Master for a team of 3 software developers
Organizing Scrum meetings and collaborating in Jira with the product owner at the client for agile fixed-price billing (payment based on t-shirt sizing)
Steadforce Campus: Redefining software development processes at Steadforce with a focus on clean code, code reviews and Scrum
Michael Pförringer
Last position:
Setup Azure cloud, Java development, CI/CD pipelines at Sulzer GmbH
- Migration of a mainframe application (PL/1, zOS) to the cloud (Azure)
- Data transfer from z/OS (USS) to Azure storage (blob containers, file shares)
- Implementation of the mainframe job control in Java
- Mapping of job network dependencies in Control-M
- Performance analysis and optimization measures
- DB2 (z/OS) migration to Postgres (Azure)
- Technologies: Azure (storage, VM, VMSS, Postgres), z/OS (USS), DB2, Postgres, Packer, Terraform, Docker, Jenkins, GitHub Actions, Control-M
- Tools: Eclipse, Visual Studio Code, IntelliJ
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 GlassFish
Aggregated from the professional profiles of matched freelancers.
Experience
28 years
Position duration
2 years
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
86%
Master's degree or higher
57%
Certifications per freelancer
2
Most common languages
German, English, Spanish
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 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 GlassFish
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
GlassFish basics
GlassFish is a Java application server for Jakarta EE and older Java EE systems. It is used to run enterprise applications, web services, and business logic in a managed server runtime. Teams also look for it under Eclipse GlassFish or the older Sun GlassFish name.
What it runs
It fits back-end services that need standard Java APIs, transaction handling, security, and deployment control. Common work includes application packaging, server configuration, data source setup, and support for EAR or WAR based releases.
Typical tasks
- Install and configure GlassFish domains and clusters
- Deploy Jakarta EE applications and service endpoints
- Set up security, logging, and resource adapters
- Tune runtime behavior and fix production issues
- Handle upgrades, migration, and rollback planning
Skills that matter
Strong GlassFish professionals understand Jakarta EE, JNDI, JMS, JPA, and servlet-based applications. They also know how to read server logs, trace startup failures, and work with build tools such as Maven or Gradle. Clear knowledge of networking, TLS, and resource configuration is important too.
When companies bring in help
Companies usually need freelance expertise when a legacy server has to stay stable while the application changes around it. That is common during migrations, environment rebuilds, release troubleshooting, or when an in-house team needs short-term support for a critical incident. In Munich, this often comes up in enterprise IT, insurance, industrial software, and regulated back-end systems.
Working with specialists
Many GlassFish projects are handled remotely because most work happens in configuration, packaging, and server logs. On-site support can still help during cutovers, security reviews, or system changes that need close coordination with local teams in Munich. The best specialists document decisions well and keep deployments repeatable.
Frequently asked questions
Not sure where to start with GlassFish? These answers cover the essentials.
GlassFish is used to run Jakarta EE and older Java EE applications that need a standard application server. Companies use it for web apps, service endpoints, messaging, transactions, and other back-end systems that depend on Java enterprise APIs. It is common in long-lived business software where stability matters.
GlassFish is the product family name searchers use for the Java application server. Older systems may still be called Sun GlassFish, and the current open-source line is often referred to as Eclipse GlassFish. In practice, the name usually points to the same server lineage and the same kind of enterprise Java work.
GlassFish is a full Jakarta EE server, while Tomcat is mainly a servlet container. If a project needs JPA, JTA, JMS, or other enterprise APIs out of the box, GlassFish is often the closer fit. If the system only needs a lighter web runtime, teams often compare it with Tomcat instead.
A strong GlassFish specialist usually knows Jakarta EE, Java, Maven or Gradle, SQL, and troubleshooting from logs and thread dumps. Skills in TLS, LDAP, reverse proxies, and deployment automation are also useful. For migration work, experience with Oracle WebLogic, JBoss, or Payara can be valuable.
GlassFish work can be simple if it is only a clean deployment or a small configuration change. It becomes more demanding when clusters, security, data sources, or legacy integration are involved. For production systems, companies usually want someone who has already handled server recovery and release problems before.
Yes, most GlassFish tasks can be done remotely because they revolve around configuration files, application builds, and server logs. On-site time in Munich helps when a release cutover, infrastructure change, or security review needs direct contact with the local team. Many projects use a mix of both.
Look for clear examples of production deployments, incident handling, and migration work on GlassFish or Eclipse GlassFish. Good specialists explain why a server issue happened, what they changed, and how they reduced the chance of a repeat problem. They also write clean handover notes and keep configuration choices easy to support.
Choose GlassFish when the application already depends on Jakarta EE standards and changing the runtime would add risk. It can be the right choice for stable enterprise systems, especially when the code base, operations setup, and team knowledge are built around that server. If the goal is a lighter service stack, a different runtime may be easier.
The average hourly rate of freelancers in Munich, Germany who have used GlassFish in their recent projects is 90 €, which corresponds to a daily rate of about 720 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used GlassFish in their recent projects, 86% hold at least a Bachelor's degree and 57% hold at least a Master's degree.
On average, freelancers in Munich, Germany who have used GlassFish in their recent projects have 28 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Munich, Germany who have used GlassFish in their recent projects are German (100%), English (100%), and Spanish (25%).
The most common industries among freelancers in Munich, Germany who have used GlassFish in their recent projects are Information Technology (100%), Automotive (63%), and Banking and Finance (50%).
The most common business areas among freelancers in Munich, Germany who have used GlassFish in their recent projects are Information Technology (100%), Product Development (88%), and Quality Assurance (75%).
Main locations of FRATCH Experts, who have recently used GlassFish
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.
Countries:
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
