Docker Compose Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Docker Compose
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.
Alois Flammensböck
Last position:
Software Architect / Backend Developer at GEO API
- Design and implementation of a Laravel backend API for provider-based geo search, feature details, boundary geometries and neighborhood detection.
- The API serves as a server-side proxy, cache and enrichment layer, protecting credentials for external geo services and persisting features, localizations, geometries, hierarchies and neighborhood relationships in MariaDB.
- Key areas included normalization of autocomplete and feature data, caching strategies for expensive boundary/polygon requests, spatial processing of GeoJSON and MultiPolygon geometries, as well as neighborhood detection using hierarchies, bounding box filters and topology checks.
- Additionally, separate production and diagnostic endpoints were created, along with status and error catalogs, discovery logging, a Docker development stack, API documentation, and unit and feature tests.
- Technologies: PHP 8.3, Laravel, REST API, geo data API, GeoJSON, MariaDB Spatial, Eloquent, Laravel Queues, PHPUnit, Mockery, Docker, Docker Compose, API design, geocoding, boundary data, spatial queries.
Frederik Claus
Last position:
Freelance Fullstack Software Developer at Bundesdruckerei GmbH
Development of the digital organ donation register, commissioned by the Federal Institute for Drugs and Medical Devices (BfArM)
Implementation of user stories in multiple microservices (front- and backend)
Ensuring quality with unit, integration, and end-to-end tests
Conducting code reviews
Coordination with other development teams
Taking over software license checks and simplifying the process
Responsible for implementing and documenting domain logging
Setting up a development environment with Docker Compose
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
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
Mohamed Saleh
Last position:
Machine Learning Engineer (Part Time) at E.ON Digital Technology
- Designed and implemented an advanced, agentic RAG pipeline using LangChain and LangGraph for structured data extraction from PDFs, utilizing tools, state management, and OpenAI LLMs (GPT-4) to improve accuracy and handle complex document structures.
- Developed a Google AI agent for extraction of structured information from PDF documents and deployed the agent on Vertex AI.
- Architected data pipelines using Azure Data Factory and Databricks to ingest data from Azure Blob Storage, process it with PySpark, and load it into Azure SQL Database via Linked Services.
- Containerized AI agents and services using Docker for consistent local development and deployment.
- Utilized PySpark and Dask for database querying in coordination with Azure Blob Storage and Document Storage.
- Created a ReAct agent that extracts structured data from PDF documents using tools and integrating Azure Document Intelligence.
- Contributed to the CPO invoices validation check project using Databricks to find existing CDRs and calculate total valid costs.
- Developed a conversational AI agent (chatbot) with a FastAPI backend, integrating RAG for precise tariff extraction and deployed the service using Azure Container Apps.
- Tools used: Azure, Azure OpenAI, Azure Document Intelligence, Azure Blob Storage, Google ADK, Google Cloud, Vertex AI, Gemini, Databricks, LangChain, LlamaIndex Ollama, Docker, PySpark, Azure SQL, Azure Data Factory, Azure AI Agent, Microsoft SQL Server
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))
Sebastian Fohler
Last position:
Managing Director System Administration & DevOps at Far Galaxy Networks
- Windows application migration using Windows Server 2022/2025, DHCP, Active Directory, directory trust and setup, GPO management
- Cloud service automation, firewall and network management, debugging
Discover over 15,000 top freelancers
Statistics of experts using Docker Compose
Aggregated from the professional profiles of matched freelancers.
Experience
21 years (Germany: 18 years)
Position duration
1.7 years (Germany: 5.4 years)
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Energy, Banking and Finance
Certification focus areas
Information Technology, Operations, Product Development
Bachelor's degree or higher
100% (Germany: 85%)
Master's degree or higher
50%
Certifications per freelancer
1 (Germany: 2)
Most common languages
German, English, Italian
Speak two or more languages
100% (Germany: 99%)
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 Docker Compose
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
Container orchestration for local stacks
Docker Compose is used to define and run multi-container applications with a single config file. It is common for web apps, APIs, databases, caches, queues, and support services that need to start together in a predictable way.
What specialists deliver
- compose files for development, test, and demo environments
- service networking, ports, volumes, and env setup
- clean startup and shutdown flows for linked containers
- local stacks that mirror CI and production behavior
Ecosystem and tooling
Strong professionals work with the Compose file format, Docker Engine, Docker CLI, and related tools such as BuildKit, bind mounts, and health checks. They also understand image tags, overrides, secrets handling, and how Compose fits with Kubernetes or plain Docker when teams outgrow a simple setup.
When companies bring in help
Teams often need freelance expertise when a stack becomes hard to start, a monolith is split into services, or a new project needs a dependable local setup fast. In Munich, this often matters for product teams, industrial software groups, and SaaS companies that want engineers and specialists to work on the same environment without delay.
What strong experts do well
Good Docker Compose professionals keep files readable, avoid brittle dependencies, and make services easy to restart and debug. They know how to reduce drift between laptops, CI, and staging, and they document the exact commands and expectations so other experts can use the stack without guesswork.
Signs you need a specialist
- docker-compose files are large, duplicated, or hard to maintain
- services fail because startup order or networking is unclear
- developers spend time fixing local environment issues
- you need a cleaner handoff between Compose and CI pipelines
Frequently asked questions
Before you brief your next project: the most common questions about Docker Compose.
Docker Compose is used to run several related containers as one application stack. Companies use it for local development, test environments, demo setups, and small production deployments where the services are tightly connected. It is especially useful when an app needs a database, cache, queue, and API to start in a known order.
Docker Compose is part of the Docker ecosystem, but it solves a different problem than the core Docker CLI. Docker builds and runs single containers, while Compose describes how multiple services work together. For teams, that usually means less manual setup and fewer one-off commands.
A company should bring in a Docker Compose specialist when the setup is slowing the team down or becoming inconsistent. Common cases are messy environment files, service startup failures, duplicated configs, or a migration from a single container to a multi-service stack. A freelance expert can clean up the setup and leave clear documentation.
A strong Docker Compose specialist usually knows Dockerfiles, Linux basics, networking, environment variables, volumes, and container health checks. Experience with CI pipelines and image publishing is also useful because Compose often sits between local work and delivery workflows. If the stack may grow, Kubernetes awareness helps too.
Docker Compose is simpler and faster to work with for local stacks and smaller deployments. Kubernetes is better for large-scale scheduling, resilience, and multi-node operations, but it adds more moving parts. Many teams use Compose for development and testing, then move to Kubernetes only when the operational need is clear.
People still search for docker-compose, the older command and project name they learned first. The current product name is Docker Compose, but both forms are common in docs, repos, and team conversations. A good specialist should understand both terms and know how they map to the same workflow.
Yes, Docker Compose works very well for remote collaboration because it gives everyone the same service layout and startup steps. For Munich-based companies, that is useful when some experts work on-site and others work remotely, since the environment is defined in files instead of shared only by local setup. Clear docs matter more than location.
Look for a Docker Compose specialist who writes clean service definitions, keeps configuration small, and explains why each dependency exists. Good signs are readable files, stable startup behavior, sensible use of volumes and networks, and a setup that another expert can run without help. Strong documentation is part of the delivery.
The average hourly rate of freelancers in Munich, Germany who have used Docker Compose in their recent projects is 97 €, which corresponds to a daily rate of about 774 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Docker Compose in their recent projects, 100% hold at least a Bachelor's degree and 50% hold at least a Master's degree.
On average, freelancers in Munich, Germany who have used Docker Compose in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Munich, Germany who have used Docker Compose in their recent projects are German (100%), English (100%), and Italian (20%).
The most common industries among freelancers in Munich, Germany who have used Docker Compose in their recent projects are Information Technology (100%), Energy (60%), and Banking and Finance (60%).
The most common business areas among freelancers in Munich, Germany who have used Docker Compose in their recent projects are Information Technology (100%), Product Development (90%), and Project Management (60%).
Main locations of FRATCH Experts, who have recently used Docker Compose
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.
Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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