Amazon VPC Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Amazon VPC
Alexandru G.
Last position:
Principal Cloud DevOps Architect at BP
In my role as Senior Cloud DevOps Architect for BP, an oil and gas company, I had the mission to migrate the Electric Vehicle Charging platform of the EV Division from on-premises and Azure to AWS cloud, resulting in a hybrid multi-cloud, multi-tenant SaaS solution.
Deployment with Kubernetes for the application layer meant provisioning Kubernetes clusters managed by EKS and AKS, with a focus on integrating them into a multi-tenant environment. This integration was achieved by using Kubernetes namespaces and access controls to ensure data isolation and privacy enforcement.
In the database layer, we chose an RDS instance with PostgreSQL to support the backend infrastructure of our applications. Tenants shared the same RDS instance, but each had a dedicated schema.
To ingest near real-time data from physical charge points (CPOs), as IoT devices, via the OCPI protocol, we ran into significant delays with batch processing. As a result, we built a real-time streaming data pipeline using Apache Kafka, while prioritizing an event-driven architecture.
Led collaboration across multiple internal teams, external vendors, cloud providers, and on-site partners to integrate over five systems into a unified solution.
Achievements:
- Successfully designed and implemented hybrid multi-cloud solutions, integrating multiple cloud platforms (AWS, Azure) with on-premises infrastructure, using Site-to-Site VPNs, Firewalls, and Load Balancing.
- Led the migration of on-premises infrastructure to multi-cloud, multi-tenant infrastructure, resulting in 30% faster processing times.
- Migrated workloads from VMware and Hyper-V environments to cloud-based VMs, leveraging cloud-native services to optimize performance, cost efficiency, and scalability.
- Designed a multi-tenant Kubernetes platform leveraging the Kubernetes ecosystem, using Karpenter for dynamic EC2 node provisioning, KEDA for event-driven pod autoscaling (e.g., Kafka message lag), and Rancher for centralized monitoring of multiple clusters (EKS, AKS, or on-prem K8s), replacing Microsoft-centric Azure Arc management service.
- Designed and implemented Python-based FastAPI microservices as part of the EV core-backend on AWS EKS application layer, powering data ingestion and customer analytics pipelines.
- Developed asynchronous, event-driven APIs (Python-FastAPI) for real-time integration with CPOs, supporting OCPI 2.3 and OICP protocols.
- Designed and implemented a secure, production-grade Azure Databricks platform using Terraform, ensuring scalability and cost efficiency.
- Migrated on-premises ERP to a hybrid Dynamics 365 architecture with ERP hosted locally and CRM running in Azure, integrated via Azure Arc.
- Automated CI/CD pipelines for Databricks notebooks and jobs using GitHub Actions & Databricks CLI, reducing deployment time. Reduced infrastructure provisioning time by 70% by automating cloud resource deployment with GitOps.
- Ensured compliance with internal audit and data governance standards (GDPR) through OAuth2/OIDC-based authentication and fine-grained role-based access controls.
- Developed a Zero Trust security model, enforcing least-privilege access and microsegmentation, enhancing security posture and compliance with GDPR and NIST.
- Built interactive analytics dashboards in Amazon QuickSight, integrating data from S3 and Redshift to deliver real-time business insights and visualizations with embedded access for multi-tenant users.
- Led cloud security assessments and full-lifecycle cybersecurity integration during M&A, covering AWS, Azure, IAM (Entra ID), and data protection, while aligning security posture with NIST, ISO 27001, and GDPR across hybrid and cloud-native environments.
- Reduced cloud costs by 64% for a client's dev environment by implementing automated start/stop schedules for EC2 and RDS instances via AWS CDK with EventBridge Scheduler or AWS Systems Manager.
Tech stack:
- Infrastructure as Code: Terraform, AWS CDK, Ansible.
- Containers: Kubernetes on EKS, AKS, Docker.
- Streaming Data Processing: Kafka to Confluent Cloud, after AWS MSK.
- Frontend: TypeScript, React, NextJS, Hooks, Styled Components.
- Backend: Python with FastAPI, also Node.js with NestJS.
- Database: Aurora on PostgreSQL with TypeORM, RDS on SQL Server, Azure Databricks full setup and administration, ETL Pipelines.
- CI/CD and GitOps: GitHub Actions, Azure DevOps, ArgoCD.
- Monitoring and Observability: Prometheus and Grafana.
- Virtualization: Hyper-V, VMware Cloud on AWS, Azure Migrate.
- ERP Systems: Odoo, Microsoft Dynamics 365 Business Central on Azure, integrated with Azure Arc.
- Networking: Site-to-Site VPNs, AWS Direct Connect, Azure ExpressRoute, Firewalls (AWS Network Firewall, Azure Firewall).
- Security: IAM, NIST Framework, Zero Trust Security, AWS WAF, AWS Shield, GuardDuty.
Thomas H.
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).
Frank E.
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
Vitaliy R.
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.
Majid A.
Last position:
Lead Consultant at Infosys
- Network automation
- CI/CD and Docker environment
- Python Nornir for network automation
- pyATS for monitoring and test case automation
- Network Access Control (Radius) and Device Admin Access Control (TACACS) with AAA and Cisco ISE with Cisco/HP/Aruba Devices
- Cisco ISE Clusters (2/4/8 nodes) configuration
- Cisco ISE Authentication and Authorization configuration
- Cisco/HP/Aruba Switch/WLC Tacacs/dot1x/Radius configuration
- Cisco ISE automation with Restconf and Python
Teemu S.
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.
Stephan S.
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Stefan Z.
Last position:
Agile Project Manager at Telefónica o2 Germany GmbH & Co. OHG
- Implementation of MVPs in fixed-line communication with a team of 3 technical product owners
- Building the product roadmap
- Defining epics with business units, breaking down into features and user stories
- Managing offshore development teams
- Providing transparency and reporting to the overall program
- Agile development using SAFe approach
Janusz M.
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 Amazon VPC
Aggregated from the professional profiles of matched freelancers.
Experience
25 years
Position duration
2.2 years
Positions per freelancer
14
Top business areas
Information Technology, Operations, Product Development
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Project Management, Operations
Bachelor's degree or higher
100%
Master's degree or higher
75%
Certifications per freelancer
4
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Munich using Amazon VPC
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Amazon VPC experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Banking and Finance (67%)
- Automotive (56%)
- Insurance (56%)
- Manufacturing (56%)
- Retail (56%)
- Telecommunication (56%)
- Energy (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Amazon VPC provides
Amazon Virtual Private Cloud, commonly called Amazon VPC, gives AWS workloads an isolated network environment. Companies use it to control IP ranges, subnets, routing, connectivity and traffic boundaries for applications, data services and internal systems. It supports both public-facing services and private workloads that should not be directly reachable from the internet.
Core network design
A strong design starts with a clear address plan and a separation of public, private and restricted subnets. Specialists configure route tables, internet gateways, NAT gateways, VPC endpoints and network interfaces to control how resources communicate. They also account for availability zones, regional architecture, DNS resolution and future expansion without creating overlapping network ranges.
Security and connectivity
Amazon VPC security combines security groups, network access control lists, routing rules, encryption services and identity controls. Experts often connect VPC environments to offices, data centers or other clouds through AWS Site-to-Site VPN or AWS Direct Connect. Transit Gateway can link multiple networks, while private endpoints keep service traffic away from the public internet.
Typical delivery work
- Design VPC layouts for new AWS workloads or account migrations
- Segment application, database and management traffic
- Build shared network foundations for multiple AWS accounts
- Establish VPN, Direct Connect or Transit Gateway connectivity
- Diagnose routing, DNS, access and reachability problems
When freelance expertise helps
Companies bring in freelance specialists when a cloud migration needs a sound network foundation, when teams inherit unclear routing or when security requirements demand tighter segmentation. They also help during mergers, multi-account rollouts, disaster recovery planning and large application changes. In Munich, remote collaboration often works well, while on-site workshops can help align infrastructure, security and operations teams in German or English.
Signs of strong specialists
The best professionals explain network decisions in terms of risk, operations and application needs. They use infrastructure as code with tools such as Terraform, AWS CloudFormation or AWS CDK, and document routes, dependencies and ownership clearly. They test failure scenarios, review flow logs and connectivity paths, and leave behind repeatable configurations that other teams can maintain.
Frequently asked questions
Everything clients usually want to know about Amazon VPC, in one place.
Amazon VPC is used to create a controlled virtual network for AWS resources. It lets teams define subnets, routes, gateways and traffic rules for applications, databases, containers and other cloud services.
Amazon VPC provides similar concepts to a data center network, including address ranges, segmentation and routing, but these are defined through AWS services and APIs. It adds elastic components such as managed gateways, private service endpoints and integration with AWS identity and monitoring tools.
A strong Amazon VPC specialist should understand AWS IAM, EC2, load balancers, Route 53, CloudWatch and logging. Useful adjacent skills include Terraform, AWS CloudFormation, container networking, Linux, DNS, VPN design and security architecture.
The right level depends on the network’s scope and risk. A simple application may need focused subnet and routing work, while hybrid connectivity, multi-account governance or regulated workloads call for a specialist who can design, test and document the full environment.
Amazon VPC work is often suitable for remote collaboration because configuration, reviews and diagnostics happen through AWS consoles, APIs and infrastructure-as-code repositories. On-site sessions may still help when teams must coordinate physical data center links, office networks or shared operating procedures.
Ask the Amazon VPC freelancer to explain a comparable network design, including address planning, routing, private access and failure handling. Review diagrams, infrastructure-as-code examples and documentation quality, then confirm that the specialist can communicate clearly with security and application teams.
Amazon VPC can connect to on-premises networks through AWS Site-to-Site VPN or AWS Direct Connect. The appropriate option depends on latency, resilience, traffic patterns, existing network equipment and the operational model the company can support.
A Amazon VPC design may need review when teams rely on broad access rules, cannot trace traffic paths or repeatedly encounter DNS and routing failures. Overlapping address ranges, undocumented dependencies, unused public exposure and manually changed infrastructure are also warning signs.
The average hourly rate of freelancers in Munich, Germany who have used Amazon VPC in their recent projects is 103 €, which corresponds to a daily rate of about 823 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Amazon VPC in their recent projects, 100% hold at least a Bachelor's degree and 75% hold at least a Master's degree.
On average, freelancers in Munich, Germany who have used Amazon VPC in their recent projects have 25 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Munich, Germany who have used Amazon VPC in their recent projects are German (100%), English (100%), and Spanish (22%).
The most common industries among freelancers in Munich, Germany who have used Amazon VPC in their recent projects are Information Technology (100%), Banking and Finance (67%), and Automotive (56%).
The most common business areas among freelancers in Munich, Germany who have used Amazon VPC in their recent projects are Information Technology (100%), Operations (89%), and Product Development (89%).
Main locations of FRATCH Experts, who have recently used Amazon VPC
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
