
AWS Fargate Experts in Germany
, matched in minutes from over 15,000 CVsHire experts who configure ECS and Amazon EKS workloads, design secure container deployments, and automate delivery with AWS tooling. FRATCH connects you quickly with vetted, available freelancers whose skills match your AWS Fargate project.
Meet FRATCH Experts in Germany, who have recently used AWS Fargate
Collin K.
Last position:
Software Architect / Fullstack Developer at Equity Bytes
Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.
- Designed and operated a highly scalable microservice and serverless architecture
- Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
- Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
- Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
- End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
- Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
- Robust backup and disaster recovery strategies
- RDS Postgres backups and hourly snapshots
- Read-only, asynchronously synchronized replicas with automated master failover in emergencies
- Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
- Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
- Integrated Stripe for international payment processing
- Built a marketplace payment system with multiple parties and payout routines
- Used Algolia for high-performance real-time search of digital assets on the platform
- Federation of services with GraphQL and Hasura
- Later migration to GraphQL Mesh
- Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
- Used Next.js / React for modern frontend applications in the nx monorepo
- Enterprise security architecture & access control
- Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
- Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
- Built internal microfrontends with Retool for fast prototyping and operational business processes
Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest
Sabahattin K.
Last position:
Sole responsibility (design, development, infrastructure, operations) at Own project busik.ch
- Ride-sharing and bus platform, live and fully functional. Backend with Spring Boot 4.1 on Java 21, PostgreSQL with Flyway, and Testcontainers integration tests. Hosted in my own AWS account (ECS Fargate, ALB, ECR, IAM Least-Privilege) with CI/CD via GitHub Actions and OIDC federation without static credentials. Development fully AI-supported with Claude Code, including custom skills and project-specific memory. Spring Boot · Java 21 · PostgreSQL · Flyway · Docker · AWS ECS/ALB/ECR · CI/CD · GitHub Actions · Claude Code
Osman T.
Last position:
Senior Architect, DevOps Engineer at genPsoft GmbH
IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.
Frontend:
- Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
- Component testing
- Code documentation
- CI/CD with Gitlab Pipeline
Backend / IoT:
- Analysis and architectural design with AWS Greengrass IoT on Edge Devices
- Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
- CI/CD with Gitlab Pipeline, Terraform, AWS ECR
- Logging with Fluentbit Lua Language for AWS Cloudwatch
- Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
- Implementation of test-driven development with JUnit, Mockito, and code Coverage
- Jacoco
- Definition of REST interfaces with OpenAPI / Swagger
- Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
- Authentication and authorization in Aws IAM
- Development of REST and gRPC interfaces for the frontend and backend
- Implementation of Maven dependencies with DevSecOps OWASP
- Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents
Patrick D.
Last position:
Fullstack Developer
- SPA for automated communication of medical findings with role-based access (Sanctum)
- Server-side LLM integration (OpenRouter) with structured processing
- Automated sending via SMS/voice call (Twilio, ElevenLabs) with queue + status retry
- Full test coverage with 80+ documented test cases
Technologies: PHP, Laravel, LLM API (OpenRouter), Twilio, ElevenLabs, Laravel Sanctum, PHPUnit, Playwright, Docker, REST
Benito E.
Last position:
Cloud DevOps Engineer und Cloud Architekt at Energieversorgungsunternehmen (anonymisiert, NDA)
- Design and build of a fully isolated AWS offline environment with no outbound internet access for running a browser-based business application
- Design and implementation of a proxy and response service that terminates all external application calls inside the VPC and serves them from locally stored content; identification of the actual communication needs through measurement-based DNS query logging
- Creation of architecture designs and decision papers including a comparison of options (Application Load Balancer with Lambda and S3, reverse proxy on EC2, private API Gateway) assessed by operational effort, cost, and availability
- Transfer of the solution and operations documentation previously available only for Azure to an AWS target architecture, including reassignment of all services and operational processes
- Automated rollout as Infrastructure as Code (Terraform, CloudFormation) with CI deployment via GitHub Actions, plus setup of private DNS zones and an internal certificate chain for operation without internet access
- Creation of architecture, deployment, and operations documentation and handover to the customer
- Build-up of a private cloud platform on OpenStack at provider TelemaxX with Terraform, including FortiGate HA clusters, FortiManager, and Kubernetes
- Introduction of Policy as Code (Open Policy Agent, Conftest) as well as development of MCP servers (Model Context Protocol) to connect AI assistants to operations and project tools
Successes:
- Made the business application fully operable without internet access for the first time; the cause of the loading error was narrowed down systematically to missing CORS headers after the likely certificate issue was ruled out
- Fully transferred an existing Azure concept to AWS and replaced the manually created environment with a reproducible, CI-based rollout
Technology stack: AWS (VPC, Application Load Balancer, Lambda, S3, Route 53 private hosted zones and Resolver query logging, IAM, CloudWatch, EC2, CloudFormation), Infrastructure as Code (Terraform, CloudFormation, Remote State), CI/CD (GitHub Actions with OIDC, Azure DevOps Pipelines), OpenStack, FortiGate, FortiManager, Kubernetes, Policy as Code (Open Policy Agent, Conftest), offline and air-gap architectures, PKI & certificates (internal CA, TLS, CRL/OCSP), DNS, network segmentation, Linux, Windows Server, Python, Bash, PowerShell, YAML, JSON, architecture design & decision papers, documentation (Confluence, Markdown), Generative & Agentic AI (Model Context Protocol, Agentic AI Coding Tools)
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.
Thorsten B.
Last position:
Senior Backend Engineer at VTG Rail Europe
traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.
As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.
- Design and implementation of event-driven backend services.
- Migration and replacement of legacy processing pipelines.
- Development of replay / rebuild mechanisms for large event datasets.
- High-throughput asynchronous event processing on SNS / SQS.
- Database and query optimisation for PostgreSQL and DynamoDB.
- Design of scalable read / write models and aggregation pipelines.
- Production troubleshooting and operational support.
- Performance tuning and infrastructure scaling.
- Design and stabilisation of integration and system tests.
- Technical concepts, architecture documentation, and cross-team collaboration.
- Support the further development of existing GitLab CI/CD pipelines
Geofence & Wagon Stay Processing
- Algorithm to detect vehicles within geofences (entry, exit, dwell time).
- Event sourcing with guaranteed chronological order within the affected time window.
- Refactored geofence event and wagon-stay processing logic for performance.
- Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
- Repair and replay tooling for corrupted or inconsistent movement data.
Fleet Metadata & Mileage
- Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
- Scalable mileage aggregation and replay mechanisms.
- Read / write models and optimised queries for high-volume mileage calculations.
Sensor & Telematics Integration
- Integrated telemetry and sensor processing pipelines.
- Snapshot and state-calculation logic for sensor systems.
- APIs and persistence models for wagon sensor data; data-quality improvements.
- Further development of a service using gRPC for intra-service communication.
Movement Segment Processing & Routing
- Migrated services to new movement-segment event streams.
- Built replay and rebuild tooling for segment correction.
- Optimised throughput and reliability for high-volume event processing.
Condition Monitoring & Wagon Analytics
- APIs and backend services for wagon condition monitoring.
- Brake-wear prediction processing and wagon analytics functionality.
- PostgreSQL views and optimised query models for operational dashboards.
Operational Reliability - First Responder
- Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
- Tuned database performance and AWS infrastructure under production load.
- Improved observability, monitoring and operational tooling.
- Supported rollout strategies, monitoring and post-deployment stabilisation.
Dimitri W.
Last position:
Software Architect at Environmental services company (cooperation with Sitegeist Media Solutions GmbH)
Conceptual design and implementation of a modular customer portal based on Laravel.
The focus was on defining a maintainable system architecture with broad use of Domain-Driven Design principles (within the Laravel architecture), introducing automated quality assurance processes (test strategy, CI integration), and preparing an auditable operation (logging, traceability of changes) in an AWS-based infrastructure, taking IT security standards according to NIST and process requirements according to ISO 9001 into account.
Achievements:
- Analysis and structuring of business requirements in close coordination with stakeholders
- Documentation of the system architecture and infrastructure incl. change and release management
- Design and implementation of an interface for integrating SAP systems
- Planning and implementation of automated tests for quality assurance
- Implementation of security and compliance requirements, including SBOM generation, software license management, and QA processes
- Technical consulting and support for the internal IT team
- Introduction and establishment of AI-supported development processes (Spec-Driven Development), including AI-readable specifications, integration of AI instructions into the development environment, and training developers for productive use
Technologies and tools: SAP, Docker, ddev, PHP 8.4, Laravel, Filament, C4 Model, Architecture Decision Records (ADR), Mermaid, PlantUML, Spec-Driven Development, Claude, GitHub Copilot, Codex
Halil O.
Last position:
Senior Cloud Operations & DevSecOps Engineer (Azure / Terraform / CI-CD) at KfW Bankengruppe
Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).
Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.
Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.
Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.
Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.
Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.
Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.
CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.
Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.
Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.
OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.
Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).
Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.
Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.
Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.
SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.
Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.
Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.
CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.
Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.
Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.
Moritz F.
Last position:
AWS Developer/DevOps Engineer (Energy Trading) at RWE Supply & Trading GmbH
- Further development and partial new development of a distributed cloud application for providing data in energy trading
- Independent implementation of the infrastructure (IaC)
- Creation of automated CI/CD pipelines, containers, REST APIs, and Lambdas
- Continuous cost and performance optimization
- Collaboration in an international Scrum team and with experts in energy trading
- Technologies: C#/ASP.NET Core; EF Core; PostgreSQL; Terraform/AWS CloudFormation; HTTP; REST/Web API; Swagger/OpenAPI; Azure DevOps; Rider; VS Code; git; Docker; AWS (S3, EC2, Fargate, Lambda, Step Functions, Secrets Manager, VPCs, ALB/NLB, RDS, Cloudwatch, AWS CLI, Amazon MQ); Redis; OAuth; OpenID Connect
- Languages: C#; TypeScript; HCL; Docker; Bash; PowerShell; YML; JSON
Daniel B.
Last position:
Senior Cloud Consultant and Developer at SDIA/Leitmotiv
- Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Umweltbundesamt with SIEC)
- Development of Python APIs and web applications, deployment on AWS/ECS with Terraform
- Collecting power consumption metrics for servers, CPUs, GPUs running AI workloads
- Technologies used: AWS, EC2, ECS, Fargate, CloudMap, VPC, Route53, Lambda, EventBridge, CodeBuild/CodePipeline/CodeDeploy, Terraform, Docker, Linux, Bash scripting, Python, Flask, SQLAlchemy, SQL, MariaDB, InfluxDB, Telegraf, Prometheus, Zabbix, Kubernetes, Letsencrypt, certificate management
Robin S.
Last position:
Senior Cloud & Backend Engineer at Media-Saturn-Holding GmbH
- Implementing applications with Kotlin and Ktor as microservices
- Using MongoDB in the MongoDB Atlas cloud
- Asynchronous communication of services via Google Pub/Sub
- Using Kotest and MockK for unit tests
- Developing an administration frontend with TypeScript, React and Express.js
- Provisioning environments in GCP using Terraform
- Implementing CI/CD processes with GitHub Actions
- Operating scalable production and test environments in GCP with Kubernetes, Helm and Flux CD
- Monitoring environments with Prometheus and Grafana
- Providing BI data in the Google BigQuery data warehouse
Niels M.
Last position:
Senior Software Developer / Cloud Architect at Biesterfeld SE
- Architected ETL services for event-driven data exchange between enterprise systems on a Kafka streaming backbone.
- Optimized CI/CD pipelines for Azure AKS deployments and improved OpenSearch monitoring and alerting for proactive incident detection.
Tech: Java / Kotlin, Quarkus, Kafka / Avro, Azure / AKS, Azure Storage Container, ArgoCD, GitLab CI, OpenSearch, Terraform
Viktor S.
Last position:
AI Engineer (Freelance) at Empion
Enterprise AI content categorization and AI-powered web research.
- Built multi-LLM evaluation framework with annotated data
- Iterated LLM error rates based on annotated datasets
- Implemented AI-powered web research pipeline Stack: LLM, evals, OpenRouter, Python, Node.js, TypeScript, React
Christian K.
Last position:
Senior AWS Cloud Engineer at Sopra Financial Technology GmbH
- Setup and operation of a multi-cluster AWS EKS platform for banking workloads with a unified network and security architecture across 45 AWS accounts.
- Developed and standardized a unified AWS network and security architecture for 45 AWS accounts, enabling consistent governance, connectivity, and compliance for enterprise customer environments.
- Developed and operated a multi-cluster AWS EKS platform to support production workloads, significantly improving scalability, availability, and operational reliability.
- Implemented a GitOps deployment model using ArgoCD and Helm, enabling fully automated, auditable deployments and reducing manual release errors.
- Automated infrastructure provisioning using Terraform and Terragrunt at scale, reducing environment setup time by up to 70% and eliminating configuration drift.
- Established enterprise-grade backup and disaster recovery strategies using Velero and AWS Backup, ensuring reliable multi-cluster recovery and business continuity.
- Introduced Rancher as a self-service Kubernetes platform, accelerating developer onboarding while maintaining centralized security and governance.
- Designed and implemented detailed AWS IAM concepts (roles, policies, trust relationships) to enforce the principle of least privilege for access to accounts, workloads, and CI/CD pipelines.
- Developed AWS Lambda-based pre-provisioning workflows for databases, automating initialization, configuration, and access setup to support secure and consistent application integration.
- Delivered consistent, high-quality results as part of a 5-person AWS Solutions Architecture team, resulting in three consecutive contract renewals.
Discover over 15,000 top freelancers
Statistics of experts using AWS Fargate
Aggregated from the professional profiles of matched freelancers.
Experience
16 years

Position duration
1.8 years

Positions per freelancer
13

Top business areas
Information Technology, Product Development, Operations

Top industries
Information Technology, Retail, Banking and Finance

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
83%
Master's degree or higher
42%
Doctorate
4%

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
97%
Based on our profile pool as of 19 Sep 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 AWS Fargate
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
AWS Fargate 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%)
- Retail (50%)
- Banking and Finance (47%)
- Government and Administration (40%)
- Automotive (37%)
- Education (37%)
- Healthcare (37%)
- Energy (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Serverless containers
AWS Fargate is a serverless compute engine for containers. It runs tasks without requiring a company to provision or maintain virtual machines. Teams define CPU, memory, networking, storage, and permissions while AWS manages the underlying infrastructure.
Where Fargate fits
Fargate is commonly used for APIs, web applications, background workers, scheduled jobs, and event-driven services. It works with Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS), making it suitable for both AWS-native and Kubernetes-based delivery.
- Run containerized services without host management
- Scale workloads through ECS services or EKS resources
- Separate application deployments from infrastructure operations
- Connect workloads to databases, queues, and AWS networking
Ecosystem and tooling
Strong AWS Fargate specialists understand Docker images, Amazon Elastic Container Registry, IAM, VPC networking, load balancers, CloudWatch, and secrets management. They often work with Terraform or AWS CloudFormation, CI/CD systems, ECS task definitions, Kubernetes manifests, and observability tools.
When expertise matters
Companies bring in freelance expertise when a container migration has unclear networking or security requirements, when deployment pipelines need to become repeatable, or when Fargate costs and performance are difficult to control. In Germany, specialists may support teams remotely or on site and align with existing German- or English-speaking delivery processes.
- Move services from virtual machines or another container platform
- Create reliable blue-green or rolling deployments
- Troubleshoot task startup, health checks, and service discovery
- Establish logging, monitoring, and incident workflows
Fargate or another option
Fargate removes host maintenance, but it is not the best fit for every workload. A specialist can compare it with ECS on EC2, AWS Lambda, managed Kubernetes nodes, or other container services based on runtime limits, networking, control, workload shape, and operational responsibility.
What strong specialists deliver
The best professionals make task definitions reproducible, permissions narrowly scoped, and deployments easy to observe and roll back. They understand how containers behave in production, document decisions, test failure scenarios, and connect application needs with AWS architecture instead of treating Fargate as an isolated service.
Frequently asked questions
Curious about AWS Fargate? Here are the answers that come up again and again.
AWS Fargate is used to run Docker containers without managing the virtual machines that host them. Companies use it for APIs, web services, workers, scheduled tasks, and event-driven applications through Amazon ECS or Amazon EKS.
AWS Fargate removes most host provisioning and patching work, while ECS on EC2 provides more control over instance types, placement, and underlying capacity. The right choice depends on workload requirements, operational capacity, scaling behavior, and the need for infrastructure-level control.
A strong AWS Fargate professional usually understands Docker, Amazon ECS, Amazon ECR, IAM, VPC networking, load balancing, CloudWatch, and secrets management. Infrastructure as code with Terraform or CloudFormation and practical CI/CD experience are also valuable.
The required experience depends on the scope, not on the service name alone. A simple ECS deployment may need focused container and AWS knowledge, while a production platform with private networking, security controls, observability, migrations, and recovery testing calls for broader AWS Fargate experience.
AWS Fargate projects are often suitable for remote collaboration because configuration, infrastructure code, logs, and deployment workflows are shared digitally. Teams in Germany should clarify working hours, documentation standards, and whether the specialist must communicate in German, English, or both.
Ask the specialist to explain task definitions, IAM boundaries, networking, health checks, deployment rollback, and observability in concrete terms. A capable AWS Fargate professional can also describe trade-offs with ECS on EC2 or Kubernetes and show how infrastructure changes are tested and documented.
AWS Fargate may be a poor fit when a workload needs deep host access, specialized hardware, unusual runtime behavior, or very fine-grained control over compute capacity. A specialist should assess those constraints before recommending Fargate instead of EC2-based containers, Lambda, or another managed service.
An AWS Fargate freelancer may deliver ECS or EKS configurations, container build and registry workflows, IAM policies, VPC integration, deployment pipelines, monitoring, runbooks, and migration plans. The exact deliverables should reflect the application architecture and the team's ability to operate the result after handover.
The average hourly rate of freelancers in Germany who have used AWS Fargate in their recent projects is 101 €, which corresponds to a daily rate of about 811 € based on an 8-hour working day.
Of the freelancers in Germany who have used AWS Fargate in their recent projects, 83% hold at least a Bachelor's degree, 42% hold at least a Master's degree, and 4% hold a doctorate.
On average, freelancers in Germany who have used AWS Fargate in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Germany who have used AWS Fargate in their recent projects are German (100%), English (97%), and French (13%).
The most common industries among freelancers in Germany who have used AWS Fargate in their recent projects are Information Technology (100%), Retail (50%), and Banking and Finance (47%).
The most common business areas among freelancers in Germany who have used AWS Fargate in their recent projects are Information Technology (100%), Product Development (90%), and Operations (70%).
Main locations of FRATCH Experts, who have recently used AWS Fargate
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.
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