Observability Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Observability
Jens Henneberg
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilizing an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Karen Manukyan
Last position:
Personal AI Engineering Project — Croky AI at Crocky AI
Product:
- Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
- Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
- Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
- Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
- Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.
Agent Orchestration & RAG Systems
- Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
- Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.
Alejandro Prieto
Last position:
DevOps Consultant at Freelance
- Kubernetes: EKS management, cluster upgrades and stability improvements, Infrastructure-as-Code reviews and updates, AWS support, and cost optimization.
Martin Hermann
Last position:
Lead Product Owner at Energy
- Team leadership: Prioritization and coordination of four cross-functional teams.
- Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
- Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
- Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
- Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
- Organizational development: Improving communication and decision-making structures across all organizational levels.
- Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
- Quality assurance: Ensuring high quality standards in processes, services, and deliverables.
Ali Aminian
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Frédéric Klein
Last position:
Project Manager (Enterprise Cloud Governance) at CompuGroup Medical SE & Co. KGaA
Short description: Leading a group-wide project to establish standardized cloud governance for Microsoft Azure, including policies, security and compliance controls, automation, and cost and operations management while preserving the autonomy of decentralized business units within regulatory frameworks.
Tasks and activities:
Overall responsibility for designing, building, and implementing a company-wide cloud governance structure (Azure), including target picture, roadmap, and operating model.
Managing internal and external stakeholders (C-level, IT, Security, Compliance, Cloud Architecture, DevOps), including decision and escalation management.
Planning and facilitating workshops on cloud strategy, governance principles, and the design of areas such as identity, connectivity, and platform management.
Defining, implementing, and rolling out cloud policies (Azure Policy / custom policies), security standards, and compliance requirements (including GDPR, ISO 27001, BSI C5).
Building a cloud governance framework based on the Azure Cloud Adoption Framework (CAF), including landing zone and guardrail concepts.
Introducing automation solutions for governance, security, and cost control (policy/control automation, IaC, CI/CD-based control mechanisms).
Implementing cloud security and compliance monitoring mechanisms as well as continuous improvement processes.
Establishing and operationalizing FinOps in an enterprise environment (central and decentralized FinOps teams), including cost management strategies, reporting, and guardrails.
Integrating governance policies into DevOps processes (e.g. CI/CD principles for security and compliance checks, GitLab Runner concept in spokes, GitLab CI/CD for CAF landing zones).
Implementing access concepts including RBAC design and breaking-glass mechanisms (emergency access) as well as certificate automation (ACME / step-ca).
Achievements:
Created a unified, auditable governance and control set for Azure (policies, standards, compliance mapping) and thus laid the foundation for scalable cloud use in a regulated environment.
Established repeatable automation for governance, security, and cost control (IaC + CI/CD), reducing manual effort and implementation risk.
Improved operational and decision-making capability across central and decentralized units (clearer roles, responsibilities, escalation paths, balance between autonomy and group requirements).
Significantly increased workload compliance during lift-and-shift migrations.
Technologies used:
Microsoft Azure Policy, custom policies.
Terraform, OpenTofu, Terragrunt.
step-ca (ACME).
Entra ID.
Azure Firewall.
Azure Networking, hub-and-spoke architecture.
Azure vWAN (evaluation).
Azure Front Door, Azure Application Gateway.
Azure ExpressRoute.
Azure Key Vault.
NetBox.
GitLab (on-premises).
Infrastructure, concepts used:
Cloud shared responsibility model.
Hub-and-spoke connectivity / central shared services (from hub-spoke context).
Central governance with decentralized delivery (business unit autonomy with guardrails).
Methods used:
Scrum.
Stakeholder management (C-level to engineering).
Cloud governance, Azure Cloud Adoption Framework (CAF).
DevOps, CI/CD.
Cost and FinOps approaches: tagging/chargeback models, budget/alert concepts, reserved instances/savings plans vs. on-demand scenarios, sensitivity analyses.
RBAC, breaking-glass concepts.
ACME / certificate automation.
GitLab Runner concept in spokes, GitLab CI/CD pipelines for CAF landing zones.
Carsten Rösner
Last position:
Enterprise Product Owner at opta data IT GmbH
- Product responsibility for the central platform "one" as a group-wide web-based customer portal
- Coordination of the connection of 20 group companies to the product platform
- Derivation and steering of a group-wide product strategy and roadmap aligned with company goals
- Prioritization and bundling of strategic requirements from the various group companies
- Harmonization of different interests and moderation of complex decision-making processes at management level
- Ensuring the technical and business integration of the product into existing system landscapes, business processes, and business models
- Building transparent governance and decision-making structures for group-wide product development
- Representation of the product towards internal and external stakeholders at leadership level
Halil Oeztoprak
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.
Oliver Fries
Last position:
Modernization of a multi-company backend system at Energy utility company
Enhancement and modernization of a mature Aspire backend application in the environment of a utility company, focusing on new business requirements, testing, legacy code cleanup, and stable backend delivery.
Core contributions & results Implemented new business requirements in the context of customer orders, subcontractors, and cross-company backend processes, and ensured consistent workflows in a distributed system landscape. Modernized existing backend components step by step and reduced technical debt through targeted legacy code cleanup, refactoring, and structured code reviews. Improved the testability of business-critical services by expanding automated tests with xUnit, AutoFixture, and clearer validation structures. Supported the further development of workflow automations and integration processes via microservices, messaging, and API-based communication. Took over source code from external firms, systematically checked code quality, and derived technical improvements for maintainability, stability, and integration. Worked in agile development processes with Jira, Confluence, and Azure DevOps and supported cross-team alignment on architecture, quality, and implementation. Technical metrics Technologies & methods C#, .NET, ASP.NET, ASP.NET Core, Aspire, Docker, RabbitMQ, gRPC, REST API, Swagger, Microservices, NServiceBus, AutoMapper, Autofac, xUnit, AutoFixture, FluentValidation, Entity Framework Core, MediatR, Redis, Consul, Serilog, SonarQube, Azure DevOps, Azure Monitor, GitLab, Google Protocol Buffers, IronPDF, Mailjet, Jira, Confluence, Miro, agile development, Scrum, code reviews, refactoring, legacy code cleanup, workflow automation, power grids
Kevin Fischer
Last position:
DevOps and Platform Engineer at DB Systel GmbH
- Error analysis and fixes including performance optimization of the in-house developed platform API
- Change and incident management in day-to-day operations
- Responsible for compliance with security and compliance requirements
- Vendor management for software development and maintenance
- Planning and execution of migration of legacy services to a cloud native platform
Role in the project: project staff, implementation team
Used skills: requirements analysis, IT service and application management, IT operations, error analysis and performance optimization, software maintenance and lifecycle management
Project environment: Cloud Native Platform (Kubernetes, Crossplane, AWS, ArgoCD, Grafana)
Ljubomir Obrenovic
Last position:
Senior Software Test Engineer at Keil KTM GmbH
Temporary employment
- System black-box integration tests (BBIT, IVVQ): Execution of regression, release, acceptance, and compliance tests for safety-critical brake control units in the rail industry
- Software test application & integration: Runtime configuration of software components and libraries, validation of interfaces, configuration dependencies, and component interactions
- Test automation (FEAT framework): Co-development and further development of an automated test framework for test execution, reporting, and result analysis
- Functional safety (SiL4, FuSi): Ensuring compliance with safety requirements, traceability and coverage, as well as standards compliance according to EN50126/28/29
- Test automation for communication components: Configuration and validation of fieldbus (CAN) and Ethernet-based TCMS data communication interfaces (TRDP and CIP)
- Requirements analysis & shift-left (PTC Windchill ALM): Analysis of software and system artifacts to identify gaps, ambiguities, and redundancies early in the SDLC
- Test design & test case development: Derivation of test conditions, coverage strategies, and implementation of data-driven test cases (DDT), including reusable test data fixtures
- CI/CD & automation (Python, PowerShell, Jenkins, SVN): Automation of build, test, and HIL deployment processes as well as integration into CI/CD pipelines
- Test data & configuration management (XML): Maintenance and adaptation of XML test vectors and system configurations with automated integration into test environments
- Non-functional testing: Execution of performance and load tests to assess stability and system behavior
- Agile development & defect management (JIRA, Confluence): Participation in Scrum teams, test coordination, review of test artifacts, as well as defect tracking and root-cause analysis
- Error analysis & debugging (CANoe, CANalyzer): Analysis of errors and message flows across multiple system layers (application to bus)
- Model-based analysis (UML, Enterprise Architect): Specification of SUT/SOW and support for systematic test control
- Process & test documentation: Creation of integration and test documentation according to internal quality and certification requirements
Chisom N.
Last position:
Founder & Analytics Engineer at Museni Nexus
- Client — Podimo ApS (podcast & audiobook streaming): build the finance reporting layer on BigQuery + dbt + Airflow, including the core revenue-transaction fact tables used across finance reporting.
- API automation: design and build a BigQuery → Airflow → Microsoft Dynamics 365 Business Central REST-API pipeline to automate sales-invoice posting, with idempotency and master-data sync between systems.
- Delivery: sole engineer on the engagement — requirements, modelling, orchestration and stakeholder communication with the client finance team, end to end.
Saqib Javed
Last position:
AI Developer / AI Engineer (Lead) at KOM4TEC GmbH
- Conceptual design and implementation of modular AI assistants for sales and business processes in the Microsoft ecosystem (Agentic AI, Copilot extensions)
- Frontend architecture and development with React + TypeScript for embedded chat and assistant surfaces (streaming UI, hooks, React Query, OpenAPI clients)
- Enterprise-level agent development: reusable skill/agent library, MCP server, review and compliance gates
- LLM integration into the user experience: Anthropic (Claude), OpenAI, tool use, RAG pipelines, prompt engineering, guardrails
- Architecture and code review consulting as well as mentoring in the AI development team
- Integration with Microsoft Graph, Power Platform, and Azure services
- Technologies: React, TypeScript, Anthropic Claude, OpenAI, MCP, RAG, Microsoft Graph, Power Platform, Azure
Panagiotis Tsafaridis
Last position:
Senior Data Engineer Consultant at GOLDNER GmbH
- Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
- Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
- Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
- Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
- Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
- Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
- Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
- Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.
Cherif Sahraoui
Last position:
DevOps Specialist – SCM & CI Platform at Freelancer
- Designed and developed the architecture of an enterprise SCM/CI platform for Kubernetes-native delivery and GitOps workflows.
- Implemented infrastructure automation and Vault & IAM integration for secure, compliant pipelines.
- Coordinated cross-functional teams to improve DevOps, security, and architecture in release processes.
- Increased platform adoption and developer experience by automating onboarding and artifact pipelines.
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About the technology
What observability covers
Observability helps teams understand how software behaves in production. It brings together logs, metrics, traces, and alerts so specialists can spot failures, slow paths, and hidden dependencies. Companies use it for cloud services, APIs, microservices, and distributed systems.
Core toolchain
- Instrumentation with OpenTelemetry
- Metrics and alerting with Prometheus and Grafana
- Log search in Elastic, Splunk, or cloud tools
- Trace analysis across service calls
- Dashboard design for operations and product teams
When companies bring in help
Teams often need outside experts when a system grows too complex for ad hoc monitoring. That includes noisy alerts, missing trace context, poor service ownership, or unclear incident data. In Germany, this work is common in SaaS, industrial software, logistics, finance, and platform engineering teams.
Strong specialist profile
Good professionals connect code, infrastructure, and operations. They know how to define useful signals, avoid metric overload, and build alerts that point to action. They also understand Kubernetes, cloud runtime behavior, and how to keep dashboards readable for on-call teams.
Typical delivery work
A freelancer may set up tracing for a new service, clean up an alert model, or redesign dashboards for an incident review process. They may also standardize log fields, document service health checks, or help teams adopt Elastic Observability, Datadog, or Splunk Observability without lock-in.
Why it matters in practice
Observability is not the same as basic monitoring. Monitoring asks whether a system is up; observability helps explain why it is not behaving well. Strong specialists make incidents easier to diagnose, reduce wasted time in handover, and improve the quality of production decisions.
Frequently asked questions
Questions about Observability? Start with the answers below.
A strong Observability specialist helps teams see what is happening inside live software. That usually means logs, metrics, traces, dashboards, and alerts that are tied to real services and user journeys. They also make sure the data is useful during incidents, not just visible.
Observability goes beyond basic monitoring. Monitoring tells you that something is broken or slow; observability helps explain where the problem started and how it spread. Companies usually need both, but observability is what supports faster diagnosis in distributed systems.
Yes. Observability projects often start with OpenTelemetry because it provides a common way to collect traces, metrics, and logs. Specialists use it to instrument services consistently so teams can compare signals across different runtimes and tools.
A Observability engagement often includes Prometheus, Grafana, OpenTelemetry, Elastic, Datadog, or Splunk Observability. The right mix depends on the stack already in place and how much standardization the team wants. Good specialists can work across vendor tools and cloud-native setups.
A strong Observability professional usually knows Kubernetes, cloud infrastructure, service architecture, and incident response. They should also understand log structure, alert design, and the basics of application performance. That mix helps them connect technical signals to operational action.
Observability work needs enough context to understand the system design, not just the tooling. A freelancer should know which services matter most, how incidents are handled, and which signals the team trusts. For larger platforms, that usually means access to engineers, operations staff, and existing runbooks.
Yes, most Observability work can be done remotely if the team can share access to dashboards, logs, and service documentation. For Germany-based companies, remote collaboration is common, while on-site time may help during workshops, incident reviews, or initial architecture mapping. Clear communication in English is often enough, though German can help in some teams.
Look for someone who can explain why a signal matters, not just how to configure a tool. A good Observability specialist produces clean dashboards, clear alert logic, and practical guidance for incident handling. They should also be able to remove noise, improve traceability, and leave the team with durable patterns, not one-off fixes.
Main locations of FRATCH Experts, who have recently used Observability
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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