Terraform Experts in Munich

• Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
• Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
• Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
• Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
• Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
• Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
• Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
• Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
• Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
• Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.

• This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.

Used: Python, RAG, LangGraph, LangChain, deepeval, MCP

• AI Integration (LLM & RAG): Designed and built an internal intelligent RAG system (Retrieval-Augmented Generation) based on LLMs, n8n, and vector data to automatically analyze technical documents and error logs.
• Design & Implementation: Designed a robust RS-232/UART communication interface for an SBC-based embedded device used to control medical shaker systems.
• Architecture & Protocol Design: Built a highly maintainable software structure (OOP, SOLID) and defined resilient, hardware-level communication protocols, including multithreading and advanced error handling.
• Quality Assurance & DevOps: Automated testing with xUnit, ran integration tests directly on the hardware target, and maintained technical documentation to strict medical technology standards via Azure DevOps.

Label: C#, .NET, LLMs, RAG, n8n, RS-232, UART, Multithreading, async/await, xUnit, gRPC/protobuf, Blazor, MudBlazor, EF Core, Visual Studio 2026, Azure DevOps

• Built Azure Kubernetes clusters (AKS) with network policies, security groups, and RBAC
• Terraform-based infrastructure as code for secure, reproducible deployments in the BMW Azure cloud
• Hardened CI/CD pipelines with Jenkins, SonarQube, Fortify SSC, and Contrast AST
• Integrated SAP BTP/Kyma and ServiceNow GRC

Oracle Project Management and Automation

As part of the project, the operation of an Oracle infrastructure was automated by developing and enhancing Puppet modules and migrating existing Bash scripts to a standardized configuration management solution.

The aim of the project was to standardize and automate administrative processes, improve the maintainability of the Oracle platform, and increase the efficiency and traceability of infrastructure management through the use of Infrastructure as Code.

• Analysis and migration of existing Bash shell scripts to a Puppet-based automation solution
• Development and enhancement of Puppet modules for Oracle environments
• Automation of installation, configuration and operational processes using Infrastructure as Code
• Standardization and optimization of configuration management for Oracle systems
• Creation and maintenance of technical and operational documentation
• Planning, coordination and professional support during project implementation
• Operation and automation of Oracle systems on x86-based Linux server platforms
• Testing and quality assurance of the developed Puppet modules
• Analysis and resolution of technical errors as part of the automation and migration
• Close coordination with specialist departments and infrastructure teams to implement automation requirements

Technologies used: Puppet 7/8, SLES 15, Oracle 19, Oracle Grid, SVN, Windows Server, Confluence, VS Code, Ruby, Bash, Pass

PROFILE Senior Oracle specialist, consultant and DBA with many years of experience in planning, architecture, installation, migration, operations, performance tuning and troubleshooting of large Oracle database environments. Focus on Oracle Database 19c and enterprise architectures with RAC, Active Data Guard, Golden Gate, Exadata, RMAN and CDB/PDB. Experience in heterogeneous enterprise environments on Linux, AIX, Solaris, HP-UX and Windows, as well as in cloud and migration projects. Over many years, worked as a technical consultant, DBA, architect and project manager for banks, insurers, energy providers, public institutions, industry, automotive and aviation. Combining technical Oracle expertise with operations concepts, migration, project planning, documentation and customer consulting.

ORACLE FOCUS AREAS

• Oracle Database 19c – installation, upgrade, patch/RU management, operations and troubleshooting
• Oracle Database 21c / 23ai / 26ai – knowledge of current Oracle release lines
• Oracle RAC, Active Data Guard, Data Guard, Oracle GoldenGate
• CDB / PDB, multitenant architectures and enterprise database operations
• Oracle Exadata and highly available database environments
• RMAN – backup, restore, recovery, migration and disaster recovery scenarios
• Data Pump (EXPDP / IMPDP), Transportable Tablespaces (TTS) and database-based migrations
• Performance analysis, SQL / PL/SQL, tuning, troubleshooting and capacity planning
• Oracle Enterprise Manager / monitoring and technical operational support
• Oracle Security: Wallet, TDE, Database Vault, VPD / RLS
• Oracle DWH / BI: OBIEE, ODI, OWB and Discoverer
• Oracle Applications / E-Business Suite and Oracle-based application environments

CURRENT PROJECTS

Scope Solutions AG, Basel / CH | 08/2023 – ongoing Oracle Project Management and DBA

• Installation, maintenance and regular upgrades of Oracle database systems with a focus on Oracle 19c.
• Patch and release management including OPatch and Release Updates; operations on RHEL 8.x, SLES 15.x and Windows.
• DBA support for customers in DACH and Europe and support of production, load test and other CDB/PDB environments.
• Technical operating processes and documentation via Confluence; support and service requests via My Oracle Support / Metalink.

Federal Employment Agency, Nuremberg | 04/2022 – 10/2023 Oracle Operations Support / DBA

• Operations and regular upgrades of Oracle-19c database systems on SLES 15.x.
• DBA for around 2,100 PDBs on RAC and Exadata in production, integration, load test and other environments.
• Configuration management via ARS Remedy; workflows and technical documentation via Jira and Confluence.
• Operations support and processing of service requests via My Oracle Support / Metalink.

Federal Statistical Office, Wiesbaden | 09/2021 – 03/2022 Oracle Operations and Architecture – 2022 Survey

• Merging data into a central Oracle-19c database system.
• Design of import/export procedures for the central data structure.
• KPI and performance architecture for analyses.
• Training employees in Oracle performance and DBA topics.

E.ON Digital Technology, Landshut / KKI | 03/2019 – 12/2021 Oracle Operations, Architecture and DBA

• Patch concepts, technical documentation, installation, database administration and operations of Oracle 12c/19c.
• AIX 7.x, LPAR administration including VIO server and software distribution with NIM.
• Performance monitoring and monitoring.
• Backup and restore with TSM / IBM Spectrum Protect and Oracle RMAN.
• Installation of Enterprise Manager 13c with WebLogic Server 12.1x; employee training.

KaPe Munich – various end customers in DACH / Europe | ongoing / various projects Oracle DBA, architecture, migration, DWH consulting and project management

• Many years of consulting and operational DBA work in various Oracle architectures.
• DWH/CRM platforms: planning, analysis, performance and tuning, as well as business analysis.
• RAC, Data Guard, Transportable Tablespaces, RMAN and Oracle 11g/12c in enterprise environments.
• Customer projects including Burda, Deka, E.ON, Otto Group and Augsburger Allgemeine.

AXA, Germany / Europe | 09/2018 – 02/2019 Oracle DB Operations and Migration – Cloud Architectures

• Planning, methodology and execution of Oracle database migrations to IBM Private Cloud / Spectrum and AWS Public Cloud.
• Creation of Oracle databases in the cloud with SLES and Terraform templates.
• Technical architecture work and cloud KPIs.

RWE / SÜWAG / Syna, Germany | 07/2016 – 09/2018 Oracle DB Migrations 11g/12c and Project Management

• Design, planning and execution of Oracle database migrations 11g → 12c with platform and architecture changes.
• Windows Server 2012/2016 and setup and migration of Enterprise Manager/WebLogic-based monitoring environments.
• Use of Data Guard, TTS, EXPDP/IMPDP and RMAN based on analysis of application requirements.
• Performance and tuning for Oracle 11g/12c.

MTU Aero Engines, Munich | 01/2016 – 03/2017 Oracle DBA / Requirements Engineer

• Operations and development of Oracle 11g/12c databases and application workflows.
• Interfaces to SAP via BAPI.
• Design and management of APPS modules with Visual Basic / Visual Studio and PL/SQL; version control with SVN.

UBIS (HVB), Munich | 04/2012 – 08/2015 Oracle Operations, Architecture, DBA and Project Management

• Oracle-based operations and migration of MUREX and Sophis trading platforms.
• Oracle Security, Wallet, Tablespaces, RAC, Data Guard, Database Vault, GoldenGate and DWH.
• Project management for Oracle DWH migrations and release changes from 10g to 11gR2.
• Migration OWB 11gR2 → ODI 12c and introduction of Oracle Database 12c.
• Platforms: Red Hat, AIX and Solaris.

WWK Deutschland a.G., Munich | 09/2010 – 03/2012 Oracle DB and HP-UX → Linux Migration

• Architecture, planning, operations concept and migration of 104 databases from an HP-UX cluster to Red Hat Linux.
• Single Instance with Veritas Cluster and 2-node RAC 11.2.0.2; four Data Guard databases.
• Project management for OWB/DWH migrations (>1 TB), including tuning, PL/SQL, mappings and metadata.

Allianz Deutschland, ACAS Stuttgart | 03/2010 – 09/2010 Technical DWH Project Manager

• DWH project for processing European ETL data sources.
• Business analysis and requirements management for automated loading processes.
• OWB, PL/SQL, SQL*Loader, Oracle Advanced Security / TDE, Oracle BI and Database Vault.

NETMA, Munich-Taufkirchen | 08/2007 – 02/2010 Oracle Specialist and DBA for Oracle Applications 11i

• Operations of Oracle 9i/10g and Oracle Applications 11.5.10.
• Design and development of APPS modules with PL/SQL and SVN.
• Oracle RAC, Enterprise Manager, Oracle Application Server and migration tests.
• Platforms: AIX, SLES, Windows and HP-UX.

BT Germany, Munich | 11/2007 – 04/2008 Oracle DB Migration

• Migration from Oracle 8i to 10gR2 in a Solaris cluster environment.
• Preparing offers, project planning and process planning.

Itellium (KQ), Nuremberg | 02/2007 – 08/2007 Oracle DWH Specialist

• Design and analysis of a DWH focusing on master data and logistics.
• Oracle Designer, OWB, Oracle Database, ETL, PL/SQL and External Tables; data volumes up to approx. 5 TB.

Oracle Deutschland GmbH, Munich | 10/2006 – 02/2007 and further assignments Oracle Specialist / Consultant – Data Migration and DWH

• Consulting for customers such as Volkswagen, GE Money Bank, WeKa, KSB, Swisscom and British Telecom.
• Migration Discoverer EUL4 → EUL5i, database optimization, Data Guard and web/database analysis.
• Performance and tuning on Solaris and Linux.

HaSpa, Hamburg | 07/2006 – 10/2006 Oracle Specialist / Consultant – Data Migration and DWH

• Setup of an Oracle-10gR2 environment for banking applications.
• Data transfer from DB2 / OS390, architecture, sizing, tuning and performance.
• Data preparation and integration with OWB.

AUDI, Ingolstadt | 02/2005 – 06/2006 Oracle Consultant and DBA

• Operations, installation and maintenance of Oracle 9i/10g and IAS 10g.
• RMAN, Oracle RLS, Oracle HTMLDB, Veritas Cluster, Solaris and AIX / HACMP.
• Database cloning and migration 9i → 10g; approx. 200 systems up to 4.5 TB.

Photocolor, Kreuzlingen / CH | 11/2003 – 01/2005 Project Manager / Oracle

• Implementation, configuration, technical support and acceptance of an Oracle ERP/CRM solution.
• Oracle Applications, Oracle 9i, Solaris, HP-UX, OWB and Mercury TestDirector.
• Project scope approx. 2 TB; reporting to management.

ZPD NRW, Duisburg | 05/2003 – 10/2003 Oracle Consultant

• Consulting, PL/SQL training and project planning for a nationwide Oracle Forms integration.
• Oracle on HP Superdome / HP-UX; data volume 1.2 → 2.5 TB, sizing up to 5 TB.

Messe München GmbH | 11/2002 – 05/2003 Project Manager / Oracle

• MIS/DWH solution with OWB, Discoverer, Oracle 11i / 9i and RAC.
• Architecture, design, integration, troubleshooting and consulting for data volumes of 1.5–2 TB.

Aria SA Integration, Geneva / CH | 09/2002 – 11/2002 Oracle DBA and Consultant

• Oracle 8.1.7.4 / 9i; merging the Stuttgart and Geneva databases via replication.

• Adaptation, optimization, configuration, and administration of a multi-stage GitLab instance with over 250 users
• Setup, adaptation, expansion, and optimization of infrastructure, configuration, and monitoring
• Provisioning of services and handover to production
• System environment: DependencyTrack, GitLab, Grafana, Hedgedoc, Kubernetes, Oauth2 Proxy, Openstack, Prometheus, Syseleven

• Development High-Performance ad distribution via auction
• Holistic (multi-campaign & multi-channel) advertisement placement optimization
• Algorithmic optimization for NP-Hard/NP-e
• Multiple Knapsack Problem with constraints
• Online estimation of parameters in stochastic environments

Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker

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.

• 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).

• Architect end-to-end AI/ML solutions, with a strong focus on advanced LLM applications, autonomous agentic AI workflows using MCP toolset, vLM embedding computations, and robust agentic RAG pipelines to drive real-world business impact for clients across diverse sectors.
• Designed intelligent agentic AI workflows to automate knowledge retrieval and reasoning for B2B clients, accelerating business impact.

• Partner directly with C-level leadership (CEO, CAIO, CTO) on architecture, OKR strategy, and cross-team roadmap prioritization, translating strategic goals into structured engineering requirements.
• Surfaced and mapped technical debt across the entire organization with C-level leadership and co-defined a prioritized remediation strategy, balancing debt paydown against feature delivery.
• Led code reviews and technical standards across the team, fostering a mentor-first environment with two-way feedback dialogue — pairing on complex pipeline work and unblocking junior engineers on async architecture patterns.
• Re-architected the AI companion's core processing pipeline from synchronous to asynchronous with a queue-based worker architecture, enabling horizontal scalability and cutting upload processing time ~4x (from ~22s to 5–10s) while improving response accuracy.
• Designed an AI-driven document intelligence workflow with automatic multi-document classification, per-document summarization, and relevance guardrails for the patient care journey.
• Built a unified patient memory system (short- and long-term context) bridging the document vault and chatbot into a single bidirectional, context-aware platform.

• Applied modern JavaScript features, including ES6+ syntax, destructuring, modules, array methods, and asynchronous programming, to develop efficient and readable frontend code.
• Implemented frontend integration patterns for PHP and Laravel backend services, connecting React interfaces to REST APIs and handling structured JSON data.
• Developed interactive, functional component-based frontend applications using React Hooks, JavaScript, and TypeScript, alongside backend applications and RESTful APIs using Python, Django, Flask, and FastAPI, focusing on reusable components, modular architecture, maintainability, and efficient data processing.
• Maintained a dynamic portfolio platform using PHP, Laravel, Livewire, and MySQL, implementing end-to-end functionality across frontend interfaces, backend services, and database operations.
• Validated server-side request handling, routing, middleware, and form validation using Laravel features to support reliable application workflows and consistent data processing.
• Designed and managed relational database structures using MySQL and Laravel Eloquent ORM, implementing data models, relationships, database migrations, and efficient queries for content management.
• AI-powered applications integrating Large Language Models (LLMs) through external APIs and locally hosted models, exploring practical use cases for conversational AI, intelligent automation, and AI-assisted workflows.
• Built local AI applications and developer tools for running, configuring, and interacting with locally hosted language models, gaining experience with local inference, model integration, and privacy-conscious AI workflows.
• Explored Retrieval-Augmented Generation (RAG) approaches to combine language models with external knowledge sources, enabling context-aware responses based on relevant application data and retrieved information.
• Integrated AI services with backend APIs and application components, developing reusable modules for model communication, response processing, error handling, and data exchange.

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
• Development of feature store and data synchronization between environments
• Data science: evaluation of different forecasting models, including CatBoost, Contextual Gamma and Random Forest; implementation of training pipelines using Kubeflow on Vertex AI; scaling and development of an event-driven interface using Kafka as a forecasting service; evaluation of MLFlow for model tracking and model registry
• Implementation of REST API using KeyCloak OAuth2 and OpenID (JWT)
• Monitoring: implementation of dashboards with Grafana, Prometheus, Mimir, Streamlit and Loki to monitor prediction metrics, GCP and Snowflake costs for pipelines, and system metrics
• Development of Copilot Agent Skills