Developed a highly available Kubernetes cluster with GitOps to optimize application delivery and development processes
Set up the Amazon EKS cluster using AWS CDK, including automated tests with Jest to ensure correct configuration.
Established a GitOps workflow with Flux that controls automated, versioned deployments from Git. Changes to the repository are immediately rolled out in Kubernetes, eliminating manual steps and enabling faster, reproducible deployments.
Implemented OIDC and RBAC for secure authentication and authorization.
Used Helm and Kustomize for dynamic, versioned Kubernetes deployments.
Built and integrated CI/CD pipelines with GitLab that seamlessly interact with the GitOps process to automatically roll out deployments from the repository.
Fully automated deployments without manual intervention by DevOps engineers -> drastic reduction in deployment times.
Improved consistency and traceability of infrastructure changes by combining GitOps and CDK.
Increased security and compliance through end-to-end authentication (OIDC & RBAC) and versioned infrastructure deployments.
More efficient development processes as teams commit their changes directly via Git and Flux ensures secure, automated distribution.
Technologies used: AWS IAM, AWS EKS, AWS EC2, AWS VPC, AWS S3, OIDC, RBAC, AWS CloudWatch, AWS CloudFormation, AWS Fargate, GitOps (Flux), GitLab, TypeScript, AWS CDK, Helm, Kustomize, Jest.
A client needed an SFTP solution for secure data exchange between mobile devices. AWS Transfer for SFTP offered no out-of-the-box solution for user authentication.
Developed a custom authorizer based on AWS API Gateway and Lambda.
Integrated the solution into existing AWS workflows.
Created a secure and scalable authentication structure.
Secure authentication of devices with individual user logins.
Reduced manual management effort by automating the processes.
Technologies used: AWS IAM, AWS CloudTrail, AWS CloudWatch, AWS Fargate, GitLab, TypeScript, AWS CDK, AWS Lambda, AWS API Gateway.
The client's service team wanted to build an automated cloud infrastructure with clear processes for infrastructure-as-code (IaC) and introduce maintainable CI/CD pipelines. They also needed to implement standardized AMI image creation for Windows and Linux with EC2 Image Builder.
Automated the GitLab Runner infrastructure (setup, updates, and operations).
Introduced AWS CDK to create and manage IaC templates.
Developed CI/CD pipelines tailored flexibly to client requirements.
Integrated EC2 Image Builder to automatically provide Windows and Linux AMI images - published as InnerSource under Free4All in GitLab.
Conducted workshops and enablement for the service team.
The service team now has a complete CI/CD infrastructure and can independently deploy IaC templates as well as predefined Windows and Linux images.
The introduction of AWS CDK and EC2 Image Builder simplified infrastructure management and scaling.
Deployment time for new server instances was significantly reduced through preconfigured AMIs.
Technologies used: AWS IAM, AWS EC2, AWS SAM, AWS Step Functions, AWS VPC, AWS S3, AWS CloudTrail, AWS CloudWatch, AWS Auto Scaling, AWS SSM, EC2 Image Builder, Windows Server 2022, PowerShell, AWS Fargate, GitLab, TypeScript, AWS CDK, Citrix.
A client from the energy sector needed a secure solution to allow development teams to deploy on-premises automatically while ensuring communication with Azure DevOps.
Built a secure architecture that can provide Azure DevOps agent pools.
Configured on-premises firewalls to allow secure traffic between internal services (Nexus, SonarQube) and the cloud.
Provided monitoring features to ensure data integrity.
Automatic provisioning of Azure DevOps agents within the on-premises environment.
Improved development cycles by integrating CI/CD processes with on-premises resources.
Technologies used: AWS IAM, AWS EKS, AWS EC2, AWS SAM, AWS Step Functions, AWS VPC, AWS S3, AWS CloudTrail, AWS CloudWatch, AWS CloudFormation, AWS Fargate, Azure DevOps, Terraform.
The client needed an automated deployment solution for AWS resources and containers that supports multi-account patterns and makes existing processes more efficient.
Developed a deployment pipeline based on GitLab CI/CD that uses IAM role credentials for secure access.
Implemented an AWS Landing Zone for structured management of multi-account environments and to ensure governance and security policies.
Used Docker containers for GitLab runners to optimize resource management.
Implemented AWS CloudFormation to provision infrastructure components.
Introduced a stable, reusable deployment pipeline that supports multi-account scenarios.
The AWS Landing Zone created a unified, scalable account structure that covers central security policies, network configurations, and compliance requirements.
Reduced manual configuration efforts and improved deployment speed.
Technologies used: AWS IAM, AWS ECS, AWS, AWS VPC, AWS S3, AWS CloudTrail, AWS CloudWatch, AWS CloudFormation, AWS Fargate, AWS Config, GitLab, GitLab CI/CD, Docker, Landing Zone.
A client wanted to migrate their entire IT infrastructure to the AWS public cloud to benefit from greater scalability, cost efficiency, and flexibility. The migration covered extensive systems and had to be done without interrupting ongoing operations.
Collaborated in an internal agile team at the client's (SCRUM and Kanban).
Built CI/CD pipelines to automate resource provisioning.
Advised on best practices for the migration, including implementing monitoring and security solutions.
Collaborated in an agile team at the client's (SCRUM and Kanban).
Trained internal development teams on how to use the new cloud environment.
Introduced CI/CD pipelines that reduced resource provisioning time.
Improved scalability: the infrastructure can flexibly adapt to growing demands.
Technologies used: AWS IAM, AWS EC2, AWS OpsWorks (Chef), AWS VPC, AWS VPN, AWS S3, AWS S3 Glacier, AWS Route 53, AWS Step Functions, AWS CloudTrail, AWS CloudWatch, AWS CloudFormation, AWS API Gateway, AWS Lambda, AWS SNS, AWS SQS, AWS Auto Scaling, AWS SSM, Windows Server, AWS RDS, AWS KMS, AWS ECS, AWS Config, AWS DynamoDB, AWS CloudFront.
The client needed a workflow solution to flexibly control data processes, pause workflows, and ensure that source data is processed on time.
Built a workflow orchestration based on AWS Step Functions that allows flexible control and monitoring.
Ensured data integrity through ETL processes with clearly defined milestones and deadlines.
Developed functions for monitoring and error management.
Data was successfully fetched and passed on, always within defined time targets.
The automation minimized manual interventions and increased the reliability of the processes.
Technologies used: AWS IAM, AWS EC2, AWS OpsWorks (Chef), AWS VPC, AWS S3, AWS Route 53, AWS Step Functions, AWS CloudTrail, AWS CloudWatch, AWS CloudFormation, AWS API Gateway, AWS Lambda, AWS SNS, Windows Server, AWS SSM, PowerShell.
Experienced Cloud and DevOps consultant with over 12 years of expertise in cloud architectures, Kubernetes, and CI/CD pipelines. Specialized in GitOps (Flux / ArgoCD) and infrastructure-as-code (AWS CDK, Terraform). Builds customer-focused solutions for more efficient software delivery and optimized development processes.
Technical expertise: expert in GitOps (Flux / ArgoCD) and infrastructure-as-code (AWS CDK, Terraform) to automate Kubernetes and cloud environments.
Consulting skills: successfully delivered cloud and DevOps solutions for international clients.
Communication: confident in dealing with technical and non-technical stakeholders.
Flexibility: adaptable to new technologies and challenges.
Tailored solutions: custom cloud and IT strategies that reduce costs and streamline processes.
High reliability: independent, structured, and punctual work style.
Team player mindset: promotes collaboration in agile teams.
Future focus: ongoing learning to always apply the latest technologies.
Practical advice: hands-on approach with measurable added value for your projects.
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