Cloud Architect & Software Engineer (DevOps mindset, Kubernetes, Infrastructure as Code)

I help companies on their cloud native journey.

With several years of experience in both software engineering and the operations side of designing and building scalable applications, I truly believe a strong DevOps mindset is key to continuously ship successful products. I support your teams adopting Docker, Kubernetes and cloud native technologies not only with my technological expertise, but also from a cultural perspective. Implementing new features, evolving the cloud architecture and running applications reliably in the cloud needs a thorough understanding of these disciplines for each other. I help you navigating in the cloud native ecosystem and support your teams picking up that same spirit I am carrying.

How can I support your business?
I provide consulting and hands-on support with my technological expertise in...

Designing and implementing scalable cloud native applications: Microservices, Backends and APIs in Java/Spring, Node.JS or Golang. Event-based, message-driven systems with focus on resiliency and observability. Leveraging different levels of testing.

Cloud architecture and infrastructure automation: Using infrastructure and managed services of Microsoft Azure, Google Cloud, AWS. Networking and access management. Automating the cloud infrastucture provisioning using Pulumi, terraform or CDK.

Managing highly-available container-based applications on Kubernetes: Leveraging managed Kubernetes offerings like AKS, GKE or EKS. Continuously deploying your applications using Helm, CDK8S or Pulumi. Building reliable deployment pipelines using GitOps principles (e.g. Flux).

Making use of the rich cloud native ecosystem to improve the Kubernetes experience: Centralized Logging and monitoring with fluentd, promtail, loki, ELK, Prometheus and Grafana. Ingress controllers, Network Policies, Secrets and Certificate management.

Packaging and optimizing container images and streamlining build processes: Improving docker images using multistage builds and intelligent layer caching to optimize build times and image size. Building for mutliple architectures, image hardening and trust. Of course in an automated way, e.g. Gitlab CI

Data stream processing and analytics: Processing data streams on Kafka, Confluent Cloud or other messaging systems with Kafka Streams or Apache Flink. Making use of specialized databases for analytics like elasticsearch, InfluxDB or Postgres.

Internet of Things and Industry use cases: Leveraging Cloud IoT offerings and messaging systems, MQTT brokers, LoRaWAN. Experience in containerized edge computing.