Matthias Haeussle
Kubernetes and observability expert | Java containerization specialist
About
Matthias Haeussle is a technical speaker specializing in Kubernetes observability and Java application deployment in containerized environments. He focuses on practical tooling and frameworks that help development teams monitor and manage cloud-native applications effectively.
Matthias delivers technical deep-dives on observability solutions, guiding teams from basic Kubernetes tooling like k9s through to comprehensive OpenTelemetry implementations. His expertise extends to comparing distributed system patterns across various approaches, including traditional frameworks, Kubernetes-native solutions, service meshes, and eBPF-based technologies.
He also addresses the practical challenges of containerizing Java applications, examining different approaches from Dockerfiles to specialized tools like Jib to help teams determine the most effective deployment strategies for their specific contexts. He has presented at Devoxx, sharing his knowledge on cloud-native architecture and operational best practices with developer communities.
What Matthias Talks About
Implementing observability for Kubernetes applications with OpenTelemetry
Comparing distributed system patterns: frameworks, Kubernetes, service mesh, and eBPF
Best practices for containerizing and running Java applications
Kubernetes tooling and monitoring strategies for production environments
Choosing the right approach for Java container deployment (Dockerfiles, Jib, and alternatives)
Talks4
Dockerfiles, Jib ..., what's the best way to run your Java code in Containers?
A typical workflow in a modern software dev project often looks like: Build code, put the built artifact into a container image, put the container image into a registry and deploy to Kubernetes. Each step has it’s own requirements and pitfalls alike. The overall goal is most often to bake those steps into easily repeatable pipelines and enable a high degree of automation and standardization. Dockerfiles seems to be the choice with the highest adoption when it comes to containerizing code artefacts. However most Dockerfiles (and also most sample's of Dockerfiles you find in tutorials) do not exploit it to the full potential. There are a lot of improvements to be done in how to build and optimize for VM-based applications. The talk will give deeper insights by comparing (simple and multi-stage) Dockerfiles to Cloud-Native Buildpacks (buildpacks.io/paketo.io), Google’s JIB and jlink under the evaluation criteria of - build time - build size - standardization - robustness - memory configuration - security The examples and live demo will have certain focus on Java-based frameworks (Spring Boot, Quarkus, Micronaut), but coverage of other languages will also be included and highlighted. Github @ https://github.com/maeddes/java-and-container Slides @ https://speakerdeck.com/maeddes/options-galore-from-source-code-to-container-image #vdc25
From k9s to OpenTelemetry: A guide to observability for your apps in K8s
From k9s to OpenTelemetry: A guide to observability for your apps in K8s
More Talks
Distributed patterns compared: Frameworks vs. K8s vs. Service Mesh vs. eBPF
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