Daniel Kłobuszewski
Staff Software Engineer at Google
Warsaw, Masovian Voivodeship, Poland
Summary
🤩
Rockstar🎓
Top SchoolDaniel Kłobuszewski is a Staff Software Engineer based in Warsaw with nine years of experience building and scaling cloud-native systems at Google, where he progressed from distributed data pipelines to leading Kubernetes monitoring and autoscaling efforts. He combines strong backend and DevOps skills, contributing to high-profile open-source projects like Kubernetes autoscaler and GoogleCloudPlatform tooling—work that includes improving DaemonSet eviction logic and building a kubectl-driven scaler for fluentd. His career spans production-facing infrastructure, instrumentation for GKE, and automation that tightens monitoring and resource management for large clusters. Trained in computer science and artificial intelligence, he brings a research-minded approach to practical engineering problems and a track record of shipping reliable, well-instrumented systems at scale. An uncommon strength is his blend of hands-on scripting and deep autoscaler internals, enabling both quick operational fixes and long-term architectural improvements.
9 years of coding experience
15 years of employment as a software developer
Student CCNA Course, Student CCNA Course at Polish-Japanese Academy of Information TechnologyMaster of Science (MSc) Artificial Intelligence, Master of Science (MSc) Artificial Intelligence at Warsaw University of TechnologyComputer Science, Computer Science at Oxford Brookes University
Polish, English, Japanese
Github Skills (18)
kubernetes10
scripting10
kubectl10
gcp10
automation10
script10
go10
prometheus10
kubernetes-pods10
sh10
automations10
shell10
devops10
testing9
monitoring9
Programming languages (7)
Github contributions (5)
GoogleCloudPlatform/k8s-stackdriver
Sep 2017 - Aug 2021
Role in this project:
DevOps Engineer
DevOps EngineerContributions:14 releases, 9 reviews, 95 commits in 4 years
Contributions summary:Daniel primarily contributed to the `fluentd-gcp-scaler` component, implementing initial versions and addressing scaling issues. They developed a shell script (`scaler.sh`) that interacts with Kubernetes using `kubectl` to set resource requests and limits for the `fluentd-gcp` container. They also made changes to the `prometheus-to-sd` component, including improvements to scrape and export intervals and fixing bugs. Their contributions demonstrate a focus on infrastructure automation and improving monitoring.
kubernetes/autoscaler
Jun 2017 - Dec 2022
Autoscaling components for Kubernetes
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:11 releases, 513 reviews, 58 commits in 5 years 7 months
Contributions summary:Daniel primarily focused on enhancing the cluster autoscaler's functionality, specifically around the eviction of DaemonSet pods during node scale down. They added a flag to control DaemonSet eviction on non-empty nodes, allowing for more granular control over the scaling process. Further contributions include enabling opt-in/out mechanisms for DaemonSet pod eviction, and allowing for version updates of dependencies by automating the versioning process. The user also made improvements in logging and the internal mechanisms of the auto scaler.
k8skubernetesautoscaling
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