NVIDIA/KAI-Scheduler
May 2025 – Jun 2025
2 Months active
Languages Used
GoMarkdownYAMLShell
Technical Skills
API DesignAPI RefactoringBackend DevelopmentBug FixesCustom Resource Definitions (CRDs)Go
Johan Jatko
PROFILE
Johan Jatko
Jani Jatko developed and enhanced scheduling features for the NVIDIA/KAI-Scheduler, focusing on improving workload stability and resource management for elastic Kubernetes workloads. He designed and implemented minimum runtime guarantees and a Minruntime Plugin, enabling configurable protection against premature preemption at both node pool and queue levels. Jani refactored API structures for reclamation, streamlined PodGroup observability, and introduced cluster preservation options to support robust test automation. His work, primarily in Go and YAML, emphasized system design, scheduler plugin development, and testing. The solutions addressed resource thrashing, improved debugging, and increased operational predictability, reflecting a deep understanding of backend and Kubernetes scheduling challenges.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
7Total
Bugs
2
Commits
7
Features
4
Lines of code
2,280
Activity Months2
Your Network
1368 people
Work History
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for NVIDIA/KAI-Scheduler: Delivered the Minruntime Plugin to protect critical workloads from preemption by enforcing configurable minimum runtimes, with queue-based and LCA resolution methods and support for elastic jobs. Implemented fixes to the Status Updater and Minruntime configuration, including proper annotation handling, and introduced a Cluster Preservation option to maintain cluster state after test runs. These changes improve workload stability, predictability, and automation efficiency across scheduling and test workflows.
2 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for NVIDIA/KAI-Scheduler: Delivered the Minruntime Plugin to protect critical workloads from preemption by enforcing configurable minimum runtimes, with queue-based and LCA resolution methods and support for elastic jobs. Implemented fixes to the Status Updater and Minruntime configuration, including proper annotation handling, and introduced a Cluster Preservation option to maintain cluster state after test runs. These changes improve workload stability, predictability, and automation efficiency across scheduling and test workflows.
June 2025
May 2025
5 Commits • 3 Features
May 1, 2025May 2025: Focused on stabilizing and improving resource guarantees, observability, and correctness for elastic workloads in NVIDIA/KAI-Scheduler. Delivered a design-driven minimum runtime guarantees feature, enhanced PodGroup observability, API simplification for reclamation paths, and a targeted bug fix for elastic workload preemption. These changes reduce resource thrash, improve scheduling predictability, and accelerate debugging and operational efficiency.
May 2025
5 Commits • 3 Features
May 1, 2025May 2025: Focused on stabilizing and improving resource guarantees, observability, and correctness for elastic workloads in NVIDIA/KAI-Scheduler. Delivered a design-driven minimum runtime guarantees feature, enhanced PodGroup observability, API simplification for reclamation paths, and a targeted bug fix for elastic workload preemption. These changes reduce resource thrash, improve scheduling predictability, and accelerate debugging and operational efficiency.
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Quality Metrics
Correctness90.0%
Maintainability88.6%
Architecture88.6%
Performance71.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
GoMarkdownShellYAML
Technical Skills
API DesignAPI RefactoringBackend DevelopmentBug FixesCustom Resource Definitions (CRDs)DevOpsGoGo ProgrammingKubernetesKubernetes SchedulingResource ManagementSchedulerScheduler Plugin DevelopmentSchedulingSystem Design
Repositories Contributed To
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