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Kiel Friedt

PROFILE

Kiel Friedt

Kiel Friedt developed and documented advanced benchmarking and performance tuning workflows for MongoDB and cloud networking within the madeline-underwood/arm-learning-paths repository. Over three months, Kiel delivered a reproducible ARM benchmarking process for MongoDB 8.0 using Bash and Markdown, enhanced Linux installation guides, and created a comprehensive learning path for setting up and testing 3-node MongoDB replica sets with YCSB. Additionally, Kiel authored an IRQ Tuning Guide to help engineers optimize cloud network performance, providing scripts and practical documentation for Linux environments. The work demonstrated depth in system administration, database management, and performance testing, supporting scalable and repeatable engineering practices.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

4Total
Bugs
0
Commits
4
Features
3
Lines of code
852
Activity Months3

Work History

September 2025

2 Commits • 1 Features

Sep 1, 2025

September 2025 performance-focused update: Delivered a new IRQ Tuning Guide for Cloud Network Performance within the madeline-underwood/arm-learning-paths repository. This enhances engineers’ ability to diagnose and optimize IRQ-related bottlenecks in cloud environments, accelerating performance validation and cloud-ready tuning practices.

April 2025

1 Commits • 1 Features

Apr 1, 2025

April 2025: Focused on delivering a comprehensive MongoDB learning path enhancement in madeline-underwood/arm-learning-paths, introducing a 3-node replica set setup and benchmarking guide, plus content refactors to improve clarity around configuration, replica set initialization, and performance testing with YCSB. This work lays the groundwork for repeatable benchmarks and faster onboarding into distributed MongoDB scenarios.

December 2024

1 Commits • 1 Features

Dec 1, 2024

Month 2024-12: Delivered ARM benchmarking enablement for MongoDB 8.0 with YCSB learning path documentation and updated Linux install guides. This work established a reproducible benchmarking workflow on ARM, clarified installation and configuration steps for newer MongoDB versions, and prepared the team for upcoming performance experiments.

Activity

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Quality Metrics

Correctness92.6%
Maintainability87.6%
Architecture87.6%
Performance87.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

BashConsoleMarkdown

Technical Skills

Cloud ComputingContent ManagementDatabase BenchmarkingDatabase ManagementDocumentationLinuxNetworkingPerformance TestingPerformance TuningServer AdministrationSystem Administration

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

madeline-underwood/arm-learning-paths

Dec 2024 Sep 2025
3 Months active

Languages Used

BashConsoleMarkdown

Technical Skills

Database BenchmarkingDocumentationSystem AdministrationCloud ComputingDatabase ManagementPerformance Testing

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