Red Hat Performance Tuning: Linux in Physical, Virtual, and Cloud with exam (RH443) teaches and validates skills related to the methodology of performance tuning for senior Linux® system administrators. This offering discusses system architecture with an emphasis on understanding its implications on system performance, performance adjustments, open source benchmarking utilities, networking performance, and tuning configurations for specific server use cases and workloads.
This course is based on Red Hat® Enterprise Linux 8.
Note on the exam:
The subscription duration of 365 days starts upon order submission. Cancelation of individual exam sessions is not allowed Exam session fees are nonrefundable. Non-Cancelable components: No part of any Bundles that includes both non-cancelable and cancelable components may be canceled.
Who should attend
Senior Linux system administrators responsible for maximizing resource utilization through performance tuning
Become a Red Hat Certified Engineer (RHCE®), or demonstrate equivalent experience
Impact on the organization
This course is intended to develop the skills needed to improve infrastructure performance, increase system utilization, reduce downtime, and improve responsiveness to system failures.
Red Hat has created this course in a way intended to benefit our customers, but each company and infrastructure is unique, and actual results or benefits may vary.
Impact on the individual
As a result of attending this course, you should be able to obtain, analyze, and interpret system performance metrics, then use these metrics to help increase cost effectiveness, maximize application performance, and make better decisions about investment in hardware or cloud resources.
- Analyze and tune for resource-specific scenarios
- Applying tuning profiles with the tuned tool
- Tune in virtual environments (hosts and guests)
- Trace and profile system events and activities
- Tune resource limits and utilization using systemd-integrated cgroups
- Gather performance metrics and benchmarking data