Performance tuning and capacity planning for Red Hat Enterprise Linux
Red Hat Performance Tuning: Linux in Physical, Virtual, and Cloud (RH422) teaches senior Linux® system administrators the methodology of performance tuning. This course 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.
COURSE OBJECTIVE:
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.
Following completion of this course you will have the knowledge and experience to:
• 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
TARGET AUDIENCE:
Senior Linux system administrators responsible for maximizing resource utilization through performance tuning
COURSE PREREQUISITES:
Having a RHCE certification or able to demonstrate equivalent experience
COURSE CONTENT:
Introduction to performance tuning
• Understand the basic principles of performance tuning and analysis.
Collecting, graphing, and interpreting data
• Gain proficiency in using basic analysis tools and in evaluating data.
General tuning
• Learn basic tuning theory and mechanisms used to tune the system.
Hardware profiling
• Understand and analyze hardware.
Software profiling
• Analyze CPU and memory performance of applications.
Mail server tuning
• Learn about basic storage tuning using an email server as an example.
Large memory workload tuning
• Understand memory management and tuning.
HPC workload tuning
• Understand tuning for CPU-bound applications.
File server tuning
• Understand storage and network tuning in the context of a file server application.
Database server tuning
• Tune memory and network performance using a database application as an example.
Power usage tuning
• Tune systems with power consumption in mind.
Virtualization tuning
• Tune 'host' and 'guest' for efficient virtualization.
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