Welcome to the Low-Latency Performance Workshop!

Introduction

Welcome to the comprehensive OpenShift Low-Latency Performance Workshop! This hands-on workshop will guide you through implementing high-performance, low-latency workloads on OpenShift 4.20 using enterprise-grade tuning techniques.

This workshop demonstrates real-world scenarios where microsecond-level latency matters, including financial trading systems, real-time gaming, IoT edge computing, and high-frequency data processing applications.

Who Will Benefit Most from Attending?

Platform Engineers & SREs — Learn advanced OpenShift performance tuning, CPU isolation, real-time kernel configuration, and automated cluster management at scale.

Application Architects — Understand how to design containerized applications for ultra-low latency requirements while leveraging performance optimization techniques.

DevOps Engineers — Master performance tuning techniques for consistent performance profile deployment across development, staging, and production environments.

What Content Is Covered?

These are the key modules that will be covered:

  • Module 1: Low-Latency Fundamentals: Understanding latency requirements, OpenShift performance features, and workshop architecture overview.

  • Module 2: Environment Setup and Verification: Verifying your pre-configured SNO cluster and understanding the installed operators.

  • Module 3: Baseline Performance Testing: Using kube-burner to establish performance baselines and measure pod creation latency metrics.

  • Module 4: Core Performance Tuning: Implementing Performance Profiles for CPU isolation, HugePages configuration, and real-time kernel enablement.

  • Module 5: Low-Latency Virtualization: Optimizing OpenShift Virtualization for low-latency workloads with SR-IOV networking and VM performance tuning.

  • Module 6: Monitoring & Validation: Advanced performance monitoring, validation tools, and best practices for maintaining low-latency environments.

  • Module 7: GPU Workloads (Optional): Configuring and optimizing GPU workloads on OpenShift using the NVIDIA GPU Operator.

What is Low-Latency Performance?

  • Microsecond Response Times: Applications requiring sub-millisecond response times for critical operations

  • CPU Isolation: Dedicated CPU cores for time-sensitive workloads without interference from system processes

  • Real-time Kernels: Deterministic scheduling and reduced jitter for predictable performance

  • Hardware Acceleration: Direct hardware access via SR-IOV for network-intensive applications

  • Memory Optimization: HugePages and NUMA-aware allocation for reduced memory management overhead

Workshop Technologies

This workshop leverages several OpenShift 4.20 enterprise features:

  • Node Tuning Operator: Built-in operator for automated node tuning and Performance Profiles

  • SR-IOV Network Operator: High-performance networking with direct hardware access

  • OpenShift Virtualization: KubeVirt-based virtual machines with performance optimization

  • Performance Profiles: Declarative CPU isolation, HugePages, and real-time kernel configuration

Why Choose OpenShift for Low-Latency Workloads?

Enterprise-Grade Performance: OpenShift provides certified, supportable low-latency capabilities backed by Red Hat engineering and extensive performance testing across diverse hardware platforms.

Automated Lifecycle Management: OpenShift provides declarative Performance Profiles that enable consistent performance tuning across nodes without manual intervention.

Production-Ready Integration: Native integration between performance tuning, container orchestration, and enterprise security provides a complete platform for mission-critical low-latency applications.

Next Steps

Ready to start? Begin with Module 1 to understand the fundamentals, then progress through hands-on exercises that build upon each other.

Learning Path:
1. Start Here: Module 1 - Low-Latency Fundamentals
2. Environment Setup: Module 2 - Environment Setup and Verification
3. Performance Baseline: Module 3 - Baseline Testing
4. Core Optimization: Module 4 - Performance Tuning

Additional Resources:
* OpenShift Performance Documentation
* Kube-burner Performance Testing
* OpenShift Virtualization Documentation

Requirements for the Lab Environment

Prerequisites:
* Single Node OpenShift (SNO) 4.20+ cluster with cluster-admin privileges
* SSH access to bastion host (pre-configured)
* Terminal access with oc CLI configured (pre-configured on bastion)
* Basic understanding of Kubernetes/OpenShift concepts

Hardware Recommendations:
* Worker nodes with dedicated CPU cores (minimum 8 cores per node)
* At least 32GB RAM per worker node for performance testing
* SR-IOV capable network interfaces (for Module 5)
* NVMe storage for optimal I/O performance