Workshop details

Timing and schedule

Full workshop (3 hours)

  • Module 1: User workload monitoring (60 minutes)

  • Module 2: Logging with LokiStack (60 minutes)

  • Module 3: Distributed tracing and OpenTelemetry (75 minutes)

Abbreviated workshop (90 minutes)

  • Module 1: User workload monitoring (30 minutes)

  • Module 2: Logging basics (30 minutes)

  • Module 3: Distributed tracing and OpenTelemetry overview (30 minutes)

Technical requirements

Software versions

  • Red Hat OpenShift Container Platform 4.21

  • Cluster Observability Operator 1.3.1

  • Red Hat OpenShift Logging 6.4

  • Red Hat build of OpenTelemetry 0.140.0-2

  • Tempo Operator 0.19.0-3

  • Network Observability Operator 1.10.1

Environment access

Participants need access to:

  • Red Hat OpenShift cluster (provided during workshop)

  • Namespace with admin privileges

  • OpenShift CLI (oc) - pre-configured in lab terminal

  • Web browser (Chrome, Firefox, Safari, Edge)

  • Pre-deployed observability stack via GitOps

Pre-configured components

The following components are already deployed and configured in your lab environment:

  • User Workload Monitoring: Prometheus, Thanos, Alertmanager

  • Logging: LokiStack with storage configured

  • Distributed Tracing: Tempo with OpenShift integration

  • OpenTelemetry: Operator and collector deployed

  • Sample Application: Microservices demo application for testing

Network requirements

  • Internet connectivity for accessing OpenShift console

  • Access to OpenShift cluster API

  • Browser access to monitoring dashboards

Environment setup

Pre-workshop checklist

□ OpenShift cluster access confirmed - Test login credentials □ Terminal access verified - Confirm oc CLI works □ Browser access tested - Open OpenShift console □ Sample application running - Verify demo app is deployed □ GitOps sync confirmed - Check ArgoCD application status

Setup validation

Participants should run these commands to verify setup:

# Verify OpenShift CLI
oc version

# Test cluster connectivity
oc whoami

# Check current project
oc project

# Verify observability stack
oc get pods -n openshift-user-workload-monitoring
oc get pods -n openshift-logging
oc get pods -n openshift-tempo-operator

Troubleshooting guide

Common setup issues

Problem: "oc command not found" → Solution: The oc CLI should be pre-installed in the lab terminal. If missing, refresh your browser.

Problem: "Permission denied" errors → Solution: Verify you’re using the correct namespace. Check with oc project and switch if needed using oc project <namespace-name>.

Problem: "Unable to connect to OpenShift console" → Solution: Verify you’re using the correct console URL from the lab interface: OpenShift Console

Problem: "Prometheus metrics not appearing" → Solution: Check ServiceMonitor configuration and verify pods are running: oc get servicemonitor

Problem: "Logs not visible in Loki" → Solution: Verify ClusterLogForwarder is configured: oc get clusterlogforwarder -n openshift-logging

During workshop support

  • Use the lab terminal for all command line operations

  • Console access is available via OpenShift Console

  • All credentials are provided in the lab interface

  • Sample applications are pre-deployed for testing

Follow-up resources

Next steps for participants

Additional learning paths

  • Intermediate: Advanced monitoring with custom exporters and Grafana dashboards

  • Advanced: Multi-cluster observability with OpenShift Cluster Observability Operator

  • Certification: Red Hat Certified Specialist in OpenShift Administration

Module breakdown

Module 1: User workload monitoring

Focus: Configure Prometheus monitoring for custom application metrics

Topics:

  • Understanding the 3 pillars of observability

  • Creating ServiceMonitor resources

  • Writing PromQL queries

  • Building custom dashboards

  • Configuring Alertmanager rules

Hands-on exercises: 5

Module 2: Logging with LokiStack

Focus: Implement centralized logging and log analysis

Topics:

  • LokiStack architecture and components

  • Writing LogQL queries

  • Correlating logs with metrics

  • Creating log-based alerts

  • Log retention and storage management

Hands-on exercises: 5

Module 3: Distributed tracing and OpenTelemetry

Focus: Visualize request flows across microservices and activate a full three-signal telemetry pipeline

Topics:

  • Distributed tracing concepts: traces, spans, context propagation

  • Tempo deployment and component architecture

  • Two-tier sidecar-to-central OpenTelemetry Collector topology

  • Application instrumentation with the OpenTelemetry Go SDK

  • Deploying a sidecar OpenTelemetryCollector and Instrumentation CR

  • Activating the telemetry pipeline without image rebuilds

  • Querying live traces with TraceQL in the OpenShift console

  • Span metrics connector generating RED metrics from traces

  • Zero-code Python auto-instrumentation via the Operator

  • Correlating traces, metrics, and logs across all four services

Hands-on exercises: 9

Authors and contributors

Primary Author: Magnus Bengtsson <mbengtss@redhat.com>

Last Updated: April 2026

Workshop Version: 1.1

Contact Information:

  • Workshop feedback: Share via lab interface

  • Technical questions: Consult documentation links provided

  • Content updates: Submit issues via workshop repository