Observability: Logs, Metrics, Traces and Alerting Overview
The Observability: Logs, Metrics, Traces and Alerting Training Course is a comprehensive hands-on program designed for IT operations, DevOps, Site Reliability Engineering (SRE), cloud, and application support professionals who need to effectively monitor, troubleshoot, and optimize modern distributed systems. Participants will learn the core principles of observability and how to collect, analyze, and correlate logs, metrics, and distributed traces to rapidly identify, diagnose, and resolve system issues.
The course covers observability architecture, telemetry collection, monitoring strategies, dashboards, alerting, Service Level Indicators (SLIs), Service Level Objectives (SLOs), incident response, and best practices using widely adopted open-source and enterprise observability platforms. Through practical laboratories and real-world scenarios, participants will develop the skills necessary to build reliable monitoring solutions that improve application performance, system availability, and operational efficiency.
Duration 4 Days – 28 hrs.
Objectives
- Understand the principles and value of observability in modern IT environments.
- Differentiate between monitoring and observability.
- Collect and analyze logs, metrics, and distributed traces.
- Design effective monitoring and alerting strategies.
- Configure dashboards for infrastructure and application visibility.
- Implement meaningful alerts that reduce alert fatigue.
- Understand SLIs, SLOs, and Service Level Agreements (SLAs).
- Correlate telemetry data to troubleshoot complex issues.
- Apply observability best practices in cloud-native and distributed systems.
- Improve incident response and operational reliability.
Target Audience
- DevOps Engineers
- Site Reliability Engineers (SREs)
- Cloud Engineers
- Infrastructure Engineers
- Linux System Administrators
- Platform Engineers
- Application Support Engineers
- Network Operations Engineers
- IT Operations Teams
- Software Developers
- Monitoring and Operations Center (NOC) Engineers
Prerequisites
- Basic understanding of operating systems
- Basic networking knowledge
- Familiarity with cloud or server infrastructure
- Basic understanding of application architecture
- Experience with Linux command line is beneficial but not required
Course Outline
Day 1 – Foundations of Observability
Module 1: Introduction to Observability
- Evolution from monitoring to observability
- The three pillars of observability
- Modern IT operations
- Challenges in distributed systems
- Observability architecture
Module 2: Monitoring Fundamentals
- Infrastructure monitoring
- Application monitoring
- Network monitoring
- User experience monitoring
- Business service monitoring
Module 3: Telemetry Data
- Logs
- Metrics
- Traces
- Events
- Telemetry pipelines
Module 4: Observability Platforms
- OpenTelemetry concepts
- Prometheus overview
- Grafana overview
- Elasticsearch/OpenSearch overview
- Jaeger and Zipkin overview
- Enterprise observability solutions
Hands-on Lab
- Explore telemetry data
- Install a basic observability stack
- Visualize system health
- Generate sample telemetry
Day 2 – Logs and Metrics
Module 1: Log Management
- Structured logging
- Log collection
- Centralized logging
- Log aggregation
- Log retention
- Log analysis
Module 2: Metrics Collection
- Infrastructure metrics
- Application metrics
- Custom metrics
- Time-series databases
- Metric aggregation
Module 3: Dashboards
- Dashboard design principles
- Infrastructure dashboards
- Application dashboards
- Executive dashboards
- Capacity planning dashboards
Module 4: Querying and Visualization
- Filtering logs
- Searching telemetry
- Metric queries
- Data visualization techniques
- Trend analysis
Hands-on Lab
- Configure centralized logging
- Build monitoring dashboards
- Query logs
- Visualize infrastructure metrics
Day 3 – Distributed Tracing and Alerting
Module 1: Distributed Tracing
- Request lifecycle
- Trace context
- Spans
- Parent-child relationships
- Root cause analysis
Module 2: OpenTelemetry Fundamentals
- Instrumentation concepts
- Collectors
- Exporters
- SDK overview
- Data pipelines
Module 3: Alerting Strategies
- Alert lifecycle
- Threshold alerts
- Dynamic alerts
- Predictive alerts
- Composite alerts
Module 4: Reducing Alert Fatigue
- Alert prioritization
- Deduplication
- Escalation policies
- Noise reduction
- Incident workflows
Module 5: Incident Detection
- Correlating logs, metrics, and traces
- Root cause identification
- Performance bottleneck analysis
- Troubleshooting methodologies
Hands-on Lab
- Trace distributed applications
- Configure alert rules
- Simulate incidents
- Correlate telemetry data
Day 4 – Reliability Engineering and Best Practices
Module 1: Service Reliability
- Service Level Indicators (SLIs)
- Service Level Objectives (SLOs)
- Service Level Agreements (SLAs)
- Error budgets
Module 2: Observability in Cloud-Native Environments
- Kubernetes observability
- Containers
- Microservices monitoring
- Serverless monitoring
- Hybrid cloud monitoring
Module 3: Operational Best Practices
- Monitoring strategy design
- Dashboard governance
- Capacity management
- Performance optimization
- Security considerations
Module 4: Observability Architecture Design
- Telemetry pipelines
- High availability
- Scalability
- Data retention
- Cost optimization
Module 5: Capstone Project
- Build a complete observability solution
- Configure dashboards
- Implement alerting
- Investigate production incidents
- Present findings and recommendations
Hands-on Lab
- Deploy an end-to-end observability workflow
- Create operational dashboards
- Configure SLO-based alerts
- Troubleshoot a simulated production environment
- Final practical assessment
