Observability: Logs, Metrics, Traces and Alerting

Inquire now

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

 

Inquire now

Best selling courses

The Data Analytics with DAX, Python, SQL, and Business Intelligence Tools Training Course provides participants with practical knowledge and skills for collecting, preparing, analyzing, modeling, and visualizing data to support informed business decision-making. The course combines key data analytics technologies and techniques, including Python, SQL, DAX (Data Analysis Expressions), Power BI, data modeling, data transformation,...

The Project Management – SDLC (Software Project Management: The Complete Course) Training Course is a comprehensive program designed to equip project managers, software development leaders, business analysts, product owners, and IT professionals with the knowledge and practical skills required to successfully manage software development projects throughout the entire Software Development Life Cycle (SDLC). This course...

Warehouse Operations and Inventory Management Training Course     Duration 2 Days – 14 hrs.   Overview   This course provides a practical understanding of warehouse operations and inventory management for personnel who supervise, review, or audit warehouse processes. It covers the movement of goods from receiving through dispatch, with emphasis on warehouse layout, storage systems, picking strategies, stock rotation, inventory accuracy, and operational controls.   Participants will learn to identify process weaknesses, investigate stock discrepancies, reduce shrinkage, and interpret warehouse productivity indicators. The course connects day-to-day warehouse activities with the records, controls, and performance measures needed for effective supervision and auditing.   Objectives  

  • Explain warehouse processes and their impact on inventory accuracy and service performance.
  • Evaluate warehouse layouts, storage systems, and product locations.
  • Identify appropriate controls for receiving, put-away, storage, picking, and dispatch.
  • Apply First-In, First-Out (FIFO) and First-Expired, First-Out (FEFO) principles.
  • Compare picking strategies based on order characteristics and operational requirements.
  • Identify causes of inventory discrepancies and recommend corrective actions.
  • Develop a cycle counting approach based on inventory value, movement, and risk.
  • Recognize sources of shrinkage and recommend preventive and detective controls.
  • Interpret warehouse productivity and inventory performance KPIs.
  • Review warehouse processes using supporting records, observations, and control evidence.
        Target Audience  
  • Warehouse supervisors, team leaders, and managers.
  • Inventory controllers and stock control personnel.
  • Logistics and distribution supervisors.
  • Internal auditors and operational compliance personnel.
  • Supply chain and operations professionals.
  • Personnel responsible for reviewing warehouse controls and performance.
  Prerequisites  
  • Basic familiarity with warehouse, logistics, or inventory activities.
  • General understanding of business processes and operational documentation.
  • Basic numerical skills, including percentages and simple calculations.
  • Basic spreadsheet skills are helpful.
  • No prior experience with a specific Warehouse Management System (WMS) is required.
   

Course Outline

  Day 1: Warehouse Processes, Layout, and Storage Controls Module 1: Warehouse Operations and Process Controls  
  • Warehouse roles within the supply chain.
  • End-to-end flow: receiving, put-away, storage, replenishment, picking, packing, and dispatch.
  • Physical stock movement and corresponding system transactions.
  • Responsibilities, authorization, and segregation of duties.
  • Common operational weaknesses and audit evidence.
  Module 2: Warehouse Layout and Storage Systems  
  • Functional zones, movement paths, and space utilization.
  • Receiving, storage, picking, staging, and dispatch areas.
  • Storage options: floor stacking, shelving, pallet racking, and bin storage.
  • Fixed and dynamic location systems.
  • Product slotting based on movement, size, handling needs, and compatibility.
  • Layout bottlenecks and their effects on productivity and inventory control.
  Module 3: Receiving and Put-Away  
  • Purchase orders, delivery documents, and expected receipts.
  • Quantity, condition, and item identification checks.
  • Recording shortages, overages, damage, and discrepancies.
  • Controls for acceptance, quarantine, and release.
  • Put-away rules and location confirmation.
  • Traceability through labels, barcodes, lot numbers, and serial numbers.
  • Timely recording of receipts and stock movements.
  Module 4: Storage, Stock Rotation, and Replenishment  
  • Storage discipline and location integrity.
  • FIFO and FEFO principles, applications, and limitations.
  • Batch, lot, and expiry-date management.
  • Controls for slow-moving, obsolete, damaged, and expired stock.
  • Replenishment of picking locations.
  • Supervision and review of stock rotation compliance.
    Day 2: Order Fulfillment and Inventory Accuracy Module 5: Picking Strategies and Order Fulfillment  
  • Discrete, batch, zone, and wave picking.
  • Selecting picking strategies for different order profiles.
  • Pick paths, location sequencing, and travel reduction.
  • Replenishment coordination and stock availability.
  • Picking verification and error prevention.
  • Packing, staging, and dispatch confirmation.
  • Handling short picks, substitutions, cancellations, and returns.
  Module 6: Inventory Records and Accuracy Controls  
  • Item master data, units of measure, and location records.
  • On-hand, available, allocated, and quarantined stock.
  • Transaction controls for receipts, transfers, issues, returns, and adjustments.
  • Common causes of physical and system stock mismatches.
  • Barcode scanning and WMS control points.
  • Inventory reconciliation and supporting documentation.
  • Measuring inventory accuracy and interpreting discrepancies.
  Module 7: Cycle Counting and Physical Inventory  
  • Cycle counting versus full physical inventory.
  • ABC classification and risk-based count priorities.
  • Count frequency based on value, movement, and discrepancy history.
  • Count preparation, blind counting, and movement controls.
  • Recounts, variance investigation, and adjustment approval.
  • Root cause analysis and corrective action follow-up.
  • Reviewing the effectiveness of the counting program.
  Module 8: Shrinkage Reduction and Inventory Protection  
  • Sources of shrinkage: loss, damage, theft, misplacement, and recording errors.
  • Access controls and accountability for stock movements.
  • Controls for high-value and sensitive inventory.
  • Returns, write-offs, scrap, and disposal controls.
  • Exception reporting and unusual transaction patterns.
  • Investigating recurring losses and unexplained adjustments.
  • Preventive and detective controls for shrinkage reduction.
    Day 3: Performance Management, Process Review, and Improvement Module 9: Warehouse Productivity and Inventory KPIs  
  • Receiving productivity and dock-to-stock time.
  • Put-away productivity and replenishment performance.
  • Picking productivity and order accuracy.
  • Inventory accuracy and cycle count variance.
  • Space utilization and storage capacity.
  • Shrinkage, damage, and expiry indicators.
  • Defining KPI formulas, data sources, and reporting boundaries.
  • Interpreting trends while balancing speed, accuracy, and service.
      Module 10: Supervising and Auditing Warehouse Processes  
  • Process mapping and identification of critical control points.
  • Reviewing procedures against actual warehouse practices.
  • Tracing transactions from documents to systems and physical stock.
  • Reviewing approvals, access rights, and segregation of duties.
  • Identifying control gaps and recurring process exceptions.
  • Documenting findings with clear supporting evidence.
  • Prioritizing corrective actions and tracking closure.
  Module 11: Warehouse Improvement Planning  
  • Identifying bottlenecks, unnecessary movement, and rework.
  • Improving layout, slotting, and picking arrangements.
  • Addressing inventory discrepancy root causes.
  • Standardizing transaction recording and exception handling.
  • Assigning improvement owners and measurable targets.
  • Monitoring results and sustaining operational improvements.
  Module 12: Capstone — Warehouse Operations and Inventory Improvement Plan  
  • Review a warehouse scenario containing layout, transaction, inventory, and performance information.
  • Identify weaknesses across receiving, put-away, storage, picking, and dispatch.
  • Recommend appropriate FIFO or FEFO controls.
  • Develop a cycle counting and inventory reconciliation plan.
  • Propose controls to reduce shrinkage and improve traceability.
  • Select relevant KPIs and define their calculation and reporting requirements.
  • Produce a prioritized improvement plan with responsibilities and expected outcomes.
 

This course develops the foundational knowledge and practical skills needed to configure, administer, and maintain the ServiceNow platform. Participants explore platform navigation, instance configuration, application collaboration, self-service, automation, database management, security, and configuration migration. The proposed five-day duration accommodates foundational learning, configuration activities, and an integrated capstone. Duration 5 Days – 35 hrs.   Objectives...

Duration: 5 days – 35 hrs   Overview The “SOC Network and Threat Detection and Analysis” training course is designed to equip Security Operations Center (SOC) analysts and IT security professionals with the skills and knowledge required to detect, analyze, and respond to network threats effectively. This comprehensive course covers essential topics such as threat...

Duration 1 day – 7 hrs   Overview   This 1-day training builds upon basic warehouse operations knowledge and introduces key logistics concepts involved in the movement and coordination of goods—especially wet and dry food items—within and outside the warehouse. Participants will explore transport logistics, inbound and outbound coordination, documentation practices, and cold chain considerations,...

Duration 2 days – 14 hrs   Overview   This hands-on course provides an introduction to Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data. The training focuses on how developers and QA professionals can leverage Splunk to gain insights from logs and metrics, improve application observability, detect anomalies, and support test validation....

Duration 3 days – 21 hrs   Overview.   This course is designed for fresh graduates aspiring to build a career in Data Science. It introduces the fundamentals of data science, focusing on data analysis, visualization, and basic machine learning concepts using Python. The course provides hands-on practice with real-world datasets, equipping participants with the...

// BG EARTH WHEN NOT PLAYING

We use cookies on our website to personalize your experience by storing your preferences and recognizing repeat visits. By clicking “Accept”, you agree to the use of all cookies. You can also select “Cookie Settings” to adjust your preferences and provide more specific consent. Cookie Policy