Observability and Telemetry
Learn to monitor, measure, and troubleshoot modern applications using telemetry data and observability best practices.Preview Observability and Telemetry course
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Clear understanding of observability principles and telemetry data
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Hands-on experience with tools like Prometheus, Grafana, and Jaeger
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Ability to collect, visualize, and analyze metrics, logs, and traces
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Skills to troubleshoot performance issues in distributed systems
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Site Reliability Engineers (SREs)
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DevOps and Platform Engineers
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Backend Developers and Cloud Architects
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QA and Incident Response Teams
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Anyone building or maintaining microservices and distributed systems
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Begin by understanding observability fundamentals and use cases
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Instrument your own applications with telemetry libraries
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Set up end-to-end observability stacks using open-source tools
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Use real-world failure scenarios to simulate debugging and alerting
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Apply learned concepts to optimize system performance and uptime
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Complete the final project to demonstrate observability planning and implementation
Course/Topic 1 - Coming Soon
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The videos for this course are being recorded freshly and should be available in a few days. Please contact info@uplatz.com to know the exact date of the release of this course.
By the end of this course, you will be able to:
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Define observability and explain its importance in modern systems
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Collect and analyze telemetry data: metrics, logs, and traces
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Instrument applications with OpenTelemetry SDKs
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Build dashboards and alerts using Prometheus and Grafana
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Trace transactions across microservices using Jaeger or Zipkin
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Monitor logs using Loki or ELK stack
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Apply observability to real-world incident response and performance tuning
Course Syllabus
Module 1: Introduction to Observability
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What is observability?
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Observability vs. monitoring
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Telemetry types: metrics, logs, traces
Module 2: Metrics Collection and Monitoring
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Setting up Prometheus
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Exporters and time-series metrics
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Grafana for visualization and dashboards
Module 3: Log Aggregation and Analysis
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Structured vs. unstructured logs
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Loki setup and queries with LogQL
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Using Elastic Stack (ELK) for advanced log management
Module 4: Distributed Tracing
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Introduction to tracing and span concepts
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OpenTelemetry and Jaeger integration
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End-to-end transaction tracking
Module 5: Instrumentation with OpenTelemetry
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SDKs for Python, Node.js, Java
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Manual vs. automatic instrumentation
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Custom metrics and trace propagation
Module 6: Alerting and Incident Response
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Creating meaningful alerts
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Avoiding alert fatigue
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Incident tracking with Alertmanager and integrations
Module 7: Observability for Microservices and Kubernetes
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Monitoring containerized apps
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Kubernetes-native observability tools
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Service meshes and tracing (e.g., Istio + Kiali)
Module 8: Final Project
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Implement full observability stack for a sample app
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Simulate failure, observe patterns, create remediation plan
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Present metrics, traces, and logs analysis
This course prepares you for roles such as:
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Site Reliability Engineer (SRE)
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Observability Engineer
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DevOps and Infrastructure Engineer
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Cloud Monitoring Specialist
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Platform Reliability Consultant
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What is observability, and how is it different from monitoring?
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What are the three pillars of observability?
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How do metrics, logs, and traces complement each other?
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What is OpenTelemetry and why is it important?
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How does Prometheus collect and store metrics?
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What is the role of Grafana in observability workflows?
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How do you implement distributed tracing with Jaeger?
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What are some common issues in alerting systems and how do you avoid them?
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How can observability help with root cause analysis in microservices?
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What tools would you use to implement observability in a Kubernetes environment?