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  • Welcome
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Lesson 06
      • Lesson 07
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Lesson 06
      • Lesson 07
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Lesson 06
      • Lesson 07
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Lesson 06
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 05
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Introduction to Infrastructure as Code & Terraform
      • HCL Declarative Syntax & Core Concepts
      • State Management & Remote Backends
      • Reusable Module Architecture
      • Terraform in CI/CD & GitOps
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Lesson 1: Cloud Service Models (IaaS, PaaS, SaaS)
      • Lesson 2: Core Cloud Infrastructure Components
      • Lesson 3: Cloud-Native Architecture
      • Lesson 4: High Availability and Disaster Recovery
      • Lesson 5: Hybrid and Multi-Cloud Strategies
      • Readme
      • Lesson 01
      • Lesson 02
      • Lesson 03
      • Lesson 04
      • Readme
      • Lesson 01
      • Kubernetes Architecture and Components
      • Lesson 02
      • Pod Lifecycle and Workload Management
      • Lesson 03
      • Services, Networking, and Ingress
      • Lesson 04
      • Stateful Workloads and Storage
      • Lesson 05
      • Kubernetes Security and RBAC
      • Lesson 06
      • Lesson 07
      • Readme
      • Introduction to CI/CD and GitOps
      • GitHub Actions Fundamentals
      • Automated Container Builds and Scanning
      • Progressive Delivery (Canary, Blue/Green)
      • GitOps and Rollback Automation with ArgoCD
      • The Three Pillars of Observability: Metrics, Logs & Traces
      • Time-Series Instrumentation with Prometheus & PromQL
      • Designing Mission-Critical Grafana Dashboards
      • OpenTelemetry Architecture & Distributed Tracing Fundamentals
      • AlertManager Configuration & Actionable Routing
      • Readme
      • Observability (Prometheus, Grafana) - Lesson 1
      • Observability (Prometheus, Grafana) - Lesson 2
      • Observability (Prometheus, Grafana) - Lesson 3
      • Observability (Prometheus, Grafana) - Lesson 4
      • Observability (Prometheus, Grafana) - Lesson 5
      • SLIs, SLOs, SLAs & Error Budget Calculations
      • Incident Command Management & On-Call Workflows
      • Structured Blameless Postmortems & Root Cause Analysis (RCA)
      • Chaos Engineering & Proactive System Testing
      • Toil Reduction & Automation
      • Readme
      • Site Reliability Engineering - Lesson 1
      • Site Reliability Engineering - Lesson 2
      • Site Reliability Engineering - Lesson 3
      • Site Reliability Engineering - Lesson 4
      • Site Reliability Engineering - Lesson 5
      • Hardware Architecture for AI: GPUs, TPUs, CUDA & Memory Bandwidth
      • Local LLM Execution with Ollama & Model Runtime Internals
      • Production LLM Serving with vLLM & Continuous Batching
      • Auto-scaling AI Workloads in Kubernetes (KEDA & GPU Nodes)
      • Monitoring LLM Latency, Token Throughput & GPU Utilization
      • Readme
      • AI Infrastructure & LLM Serving - Lesson 1
      • AI Infrastructure & LLM Serving - Lesson 2
      • AI Infrastructure & LLM Serving - Lesson 3
      • AI Infrastructure & LLM Serving - Lesson 4
      • AI Infrastructure & LLM Serving - Lesson 5
      • Designing Retrieval-Augmented Generation (RAG) Infrastructure
      • Vector Database Architecture (Qdrant, Milvus, pgvector)
      • Automated Model Weight Ingestion & Storage Pipelines
      • MLOps Lifecycle Management & Artifact Provenance
      • Real-world MLOps and Vector Database Implementation
      • Readme
      • MLOps & Vector Databases - Lesson 1
      • MLOps & Vector Databases - Lesson 2
      • MLOps & Vector Databases - Lesson 3
      • MLOps & Vector Databases - Lesson 4
      • MLOps & Vector Databases - Lesson 5
      • Platform Engineering Principles & Treating Developers as Customers
      • Designing Developer Portals & Golden Paths
      • Self-Service Dynamic Infrastructure Scaffolding & Templates
      • Building Internal Developer Platforms with Backstage
      • Measuring Developer Experience (DevEx) & Platform Adoption
      • Readme
      • Internal Developer Platform - Lesson 1
      • Internal Developer Platform - Lesson 2
      • Internal Developer Platform - Lesson 3
      • Internal Developer Platform - Lesson 4
      • Internal Developer Platform - Lesson 5
      • Highly Available Multi-Region Platform Topologies
      • Distributed Caching, Sharding & High-Throughput Architectures
      • Kubernetes Cluster Mesh & Cross-Cluster Networking
      • Active-Active and Active-Passive Failover Strategies
      • Stateful Data Replication Across Geographic Regions
      • Readme
      • Advanced Systems & Scaling - Lesson 1
      • Advanced Systems & Scaling - Lesson 2
      • Advanced Systems & Scaling - Lesson 3
      • Advanced Systems & Scaling - Lesson 4
      • Advanced Systems & Scaling - Lesson 5
      • Architectural Blueprint: Production Internal Developer Platform
      • Architectural Blueprint: Highly Scalable Enterprise AI Inference Engine
      • Integrating Platform and AI Services
      • Building the Final CI/CD and MLOps Pipelines
      • Final Review, Hardening, and Best Practices
      • Readme
      • Production Platform Capstone - Lesson 1
      • Production Platform Capstone - Lesson 2
      • Production Platform Capstone - Lesson 3
      • Production Platform Capstone - Lesson 4
      • Production Platform Capstone - Lesson 5
      • Structured System Design Frameworks for Platform Engineers
      • Whiteboard Architecture Scenarios & Trade-off Decisions
      • Behavioral Engineering Interviews & Engineering Communication
      • High-Impact Portfolio Refinement & Industry Presentation
      • Executive Engineering Leadership & Offer Negotiation
      • Readme
      • System Design & Interview Prep - Lesson 1
      • System Design & Interview Prep - Lesson 2
      • System Design & Interview Prep - Lesson 3
      • System Design & Interview Prep - Lesson 4
      • System Design & Interview Prep - Lesson 5
    • Deploying a Multi-Region Cluster Mesh
    • Deploying a Local LLM with Ollama
    • Capstone Lab: Building the Foundation
    • Mock System Design Interview & Whiteboard Exercise
    • Deploying a Backstage Developer Portal
    • Deploying Qdrant and Ingesting Embeddings
    • Instrumenting and Monitoring a Microservice
    • Implementing SLOs and Error Budgets
    • Advanced Resilience and Chaos Engineering
    • Ai Infrastructure and Gpu Management
    • Capstone Project
    • Career Advancement
    • CI CD Pipelines and Automation
    • Lab 1: Deploying a Scalable Web Application
    • Containers and Docker
    • Git Version Control
    • Deploying a VPC and EC2 Instance with Terraform
    • Internal Developer Platform
    • Deploying a Microservices Application on Kubernetes
    • Building a Complete CI/CD Pipeline with GitHub Actions and ArgoCD
    • Linux Administration
    • Linux Getting Started
    • Linux Internals
    • Mlops Training and Model Serving
    • CI/CD Pipelines & Automation - Practical Lab
    • Observability (Prometheus, Grafana) - Practical Lab
    • Site Reliability Engineering - Practical Lab
    • AI Infrastructure & LLM Serving - Practical Lab
    • MLOps & Vector Databases - Practical Lab
    • Internal Developer Platform - Practical Lab
    • Advanced Systems & Scaling - Practical Lab
    • Production Platform Capstone - Practical Lab
    • System Design & Interview Prep - Practical Lab
    • Networking Fundamentals
    • Observability Prometheus Grafana
    • Security Fundamentals
    • Sre and Chaos Engineering
    • Capstone: Global E-Commerce Platform Architecture
    • Production LLM Inference Cluster with vLLM and KEDA
    • Capstone Project: The AI Platform Portfolio
    • Platform Engineering Portfolio Launch
    • Build a Self-Service IDP for Microservices
    • End-to-End Enterprise RAG Pipeline
    • Capstone Project: Enterprise Observability Platform
    • SRE Implementation & Chaos Experiment
    • Capstone Project: Architecting a Cloud-Native Platform
    • Kubernetes Platform Engineering Capstone
    • Linux Administration
    • Linux Getting Started
    • Linux Internals
    • CI/CD Pipelines & Automation - Capstone Project
    • Observability (Prometheus, Grafana) - Capstone Project
    • Site Reliability Engineering - Capstone Project
    • AI Infrastructure & LLM Serving - Capstone Project
    • MLOps & Vector Databases - Capstone Project
    • Internal Developer Platform - Capstone Project
    • Advanced Systems & Scaling - Capstone Project
    • Production Platform Capstone - Capstone Project
    • System Design & Interview Prep - Capstone Project
    • Networking Fundamentals
    • End-to-End GitOps Deployment Pipeline for Microservices
    • Capstone: High-Availability Web Infrastructure
    • Advanced Systems & Scaling Knowledge Check
    • AI Infrastructure & LLM Serving Knowledge Check
    • Module 18 Quiz: Capstone Architecture
    • Career & System Design Quiz
    • Internal Developer Platforms Quiz
    • MLOps & Vector Databases Quiz
    • Observability Knowledge Check
    • SRE Fundamentals Quiz
    • Quiz: Cloud Platforms & Architecture
    • Kubernetes Engineering Knowledge Check
    • Linux Administration Quiz
    • Linux Getting Started Quiz
    • Linux Internals Quiz
    • CI/CD Pipelines & Automation - Knowledge Check
    • Observability (Prometheus, Grafana) - Knowledge Check
    • Site Reliability Engineering - Knowledge Check
    • AI Infrastructure & LLM Serving - Knowledge Check
    • MLOps & Vector Databases - Knowledge Check
    • Internal Developer Platform - Knowledge Check
    • Advanced Systems & Scaling - Knowledge Check
    • Production Platform Capstone - Knowledge Check
    • System Design & Interview Prep - Knowledge Check
    • Networking Fundamentals Quiz
    • CI/CD & GitOps Knowledge Check
    • Infrastructure as Code Concept Check
    • PromQL & Observability Cheat Sheet
    • Advanced Systems Architecture Cheat Sheet
    • AI Infrastructure & LLM Serving Cheat Sheet
    • Cheat Sheet: Capstone Architecture & Best Practices
    • Platform Engineering Interview Cheat Sheet
    • Internal Developer Platforms Cheat Sheet
    • MLOps & Vector DB Cheat Sheet
    • SRE Cheat Sheet
    • CI/CD & ArgoCD Commands and Concepts
    • Cheat Sheet: Cloud Architecture
    • Kubectl & Kubernetes Cheat Sheet
    • Linux Administration Learner Cheatsheet
    • Linux Administration Pro Reference
    • Linux Internals Learner Cheatsheet
    • Linux Internals Pro Reference
    • CI/CD Pipelines & Automation - Cheat Sheet
    • Observability (Prometheus, Grafana) - Cheat Sheet
    • Site Reliability Engineering - Cheat Sheet
    • AI Infrastructure & LLM Serving - Cheat Sheet
    • MLOps & Vector Databases - Cheat Sheet
    • Internal Developer Platform - Cheat Sheet
    • Advanced Systems & Scaling - Cheat Sheet
    • Production Platform Capstone - Cheat Sheet
    • System Design & Interview Prep - Cheat Sheet
    • Networking Fundamentals Learner Cheatsheet
    • Networking Fundamentals Pro Reference
    • Terraform Command & Syntax Cheat Sheet
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Curriculum Modulesmodule-12The Three Pillars of Observability: Metrics, Logs & Traces

The Three Pillars of Observability

Observability is defined by three main pillars: Metrics, Logs, and Traces.

GitOps and Rollback Automation with ArgoCDTime-Series Instrumentation with Prometheus & PromQL
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