Visão Geral

Este curso oferece uma compreensão completa da solução Elastic Observability, capacitando o aluno a monitorar logs, métricas, traces (APM) e disponibilidade de sistemas utilizando a Elastic Stack (Elasticsearch, Kibana, Beats e Elastic Agents).
O participante aprenderá a configurar pipelines de observabilidade, criar dashboards, investigar problemas de performance e implementar práticas modernas de observabilidade para ambientes cloud-native, containers e microserviços.

Objetivo

Após realizar este curso Elastic Observability, você será capaz de:

• Entender a arquitetura completa da Elastic Stack voltada para observabilidade.
• Configurar ingestion pipelines para logs, métricas e traces.
• Utilizar Elastic APM para monitorar aplicações.
• Criar dashboards eficientes no Kibana.
• Implementar alertas inteligentes e detecção de anomalias.
• Aplicar tracing distribuído em ambientes de microserviços.
• Implementar monitoramento de disponibilidade (Uptime/Synthetics).
• Diagnosticar problemas de performance e incidentes usando dados unificados.

Publico Alvo

• Profissionais de DevOps
• Engenheiros de Observabilidade
• SRE (Site Reliability Engineers)
• Administradores de Sistemas
• Analistas de Infraestrutura e NOC
• Desenvolvedores que desejam entender performance e tracing
• Equipes de suporte e operações

Pre-Requisitos

• Conhecimento básico de infraestrutura (Linux, redes, servidores).
• Noções gerais sobre logs, métricas e monitoramento.
• Familiaridade com Docker ou Kubernetes é desejável, mas não obrigatória.

Materiais

Conteúdo Programatico

Module 1 – Introduction to Elastic Observability

1. What is Elastic Observability
2. Elastic Stack architecture (Elasticsearch, Kibana, Beats, Elastic Agent)
3. Observability vs Monitoring
4. Key concepts: Logs, Metrics, Traces, Uptime

Module 2 – Installing and Configuring Elastic Stack

1. Installing Elasticsearch
2. Installing Kibana
3. Configuring Elastic Agents
4. Fleet Server introduction
5. Understanding indices, pipelines, ingestion methods

Module 3 – Log Observability

1. Collecting logs with Filebeat and Elastic Agent
2. Log ingestion pipelines
3. Parsing logs with Ingest Node
4. Searching and filtering logs
5. Building log dashboards
6. Log retention, lifecycle management (ILM)

Module 4 – Metrics Observability

1. Collecting host and service metrics
2. System metrics (CPU, Memory, Disk, Network)
3. Kubernetes and container metrics
4. Database and cloud metrics
5. Creating metrics dashboards
6. Using machine learning for anomaly detection

Module 5 – Application Performance Monitoring (APM)

1. Installing APM Server
2. Instrumenting applications (Java, .NET, Node.js, Python, Go)
3. Transaction tracing
4. Error tracking
5. Performance bottleneck analysis
6. Distributed tracing across microservices

Module 6 – Distributed Tracing Deep Dive

1. Trace lifecycle
2. Spans, context propagation
3. Correlating logs, metrics, and traces
4. Root cause analysis techniques

Module 7 – Uptime & Synthetic Monitoring

1. Monitoring service availability
2. Browser tests and API checks
3. Alerts for downtime
4. Configuring synthetic monitors via Elastic Synthetics

Module 8 – Dashboards, Visualization & Analytics

1. Building dashboards in Kibana
2. Advanced visualizations
3. Lens, time series, and data discovery
4. Creating Observability overview dashboards

Module 9 – Alerts & Machine Learning

1. Creating operational alerts (logs, metrics, APM)
2. Notifications (Slack, Email, Webhook)
3. ML anomaly detection
4. SLOs and SLIs inside Kibana

Module 10 – Best Practices & Enterprise Use Cases

1. Observability for Kubernetes clusters
2. Observability in microservices
3. Designing a unified observability strategy
4. Scaling Elastic Observability in production
5. Governance, cost management and data retention
6. Security considerations in Observability environments