Visão Geral

Este Curso Datadog Metrics Essentials, apresenta os fundamentos essenciais do monitoramento baseado em métricas utilizando a plataforma Datadog. O participante aprenderá como coletar, visualizar, analisar e correlacionar métricas de infraestrutura, aplicações, containers e serviços cloud. O curso aborda desde conceitos básicos de métricas até configurações avançadas de dashboards e alertas inteligentes, garantindo ao aluno domínio prático para ambientes reais.

Objetivo

Após realizar este Curso Datadog Metrics Essentials, você será capaz de:

• Entender os tipos de métricas e como utilizá-las
• Instalar e configurar o Datadog Agent para coleta de métricas
• Visualizar e analisar métricas no Datadog
• Criar dashboards com métricas de infraestrutura e aplicações
• Configurar alertas eficientes usando métricas
• Enviar métricas customizadas para o Datadog
• Identificar anomalias e acompanhar performance de serviços

Publico Alvo

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• Engenheiros DevOps
• SREs
• Administradores de Sistemas
• Desenvolvedores
• Analistas de Observabilidade e Performance
• Profissionais que utilizam Datadog para monitoramento contínuo
•  

Pre-Requisitos

•  
• Noções básicas de Linux
• Noções de infraestrutura ou cloud computing
• Conhecimento básico de métricas (desejável)
•  

Materiais

Conteúdo Programatico

1. Introduction to Metrics and Observability

1. What are metrics and how they work
2. Types of metrics: gauge, count, rate, histogram
3. Why metrics matter for observability
4. Datadog Metrics architecture
5. Key concepts: tags, aggregation, scopes, host maps

2. Installing and Configuring Metrics Collection

1. Installing the Datadog Agent
2. Enabling system metrics collection
3. Metric collection from Docker and Kubernetes
4. Metric collection via cloud integrations (AWS, Azure, GCP)
5. Understanding metric sources and namespaces
6. Best practices for metric ingestion

3. Working with Metrics in Datadog

1. Exploring metrics in the Metrics Explorer
2. Using tags and filtering metrics
3. Analyzing timeseries data
4. Understanding metric granularity and retention
5. Creating metric queries
6. Metric correlation with logs and traces

4. Custom Metrics

1. What are custom metrics
2. Sending custom metrics using DogStatsD
3. Sending custom metrics via API
4. Naming conventions and tagging strategy
5. Monitoring the usage and cost of custom metrics

5. Dashboards for Metrics Visualization

1. Creating dashboards from scratch
2. Using widgets: timeseries, query values, heatmaps, toplists
3. Using template variables
4. Designing dashboards for teams
5. Best practices for effective metric dashboards

6. Metric Alerts and Monitors

1. Creating monitors using metrics
2. Threshold, anomaly, outlier, and forecast monitors
3. Multi-alert and multi-scope monitors
4. Reducing alert fatigue with smart alerting
5. Notification channels and integrations
6. Using metrics in SLOs (Service Level Objectives)

7. Advanced Metrics Concepts

1. High cardinality challenges
2. Metric aggregation and roll-ups
3. Understanding Datadog’s pricing model for metrics
4. Optimizing metric usage and cost
5. Tagging standards for large environments

8. Hands-On Labs

1. Configure Agent to collect metrics from multiple sources
2. Build dashboards with real infrastructure metrics
3. Create metric-based monitors
4. Send custom metrics using DogStatsD
5. Troubleshoot performance issues using metrics