Prometheus and Metric Collection in the
Cloud
Introduction to Cloud Monitoring and
Observability
Monitoring needs in cloud-native environments
Role of Prometheus and Grafana
Overview of cloud-native telemetry
Prometheus Architecture and Setup in
the Cloud
Components of Prometheus
Installing Prometheus in AWS EC2, Azure VM, or GKE/EKS
Cloud-friendly Prometheus configuration
Scraping Metrics from Cloud and
Kubernetes Resources
Node exporter and cAdvisor for cloud VMs and containers
Using exporters for AWS, Azure, GCP (e.g., CloudWatch
exporter, Azure Monitor exporter)
Discovering cloud-based targets dynamically
Metric Types and Collection Best
Practices
Prometheus metric types and formats
Labeling and job organization
Dealing with high-cardinality metrics
PromQL, Grafana Dashboards, and Alerting
in the Cloud
Querying Metrics with PromQL in Cloud
Context
Filters, aggregations, and functions
Querying for CPU, memory, latency, and availability metrics
Building queries for cloud-specific use cases
Deploying and Configuring Grafana in
the Cloud
Grafana OSS vs Grafana Cloud
Setting up Grafana with Prometheus as a data source
Integrating with AWS, Azure, or GCP data sources
Building Cloud Monitoring Dashboards in
Grafana
Panels, variables, and templates
Using pre-built dashboards for cloud services
Best practices for dashboard layout and usage
Alerting and Notifications with Cloud
Integration
Creating alert rules in Grafana
Routing alerts via Alertmanager or cloud-native tools
(e.g., SNS, Azure Alerts)
Integrating with Slack, Teams, PagerDuty, etc.
Hands-on Exercises
Summary and Conclusion
