monitoring-observability

To set up monitoring for a microservice, configure Prometheus to scrape metrics from your application endpoints and use Grafana to visualize the data. This Skill provides example PromQL queries and dashboard design principles to track system health effectively from day one.

The core pillars of observability are metrics, logs, and distributed traces. Implementing these pillars allows you to define SLOs and SLIs, enabling proactive system health management, faster incident response, and comprehensive performance optimization across cloud environments.

The best way to manage log aggregation and alerting is by using tools like ELK or Loki for centralized logs. This Skill outlines strategies for effective alerting and incident response to ensure you can quickly identify and resolve system reliability issues.

Yes, it provides detailed setup and best practices for cloud-native monitoring across major platforms. You get comprehensive guidance on using AWS CloudWatch, Azure Monitor, and Google Cloud's Stackdriver to manage system performance and reliability.

Defining SLOs and SLIs involves establishing clear metrics for service level objectives and indicators based on your system's performance data. This Skill provides guidance on integrating these definitions with your observability strategy to maintain reliable cloud operations.

You need distributed tracing when managing complex microservice architectures to track requests across multiple services. This Skill addresses how to implement tracing alongside metrics and logs to achieve full observability and optimize system performance.