cloud-monitoring

name	cloud-monitoring
description	Monitor cloud infrastructure and applications using metrics, logs, and traces to provide real-time observability into performance, health, and reliability. Use when the user requests cloud monitoring or provides relevant inputs for this workflow.
license	MIT
metadata	{"author":"awesome-ai-agent-skills","version":"1.0.0"}

Cloud Monitoring

This skill enables the agent to design and configure comprehensive monitoring and observability solutions for cloud infrastructure and applications. The agent understands the three pillars of observability — metrics, logs, and traces — and can set up dashboards, alerting rules, SLIs, SLOs, and SLAs using tools like Prometheus, Grafana, CloudWatch, Datadog, and OpenTelemetry. The agent also applies alerting best practices to minimize alert fatigue while ensuring critical issues are surfaced promptly.

Workflow

1. Identify Monitoring Objectives: The agent works with the user to define what needs to be monitored and why. This includes identifying critical services, establishing Service Level Indicators (SLIs) such as request latency, error rate, and throughput, and setting Service Level Objectives (SLOs) that define acceptable performance thresholds. SLAs (Service Level Agreements) are documented as contractual commitments to customers.

2. Select Monitoring Tools and Instrumentation: Based on the cloud provider and application architecture, the agent recommends an appropriate monitoring stack. This may include Prometheus for metrics collection, Grafana for visualization, Loki or CloudWatch Logs for log aggregation, and Jaeger or AWS X-Ray for distributed tracing. The agent configures OpenTelemetry SDKs in application code to emit standardized telemetry data.