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MonumentalSystems
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monitoring-observability

Establish monitoring and observability across metrics, logs, and traces.

17|5|Updated Feb 6, 2026
Search Tags:#monitoring#logging#observability#grafana#prometheus#alerting#cloudwatch
One-click install
npx skills add https://github.com/MonumentalSystems/Atlas-Agent-Teams --skill monitoring-observability-monumentalsystems
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: monitoring-observability
Source: https://github.com/MonumentalSystems/Atlas-Agent-Teams/tree/main/teams/devops-cloud/skills/monitoring-observability
Command: npx skills add https://github.com/MonumentalSystems/Atlas-Agent-Teams --skill monitoring-observability-monumentalsystems

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you reduce outages and diagnose performance problems by turning raw telemetry into actionable metrics, logs, dashboards, alerts, and SLO/SLI tracking.

Core Features & Use Cases

  • Metrics monitoring with Prometheus + Grafana: Define PromQL queries, create dashboards, and configure alerting with practical alert routing to tools like Slack or PagerDuty.
  • Cloud-native observability with CloudWatch, Azure Monitor, and Stackdriver: Collect metrics and logs, design service dashboards, and set alarms using each platform’s native constructs.
  • Logging, alerting, and incident response guidance: Implement centralized logging patterns (ELK/Loki), design alert strategies to reduce noise, and run incidents with clear lifecycle steps and runbooks.
  • SLO/SLI and error budget workflows: Model reliability targets, compute SLI/SLO outcomes, and use error budgets to drive engineering decisions.

Example use case: you run a microservices platform and need dashboards plus alerts for latency and error-rate regressions across clusters, with SLO tracking and incident-ready runbooks.

Quick Start

Configure Prometheus scrape targets and Grafana dashboards for your services, then create alert rules for high error rate and p95 latency.

Frequently Asked Questions about monitoring-observability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up Prometheus and Grafana dashboards for microservices monitoring?▼

Microservices monitoring with Prometheus and Grafana requires configuring scrape targets, formulating PromQL queries, and building dashboards for latency and error-rate metrics. You then create alert rules with routing to tools like Slack or PagerDuty to catch regressions across clusters.

What is an SLO error budget and how do I track SLIs for service reliability?▼

An SLO error budget represents the allowable unreliability of a service based on targeted SLIs. You track service reliability by modeling reliability targets, computing SLI/SLO outcomes from metrics, and using the remaining error budget to drive engineering decisions and prioritization.

Can I use CloudWatch, Azure Monitor, and Stackdriver for multi-cloud observability?▼

Yes, multi-cloud observability is supported using CloudWatch for AWS, Azure Monitor for Azure, and Stackdriver for GCP. You collect native metrics and logs, design service dashboards, and set alarms using each platform's specific constructs to maintain visibility across different cloud providers.

How do I reduce alert fatigue and design effective incident response runbooks?▼

Reducing alert fatigue requires designing alert strategies that minimize noise by routing and grouping alerts effectively. Incident response is managed through clear lifecycle steps and runbooks, ensuring that triggered alerts via Slack or PagerDuty map to actionable resolution procedures.

What is the best way to aggregate logs for observability using ELK or Loki?▼

Log aggregation for observability is best achieved by implementing centralized logging patterns using tools like ELK or Loki. This approach consolidates logs from distributed services, enabling you to query and correlate log data alongside metrics and traces to diagnose performance issues.

Does Kubernetes monitoring require special Prometheus scrape configurations?▼

Kubernetes monitoring using Prometheus requires configuring scrape targets to collect cluster metrics effectively. You formulate PromQL queries to extract resource utilization and performance data, then visualize it in Grafana dashboards to detect service degradation across multi-cluster deployments.

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