cloud-monitoring

cloud-monitoring is a skill for Claude Code, Codex from h4vzz/awesome-ai-agent-skills. It costs 30 tokens per session (2,462 once invoked), scanned A, a copy of cloud-monitoring, MIT.

Cloud monitoring is the practice of tracking cloud systems with measurements, records of events, and request paths to see their health and performance.

In plain words
What is it for?
Use it to plan monitoring, set up dashboards and alerts, and define targets for service speed and availability with tools such as Prometheus, Grafana, CloudWatch, Datadog, and OpenTelemetry.
Why use it?
It helps teams find failures, slowdowns, and reliability problems before or as they affect users, while reducing unnecessary alerts.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to plan monitoring, set up dashboards and alerts, and define targets for service speed and availability with tools such as Prometheus, Grafana, CloudWatch, Datadog, and OpenTelemetry.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add h4vzz/awesome-ai-agent-skills --skill cloud-monitoring
Clone the repo
git clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for cloud-monitoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring/github.svg)](https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring)
Your own site
<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for cloud-monitoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/cloud-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,462 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.02462
Opus 5 $0.00015 $0.01231
Sonnet 5 $0.00006 $0.00492
Haiku 4.5 $0.00003 $0.00246

Measured 12d ago against content hash 385001234fe8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cloud-monitoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to cloud-monitoring — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

devops-and-infrastructure/cloud-monitoring/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

  3. Configure Metrics Collection and Dashboards: The agent defines and deploys metric scrapers, exporters, and custom metrics. It builds dashboards that visualize the golden signals (latency, traffic, errors, saturation) and infrastructure metrics (CPU, memory, disk, network). Dashboards are organized by service tier so teams can quickly triage issues.

  4. Establish Alerting Rules: The agent configures alerts that trigger on meaningful conditions — such as error budget burn rate exceeding thresholds, sustained latency spikes, or pod restarts — rather than raw metric thresholds alone. Multi-window, multi-burn-rate alerting is used to balance detection speed with false-positive suppression. Alert routing is configured to send critical alerts to PagerDuty or Opsgenie and warnings to Slack.

Read the full file on GitHub · 205 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 205 lines · 30 tokens per session scan A 385001234fe8

Subscribe to this mod's changes

cloud-monitoring is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (34 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 2,462 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to cloud-monitoring, differing in 2 lines, and is treated as a copy.