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Aws Cloud Monitoring

Community
automateyournetwork
aws-cloud-monitoring

AWS CloudWatch monitoring — metrics, alarms, log queries, VPC flow log analysis, network performance. Use when checking AWS alarms, analyzing VPC flow logs, investigating network latency, or monitoring VPN and NAT Gateway metrics.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill nameaws-cloud-monitoring
Stars
680
Forks
189
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by automateyournetwork on GitHub. Read the source before you install it.

Installation

Install the Aws Cloud Monitoring AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/aws-cloud-monitoring
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/automateyournetwork/netclaw.git /tmp/netclaw
mkdir -p .claude/skills
cp -r /tmp/netclaw/workspace/skills/aws-cloud-monitoring .claude/skills/aws-cloud-monitoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Cloud Monitoring in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Cloud Monitoring on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Cloud Monitoring is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS Cloud Monitoring

MCP Server

  • Command: uvx awslabs.cloudwatch-mcp-server@latest (stdio transport)
  • Requires: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION (or AWS_PROFILE)

Key Capabilities

  • Metrics: Query CloudWatch metrics for any AWS service (EC2, ELB, TGW, NAT GW, VPN)
  • Alarms: List and inspect CloudWatch alarms and their states
  • Logs: Run CloudWatch Logs Insights queries across any log group
  • Flow Logs: Analyze VPC and TGW flow logs for traffic patterns and dropped connections

Workflow: Network Monitoring Dashboard

When a user asks "how is our AWS network performing?":

  1. Check alarms: List CloudWatch alarms in ALARM state
  2. VPN metrics: Tunnel state, bytes in/out for site-to-site VPNs
  3. NAT Gateway metrics: Active connections, packets dropped, bytes processed
  4. Transit Gateway metrics: Bytes in/out, packets dropped per attachment
  5. ELB metrics: Healthy/unhealthy targets, latency, 5xx errors
  6. Report: Network health dashboard with any issues flagged

Workflow: Flow Log Analysis

When investigating traffic patterns or security events:

  1. Query VPC flow logs: Filter by source IP, destination IP, port, action (ACCEPT/REJECT)
  2. Identify rejected traffic: Find REJECT entries to see blocked connections
  3. Top talkers: Aggregate by source/destination to find heaviest traffic flows
  4. Time correlation: Narrow to specific time windows around incidents
  5. Report: Traffic analysis with recommendations

Common CloudWatch Network Metrics

ServiceMetricWhat It Tells You
VPNTunnelState0=down, 1=up for each tunnel
VPNTunnelDataIn/OutBytes through each VPN tunnel
NAT GWActiveConnectionCountActive NAT connections
NAT GWPacketsDropCountPackets dropped (capacity issue)
NAT GWBytesProcessedTraffic volume through NAT
TGWBytesIn/BytesOutTraffic per TGW attachment
TGWPacketDropCountBlackholeBlackhole route drops
ELBHealthyHostCountHealthy targets behind ALB/NLB
ELBTargetResponseTimeBackend latency
EC2NetworkIn/NetworkOutInstance network throughput
EC2NetworkPacketsIn/OutInstance packet rate

Flow Log Query Examples

# Top rejected connections in last hour
fields @timestamp, srcAddr, dstAddr, dstPort, action
| filter action = "REJECT"
| stats count() as rejections by srcAddr, dstAddr, dstPort
| sort rejections desc
| limit 20

# Traffic from specific source
fields @timestamp, srcAddr, dstAddr, dstPort, bytes, action
| filter srcAddr = "10.0.1.50"
| sort @timestamp desc

# Top talkers by bytes
fields srcAddr, dstAddr, bytes
| stats sum(bytes) as totalBytes by srcAddr, dstAddr
| sort totalBytes desc
| limit 10

Important Rules

  • CloudWatch Logs Insights queries have a cost — be mindful of time range and data volume
  • Region-specific — metrics and logs are scoped to the configured region
  • Record in GAIT — log monitoring investigations for audit trail

Environment Variables

  • AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION (or AWS_PROFILE)

Failure Behavior

  • On a tool error (timeout, unreachable host, malformed response), report the failure and its error message directly to the user rather than fabricating or guessing at results.
  • For a confirmed read-only call, check connectivity and retry once if appropriate. For any call that changes state or sends a message, a timeout does not prove the action failed: inspect current state or delivery status before retrying, preserve the required approval/change gates, and do not repeat an action whose outcome is unknown.

Frequently asked questions

What does the Aws Cloud Monitoring AI skill do?

AWS CloudWatch monitoring — metrics, alarms, log queries, VPC flow log analysis, network performance. Use when checking AWS alarms, analyzing VPC flow logs, investigating network latency, or monitoring VPN and NAT Gateway metrics.

Why use Aws Cloud Monitoring on TypingMind?

Because you install it once and use it with any model. Aws Cloud Monitoring is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Cloud Monitoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/aws-cloud-monitoring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aws Cloud Monitoring?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Cloud Monitoring?

As many as you like. As long as a model supports skills, you can use Aws Cloud Monitoring with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Cloud Monitoring AI skill free?

Yes. It is published on GitHub by automateyournetwork under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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