🛠️ GoogleクラウドNetworkingObservability
Google Cloudのネットワークで発生する様々な問題を、通信
📺 まず動画で見る(YouTube)
▶ 【衝撃】最強のAIエージェント「Claude Code」の最新機能・使い方・プログラミングをAIで効率化する超実践術を解説! ↗
※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。
📜 元の英語説明(参考)
Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.
🇯🇵 日本人クリエイター向け解説
Google Cloudのネットワークで発生する様々な問題を、通信
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-17
- 取得日時
- 2026-05-17
- 同梱ファイル
- 8
💬 こう話しかけるだけ — サンプルプロンプト
- › google-cloud-networking-observ で、私のビジネスを分析して改善案を3つ提案して
- › google-cloud-networking-observ を使って、来週の会議用の資料を作って
- › google-cloud-networking-observ で、現状の課題を整理してアクションプランに落として
これをClaude Code に貼るだけで、このSkillが自動発動します。
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Google Cloud Networking Observability Expert
Core Directive: Results First
- Identify the Primary Source: Quickly determine if the user needs firewall logs, threat logs, Cloud NAT, VPC Flow logs, or metrics.
- Execute & Present: Perform the minimum required query to get a direct answer.
- Definitive Termination: Once you identify the requested data, regardless of the value (including 0, null, or "No traffic"), present the finding and call the finish tool in the same turn. Do NOT attempt to find "active" or "busier" resources to provide a "better" answer unless specifically instructed to troubleshoot a resource that is expected to be busy.
Log & Telemetry Overview
- Threat Logs: Specialized logs from Cloud Firewall Plus and Cloud IDS that identify malicious traffic patterns (for example, SQL injection or malware) using deep packet inspection.
- VPC Flow Logs: Capture sample IP traffic to and from network interfaces. Use for traffic analysis, volume trends, and top talkers.
- Firewall Logs: Record connection attempts matched by firewall rules. Use to identify "DENY" events or verify "ALLOW" rules.
- Cloud NAT Logs: Audit NAT translations. Use to audit traffic going through NAT gateways or troubleshoot port exhaustion.
- Networking Metrics: Aggregated time-series data for throughput, RTT (latency), and packet loss. Use for historical trends and performance monitoring.
- Connectivity Tests: Static analysis tool for path diagnostics. Use to identify firewall or routing misconfigurations between endpoints.
Procedures
0. Log Source Preference
- ALWAYS check for BigQuery linked datasets (for example,
big_query_linked_dataset,_AllLogs) before using Cloud Logging for high-volume analysis or aggregations. This is the preferred method for finding trends or top-blocking rules. - Metadata Awareness (BigQuery): Subnetworks may be configured with
EXCLUDE_ALL_METADATA, causing VM names to be NULL in VPC Flow Logs. If a query by VM name returns nothing, retry using the internal IP address (jsonPayload.connection.src_ip).
1. Tool Selection & Discovery
- MCP Servers First: Use Cloud Monitoring MCP, BigQuery MCP, or Cloud Logging MCP.
- Resource Discovery: If a user-specified resource (for example, NAT
gateway, VPN tunnel) is not found in metrics/logs:
- Use
run_shell_commandwithgcloudto list resources in the project. - Search Cloud Logging MCP for the resource name to find correct labels.
- Use
- CLI Fallback: Use
gcloudorbqonly if MCP servers are unavailable. DO NOT use gcloud monitoring; it is restricted. Immediately use the curl templates in metrics-analysis.md.
2. Schema Verification & Error Recovery
If a BigQuery query fails with an 'Unrecognized name' error or schema mismatch:
- Validate Schema: Run
bq show --schema --format=json {project_id}:{dataset_id}.{table_id}to verify field names and casing (for example,jsonPayloadversusjson_payload). 2. Dry Run: Before executing a corrected query, usebq query --use_legacy_sql=false --dry_run "{query_text}"to verify field references without incurring cost or execution time. 3. Retry: Apply identified fixes to the original query and execute.
3. Analysis Guides (Read Only When Needed)
For detailed SQL patterns, field definitions, and advanced troubleshooting, read the corresponding reference file:
- Threat Log Analysis: references/threat-analysis.md
- VPC Flow Analysis: references/vpc-flow-analysis.md
- Cloud NAT Analysis: references/cloud-nat-analysis.md
- Firewall Rule Analysis: references/firewall-analysis.md
- Networking Metrics: references/metrics-analysis.md
- Connectivity Test Analysis: references/connectivity-tests.md
Boundaries (CRITICAL)
- ALWAYS present the direct answer as soon as it is identified.
- NEVER run more than 2 exploratory queries before showing results.
- NEVER perform secondary verification (for example, don't check VPC flows after finding a firewall block) without explicit user permission.
- ALWAYS print the generated SQL for review before execution.
- ALWAYS include a link to the Flow Analyzer in the Google Cloud Console.
- NEVER query a second data source (such as, BigQuery logs) if the primary source (for example, Cloud Monitoring metrics) has already provided a conclusive answer. DO NOT compare metrics and logs to "verify" accuracy unless the user specifically asks why they differ.
- NO DISCREPANCY LOOPS: If Tool A provides a result (such as, 80,000 counts) and Tool B provides a different result (for example, 1,000 counts), DO NOT initiate a deep dive to explain the difference. Present the result from the primary tool and STOP.
- ALWAYS perform time-range calculations (such as, "12 hours ago") during the first turn to save steps.
- Conclusive Acceptance of Inactivity: Treat a result of "0", "0 traffic", "No data found", or "No records found" as a conclusive finding for the requested timeframe and resource. You MUST report this as the definitive state and terminate immediately.
- Standardized Discovery Path: For all "Top-N" or volume-based discovery tasks (for example, "highest traffic," "most hits," "top talkers"), you MUST use BigQuery aggregation on _AllLogs datasets. Manual aggregation of individual time-series points using the Monitoring API is forbidden due to step inefficiency.
- Ban on Auxiliary Scripting: Execute all data retrieval and parsing logic as direct tool calls (bq, curl, gcloud). Do NOT write or execute local shell scripts (.sh) or python files, as these introduce avoidable environment and permission errors that lead to investigation timeouts.
- Discovery Efficiency: For volume analysis (for example, "how many connections" or "top IPs by bytes"), BigQuery aggregation on VPC Flow logs (_AllLogs) is the Primary Source of Truth. If BigQuery data is available, it is conclusive. Do NOT query Monitoring API to "double check" BigQuery counts.
同梱ファイル
※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。
- 📄 SKILL.md (7,191 bytes)
- 📎 references/cloud-nat-analysis.md (2,767 bytes)
- 📎 references/connectivity-tests.md (1,411 bytes)
- 📎 references/firewall-analysis.md (3,080 bytes)
- 📎 references/mcp-usage.md (2,617 bytes)
- 📎 references/metrics-analysis.md (3,078 bytes)
- 📎 references/threat-analysis.md (5,787 bytes)
- 📎 references/vpc-flow-analysis.md (4,904 bytes)