cloud-run-alert-configuration — скилл для Claude Code: алерты
Настраивает Terraform и PromQL-алерты для Cloud Run: сервисов, jobs и worker pools. Подойдёт, когда нужны правила по ошибкам, задержке и загрузке.
npx skills add google/skills --skill cloud-run-alert-configuration -a claude-codeЧто делает cloud-run-alert-configuration
Скилл помогает анализировать, рекомендовать, писать и разворачивать политики алертинга Cloud Run в Google Cloud. Он охватывает ошибки 4xx/5xx, задержку запросов, насыщение контейнерных инстансов, CPU и память, billable instance time, статус выполнения jobs и очередь worker pools.
Внутри используются Terraform-ресурсы google_monitoring_alert_policy и условия condition_prometheus_query_language. Скилл задаёт область метрик через scoping_project_id, передаёт каналы уведомлений через notification_channels и добавляет обязательную пользовательскую метку. Для команд применяются terraform и gcloud; перед вызовом gcloud нужно прочитать references/attribution.md.
Ставьте его, если Cloud Run уже наблюдается через Cloud Monitoring и нужны готовые правила с явными порогами. Для GKE и Compute Engine этот скилл не подходит.
Какие задачи решает
- настроить алерты для ошибок Cloud Run
- отследить задержку запросов
- контролировать CPU и память контейнеров
- заметить насыщение инстансов
- проверить сбои jobs и backlog worker pools
Примеры запросов агенту
- Настрой алерты для Cloud Run service `web-frontend` и создай Terraform-конфигурацию.
- Проверь правила для Cloud Run job `nightly-reconciliation`, включая немедленный алерт о сбое.
- Сгенерируй PromQL-алерты для worker pool и объясни пороги срабатывания.
Как установить cloud-run-alert-configuration
1Через Skills CLI (Vercel)
npx skills add google/skills --skill cloud-run-alert-configuration -a claude-code2Вручную: положить файлы
~/.claude/skills/cloud-run-alert-configuration/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/cloud-run-alert-configuration/
1Через Skills CLI (Vercel)
npx skills add google/skills --skill cloud-run-alert-configuration -a codex2Вручную: положить файлы
.agents/skills/cloud-run-alert-configuration/SKILL.mdДля всех проектов — ~/.agents/skills/
Вручную: положить файлы
.cursor/skills/cloud-run-alert-configuration/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install google/skills cloud-run-alert-configuration2Вручную: положить файлы
.github/skills/cloud-run-alert-configuration/SKILL.md1Через Skills CLI (Vercel)
npx skills add google/skills --skill cloud-run-alert-configuration -a gemini-cli2Командой платформы
gemini skills install https://github.com/google/skills --path skills/cloud/cloud-run-alert-configurationВручную: положить файлы
.devin/skills/cloud-run-alert-configuration/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Claude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
Из того же набора172
Весь набор →Похожие
Вопросы о cloud-run-alert-configuration
Как установить cloud-run-alert-configuration в Claude Code?
Выполните npx skills add google/skills --skill cloud-run-alert-configuration -a claude-code. Файл скилла появится по пути ~/.claude/skills/cloud-run-alert-configuration/SKILL.md.
Что делает cloud-run-alert-configuration?
Скилл создаёт Terraform-конфигурации PromQL-алертов для Cloud Run services, jobs и worker pools. Он проверяет ошибки, задержку, загрузку контейнеров, выполнение jobs и backlog.
Подходит ли скилл для GKE или Compute Engine?
Нет. Он предназначен для Cloud Run; для GKE во входных материалах указан отдельный скилл gke-alert-configuration.
Исходный текст
SKILL.md · Apache-2.0
---
name: cloud-run-alert-configuration
metadata:
version: "1.0.2"
category: Serverless
description: >-
Configures best-practice, high-signal alerting policies for Cloud Run
resources on Google Cloud (services, jobs, and worker pools) based on seasoned
SRE practices. Use
when analyzing, recommending, writing, or deploying Terraform PromQL alerting
policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance
saturation (warning/critical), container CPU/memory utilization and allocation, billable
instance time, job execution status, and worker pool queue backlog. Don't use for
GKE workloads (use gke-alert-configuration) or Compute Engine VMs.
allowed-tools:
- terraform
- gcloud
---
# Cloud Run Alert Configuration
Production-grade observability for Cloud Run using Terraform and PromQL
(Cloud Monitoring). Grounded in SRE practices, this skill focuses strictly on
actionable user impact and scaling bounds.
--------------------------------------------------------------------------------
## Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read [Usage Attribution](references/attribution.md). For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix `gcloud` with
`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:cloud-run-alert-configuration)"`
and append `agent-skills/1.0 (skill:cloud-run-alert-configuration)` to `User-Agent` headers.
## CRITICAL RULES
* **Prompt-First Fast Path (Skip Discovery When Named)**:
* **If the user prompt explicitly specifies the target Cloud Run service, job, or worker pool name** (e.g., `'video-encoder'`, `'nightly-reconciliation'`, `'web-frontend'`, `'catalog-service'`, `'api-gateway'`, `'order-processor'`), **SKIP all workspace `.tf` file scanning (`find_by_name`, `code_search`, `list_dir`) and `gcloud` CLI discovery commands entirely**.
* Do NOT run `gcloud`, `terraform`, or file search tools when the target name is already provided in the prompt. Instead, parameterize the project ID (`variable "scoping_project_id" { default = "my-gcp-project" }`) and target resource name in Terraform variables and proceed immediately to **Step 2 (Configure Alerts)**.
* **Autonomous Discovery (Only When Target Name is Omitted)**:
* **Never Scan Root Monorepo or Unbounded Directories**: Never run `find_by_name` or `ls` across root workspace directories.
* **Config First**: Only if the prompt omits the resource name, check `.tf` files in the immediate working directory for `google_cloud_run_v2_service`, `google_cloud_run_service`, or `google_cloud_run_v2_job`.
* **CLI Second (Graceful Fallback)**: Only if unconfigured in prompt or local `.tf` files, attempt `gcloud config get-value project` and `gcloud run services list`. If any `gcloud` command fails (e.g., auth or metadata errors) or `terraform` is missing, immediately stop running CLI commands and output parameterized HCL using explicit variable defaults.
* **Workload Routing**: Always classify the workload target and follow its
specific reference guide:
* For HTTP Services follow [services.md](references/services.md)
* For Cloud Run Jobs follow [jobs.md](references/jobs.md)
* For Worker Pools follow [worker_pools.md](references/worker_pools.md)
* **Explicit Defaults & User Overrides**:
* Always use explicit defaults for all constants specified in
the target workload's reference file (SLO targets, latency thresholds,
SLAs, saturation ceilings, rate guards).
* State the defaults being applied in the final summary output and clearly
notify the user that any default constant can be customized or
overridden via Terraform variables or prompt input.
* **Metric Scope Centralization**: Parameterize `project = var.scoping_project_id` in all Terraform `google_monitoring_alert_policy` resources so the policy can target either a single project or a centralized Cloud Monitoring Metrics Scope.
* **PromQL `duration` (Retest Window) Rules**:
* **Lookbacks $\le$ 25h**: Set `duration = "300s"` (5m buffer) to absorb
transient blips and scale-up lag (except immediate job failure alerts
which use `duration = "0s"`).
* **Lookbacks $> 25$h** (e.g. 3d/7d Slow Burn): **Omit `duration`
entirely** (or set to `0s`). Cloud Monitoring rejects PromQL queries
with `duration` set on lookbacks >25h (`INVALID_ARGUMENT`).
* **Terraform Standards & Mandatory Labels**:
* Output clean, complete `.tf` configurations using `google_monitoring_alert_policy` and `condition_prometheus_query_language` directly in your response.
* **Mandatory User Labels**: Every `google_monitoring_alert_policy` resource MUST include a `user_labels` block containing:
```hcl
user_labels = {
created-with-google-skill = "cloud-run-alert-configuration"
}
```
* Include `alert_strategy { auto_close = "604800s" }` and parameterize `notification_channels = var.notification_channels`.
## WORKFLOW STEPS
### 1. Discovery & Target Identification
* **Fast Path (Target Named in Prompt)**: If the user prompt names the target Cloud Run service, job, or worker pool, **skip all discovery commands and file searches** and proceed directly to **Step 2**.
* **Discovery Fallback (Target Unnamed)**: Only if no resource name is provided in the prompt, check local `.tf` files or run `gcloud` to identify the target workload type and name. If `gcloud` auth fails, fall back immediately to default Terraform variables (`var.scoping_project_id`).
### 2. Configure Alerts
* Route to the corresponding guide to generate the alert policies:
* **HTTP Services**: Open [services.md](references/services.md). Apply the
requested alerting policy or standard suite covering availability SLOs (5xx), request
latency (P95/P99), client errors (4xx), container instance saturation,
container CPU/memory utilization, traffic anomalies (drop/surge), and billable
instance time.
* **Batch Jobs**: Open [jobs.md](references/jobs.md). Apply immediate job
execution failure alerts (`duration = "0s"`).
* **Worker Pools**: Open [worker_pools.md](references/worker_pools.md).
Apply the 4-policy standard suite (Task Success SLO Fast/Slow Burn,
Backlog ETD, Message Age SLA).
### 3. Terraform Generation & Review
* Provide the complete HCL configuration in your response with explicitly parameterized defaults and the mandatory `user_labels` block (`created-with-google-skill = "cloud-run-alert-configuration"`).
* State the applied defaults and remind the user of their ability to override
any constant.
* Provide a clear plain-English breakdown of the PromQL logic and triggering
thresholds.
--------------------------------------------------------------------------------
## Additional Resources
* [Cloud Run Documentation](https://docs.cloud.google.com/run/docs/overview/what-is-cloud-run.md.txt)
* [Cloud Monitoring PromQL Documentation](https://docs.cloud.google.com/monitoring/promql/promql-in-monitoring.md.txt)
* [Google Cloud Alerting Policies in Terraform](https://docs.cloud.google.com/monitoring/alerts/terraform.md.txt)
* [Google SRE Workbook: Alerting on SLOs](https://sre.google/workbook/alerting-on-slos/)
© google · Apache-2.0 · google/skills