running-smoke-tests（运行冒烟测试）

Smoke Test Runner

Overview

Execute fast, high-confidence smoke tests that validate critical application functionality after deployment or build. Smoke tests verify that the application starts, core user flows work, and key integrations respond -- without running the full test suite.

Prerequisites

• Application deployed and accessible at a known URL or running locally
• HTTP client available (curl, wget, node-fetch, or Playwright)
• List of critical endpoints and user flows to validate
• Expected response codes and content patterns for each check
• CI/CD pipeline hook for post-deployment validation

Instructions

1. Identify the critical paths that constitute a "working" application:

- Health check endpoint returns 200 with expected body. - Homepage loads and contains key UI elements. - Authentication flow succeeds with test credentials. - Primary API endpoint returns valid data. - Database connection is active and responding.

1. Create a smoke test configuration listing each check:

- URL or command to execute. - Expected HTTP status code (200, 301, etc.). - Response body pattern to match (substring or regex). - Maximum acceptable response time (e.g., 3 seconds).

1. Write the smoke test suite as a lightweight script or test file:

- Use curl for HTTP checks or Playwright for browser-based checks. - Run checks sequentially for simplicity (parallel for speed if independent). - Fail fast on the first critical failure. - Log each check result with pass/fail, response time, and status code.

1. Implement timeout guards:

- Set a global timeout of 60 seconds for the entire smoke suite. - Set per-check timeouts of 5-10 seconds. - Treat timeouts as failures, not retries.

1. Add deployment-gate integration:

- On success: proceed with deployment promotion or traffic shifting. - On failure: trigger rollback and send alert notification. - Report results to CI/CD dashboard and Slack/Teams webhook.

1. Store smoke test results as CI artifacts for audit trail.
2. Schedule periodic smoke runs (every 5 minutes in production) as synthetic monitoring.

Output

• Smoke test script (scripts/smoke-test.sh or tests/smoke.test.ts)
• Pass/fail result for each critical check with response times
• Deployment gate verdict (PASS or FAIL with reason)
• CI artifact with timestamped smoke test log
• Alert payload for failed checks (Slack webhook, PagerDuty, etc.)

Error Handling

Examples

Shell-based smoke test script:

#!/bin/bash
set -e
BASE_URL="${1:-http://localhost:3000}"  # 3000: 3 seconds in ms
PASS=0; FAIL=0

check() {
  local name="$1" url="$2" expected="$3"
  status=$(curl -s -o /dev/null -w '%{http_code}' --max-time 5 "$url")
  if [ "$status" = "$expected" ]; then
    echo "PASS: $name (HTTP $status)"
    ((PASS++))
  else
    echo "FAIL: $name (expected $expected, got $status)"
    ((FAIL++))
  fi
}

check "Health check" "$BASE_URL/health" "200"  # HTTP 200 OK
check "Homepage" "$BASE_URL/" "200"  # HTTP 200 OK
check "API status" "$BASE_URL/api/status" "200"  # HTTP 200 OK
check "Login page" "$BASE_URL/login" "200"  # HTTP 200 OK

echo "Results: $PASS passed, $FAIL failed"
[ "$FAIL" -eq 0 ] || exit 1

Playwright smoke test:

import { test, expect } from '@playwright/test';

test('homepage loads with navigation', async ({ page }) => {
  await page.goto('/', { timeout: 10000 });  # 10000: 10 seconds in ms
  await expect(page.locator('nav')).toBeVisible();
  await expect(page).toHaveTitle(/My App/);
});

test('API health endpoint responds', async ({ request }) => {
  const response = await request.get('/api/health');
  expect(response.ok()).toBeTruthy();
  expect(await response.json()).toHaveProperty('status', 'ok');
});

Resources

• Smoke testing methodology: https://martinfowler.com/bliki/SmokeTest.html
• Playwright API testing: https://playwright.dev/docs/api-testing
• curl documentation: https://curl.se/docs/manpage.html
• GitHub Actions deployment gates: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment