Imported from flight505/skill-forge (plugins/saas-packs/apify-pack/skills/apify-prod-checklist/SKILL.md). Install upstream with npx skills add flight505/skill-forge --skill apify-prod-checklist. Copyright stays with the author (MIT).

Apify Production Checklist

Overview

Complete checklist for deploying Actors to the Apify platform and integrating them into production applications. Covers Actor configuration, scheduling, monitoring, alerting, and rollback.

Prerequisites

• Actor tested locally with apify run
• apify login configured with production token
• Familiarity with apify-core-workflow-a and apify-deploy-integration

Pre-Deployment Checklist

Actor Configuration

• .actor/actor.json has correct name, title, description
• INPUT_SCHEMA.json validates all required inputs
• Dockerfile uses pinned base image version (apify/actor-node:20, not latest)
• package-lock.json committed (deterministic installs)
• Memory set appropriately (start at 1024MB, tune after profiling)
• Timeout set with buffer (2x expected runtime)

Code Quality

• Actor.main() wraps entry point (handles init/exit/errors)
• failedRequestHandler logs failures without crashing Actor
• Input validation at Actor start (if (!input?.startUrls) throw ...)
• No hardcoded URLs, credentials, or magic numbers
• Proxy configured for target sites that block datacenter IPs
• maxRequestsPerCrawl set to prevent runaway costs

Data Output

• Dataset schema documented (consistent field names)
• SUMMARY key-value store record saved with run stats
• Large payloads chunked (9MB dataset push limit)
• PII sanitized before storage

Instructions

Step 1: Deploy Actor

# Build and push to Apify platform
apify push

# Verify the build succeeded
apify builds ls

# Test on platform with production-like input
apify actors call username/my-actor \
  --input='{"startUrls":[{"url":"https://target.com"}],"maxItems":10}'

Step 2: Configure Scheduling

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

// Create a scheduled task (cron)
const schedule = await client.schedules().create({
  name: 'daily-product-scrape',
  cronExpression: '0 6 * * *',  // Daily at 6 AM UTC
  isEnabled: true,
  actions: [{
    type: 'RUN_ACTOR',
    actorId: 'username/my-actor',
    runInput: {
      body: JSON.stringify({
        startUrls: [{ url: 'https://target.com/products' }],
        maxItems: 5000,
      }),
      contentType: 'application/json',
    },
    runOptions: {
      memory: 2048,
      timeout: 3600,
      build: 'latest',
    },
  }],
});

console.log(`Schedule created: ${schedule.id}`);

Or configure in Apify Console: Actors > Your Actor > Schedules.

Step 3: Set Up Webhooks for Monitoring

// Create webhook for run completion alerts
const webhook = await client.webhooks().create({
  eventTypes: ['ACTOR.RUN.SUCCEEDED', 'ACTOR.RUN.FAILED', 'ACTOR.RUN.TIMED_OUT'],
  condition: { actorId: 'ACTOR_ID' },
  requestUrl: 'https://your-server.com/api/apify-webhook',
  payloadTemplate: JSON.stringify({
    eventType: '{{eventType}}',
    actorId: '{{actorId}}',
    runId: '{{actorRunId}}',
    status: '{{resource.status}}',
    datasetId: '{{resource.defaultDatasetId}}',
    startedAt: '{{resource.startedAt}}',
    finishedAt: '{{resource.finishedAt}}',
  }),
});

Step 4: Monitor Runs

// Check recent runs for failures
async function checkActorHealth(actorId: string, lookbackHours = 24) {
  const { items: runs } = await client.actor(actorId).runs().list({
    limit: 50,
    desc: true,
  });

  const cutoff = new Date(Date.now() - lookbackHours * 3600_000);
  const recentRuns = runs.filter(r => new Date(r.startedAt) > cutoff);

  const stats = {
    total: recentRuns.length,
    succeeded: recentRuns.filter(r => r.status === 'SUCCEEDED').length,
    failed: recentRuns.filter(r => r.status === 'FAILED').length,
    timedOut: recentRuns.filter(r => r.status === 'TIMED-OUT').length,
    totalCostUsd: recentRuns.reduce((sum, r) => sum + (r.usageTotalUsd ?? 0), 0),
  };

  const successRate = stats.total > 0
    ? ((stats.succeeded / stats.total) * 100).toFixed(1)
    : 'N/A';

  console.log(`Actor: ${actorId}`);
  console.log(`Last ${lookbackHours}h: ${stats.total} runs, ${successRate}% success`);
  console.log(`Failed: ${stats.failed}, Timed out: ${stats.timedOut}`);
  console.log(`Total cost: $${stats.totalCostUsd.toFixed(4)}`);

  if (stats.failed > 0) {
    console.warn('ALERT: Failed runs detected!');
  }

  return stats;
}

Step 5: Implement Rollback

# List available builds
apify builds ls

# Roll back to a previous build
curl -X POST \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/acts/ACTOR_ID?build=BUILD_NUMBER"

# Or redeploy from a git tag
git checkout v1.2.3
apify push

Step 6: Cost Guard

// Set up a cost guard that aborts runs exceeding budget
async function runWithCostGuard(
  actorId: string,
  input: Record<string, unknown>,
  maxCostUsd: number,
) {
  const run = await client.actor(actorId).start(input);

  // Poll every 30 seconds
  const pollInterval = setInterval(async () => {
    const status = await client.run(run.id).get();
    const cost = status.usageTotalUsd ?? 0;

    if (cost > maxCostUsd) {
      console.error(`Cost guard: $${cost.toFixed(4)} exceeds $${maxCostUsd}. Aborting.`);
      await client.run(run.id).abort();
      clearInterval(pollInterval);
    }
  }, 30_000);

  const finished = await client.run(run.id).waitForFinish();
  clearInterval(pollInterval);
  return finished;
}

Production Alert Conditions

Error Handling

Resources

• Actor Deployment Guide
• Schedules Documentation
• Webhook Event Types
• Usage & Billing

Next Steps

For version upgrades, see apify-upgrade-migration.