Apify Debug Bundle

Overview

Collect all diagnostic information needed to troubleshoot failed Actor runs and prepare Apify support tickets. Pulls run metadata, logs, dataset samples, and environment info into a single bundle.

Prerequisites

• apify-client installed
• APIFY_TOKEN configured
• A failed or problematic run ID to investigate

Instructions

Step 1: Investigate a Failed Run

import { ApifyClient } from 'apify-client';

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

async function investigateRun(runId: string) {
  // Get run details
  const run = await client.run(runId).get();
  console.log('=== Run Summary ===');
  console.log(`Status:       ${run.status}`);
  console.log(`Message:      ${run.statusMessage}`);
  console.log(`Started:      ${run.startedAt}`);
  console.log(`Finished:     ${run.finishedAt}`);
  console.log(`Memory MB:    ${run.options?.memoryMbytes}`);
  console.log(`Timeout sec:  ${run.options?.timeoutSecs}`);
  console.log(`Build:        ${run.buildNumber}`);
  console.log(`Origin:       ${run.meta?.origin}`);
  console.log(`CU used:      ${run.usage?.ACTOR_COMPUTE_UNITS?.toFixed(4)}`);
  console.log(`Cost USD:     $${run.usageTotalUsd?.toFixed(4)}`);

  // Get dataset stats
  if (run.defaultDatasetId) {
    const ds = await client.dataset(run.defaultDatasetId).get();
    console.log(`\nDataset items: ${ds.itemCount}`);
  }

  // Get run log (last 5000 chars)
  const log = await client.run(runId).log().get();
  console.log('\n=== Last 2000 chars of log ===');
  console.log(log?.slice(-2000));

  return { run, log };
}

Step 2: Create Debug Bundle Script

#!/bin/bash
# apify-debug-bundle.sh <RUN_ID>

RUN_ID="${1:?Usage: apify-debug-bundle.sh <RUN_ID>}"
BUNDLE_DIR="apify-debug-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$BUNDLE_DIR"

echo "Collecting debug info for run $RUN_ID..."

# Environment info
{
  echo "=== Environment ==="
  echo "Date: $(date -u)"
  echo "Node: $(node --version 2>/dev/null || echo 'not found')"
  echo "npm:  $(npm --version 2>/dev/null || echo 'not found')"
  echo ""
  echo "=== Apify Packages ==="
  npm list apify-client apify crawlee 2>/dev/null || echo "No packages found"
  echo ""
  echo "=== Apify CLI ==="
  apify --version 2>/dev/null || echo "CLI not installed"
} > "$BUNDLE_DIR/environment.txt"

# Run details via API
curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/actor-runs/$RUN_ID" | \
  jq '.data | {id, actId, status, statusMessage, startedAt, finishedAt,
    options: {memoryMbytes: .options.memoryMbytes, timeoutSecs: .options.timeoutSecs},
    stats: .stats, usage: .usage, usageTotalUsd}' \
  > "$BUNDLE_DIR/run-details.json" 2>/dev/null

# Run log (secrets auto-redacted by platform)
curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/actor-runs/$RUN_ID/log" \
  > "$BUNDLE_DIR/run-log.txt" 2>/dev/null

# Dataset sample (first 5 items)
DATASET_ID=$(jq -r '.defaultDatasetId // empty' "$BUNDLE_DIR/run-details.json" 2>/dev/null)
if [ -n "$DATASET_ID" ]; then
  curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
    "https://api.apify.com/v2/datasets/$DATASET_ID/items?limit=5" \
    > "$BUNDLE_DIR/dataset-sample.json" 2>/dev/null
fi

# Key-value store keys
KV_ID=$(jq -r '.defaultKeyValueStoreId // empty' "$BUNDLE_DIR/run-details.json" 2>/dev/null)
if [ -n "$KV_ID" ]; then
  curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
    "https://api.apify.com/v2/key-value-stores/$KV_ID/keys" \
    > "$BUNDLE_DIR/kv-store-keys.json" 2>/dev/null
fi

# Local config (redacted)
if [ -f .env ]; then
  sed 's/=.*/=***REDACTED***/' .env > "$BUNDLE_DIR/env-redacted.txt"
fi

# Platform health
curl -sf https://api.apify.com/v2/health > "$BUNDLE_DIR/platform-health.json" 2>/dev/null

# Package it up
tar -czf "$BUNDLE_DIR.tar.gz" "$BUNDLE_DIR"
rm -rf "$BUNDLE_DIR"
echo "Bundle created: $BUNDLE_DIR.tar.gz"
echo ""
echo "Attach this file to your Apify support ticket."

Step 3: Compare Successful vs Failed Runs

async function compareRuns(successId: string, failId: string) {
  const success = await client.run(successId).get();
  const fail = await client.run(failId).get();

  console.log('=== Run Comparison ===');
  const fields = [
    'status', 'buildNumber', 'options.memoryMbytes',
    'options.timeoutSecs', 'stats.requestsFinished',
    'stats.requestsFailed', 'stats.runTimeSecs',
  ] as const;

  console.log(`${'Field'.padEnd(25)} | ${'Success'.padEnd(15)} | Failed`);
  console.log('-'.repeat(60));

  const get = (obj: any, path: string) =>
    path.split('.').reduce((o, k) => o?.[k], obj);

  for (const field of fields) {
    const sVal = get(success, field) ?? 'N/A';
    const fVal = get(fail, field) ?? 'N/A';
    const marker = sVal !== fVal ? ' <--' : '';
    console.log(`${field.padEnd(25)} | ${String(sVal).padEnd(15)} | ${fVal}${marker}`);
  }
}

Step 4: Live Tail Actor Logs

# Stream logs from a running Actor
RUN_ID="your-run-id"
while true; do
  curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
    "https://api.apify.com/v2/actor-runs/$RUN_ID/log?stream=1" 2>/dev/null
  sleep 2
done

Sensitive Data Handling

Always redact before sharing:

• API tokens (apify_api_*)
• Proxy passwords
• PII (emails, names, IPs)
• Custom environment variables

Safe to include:

• Run IDs, Actor IDs, dataset IDs
• Error messages and stack traces
• Run configuration (memory, timeout)
• Platform health status

Escalation Path

1. Check run log for stack trace
2. Compare with a successful run
3. Check Apify Status for outages
4. Create debug bundle
5. Submit to Apify Support with bundle attached

Error Handling

Issue	Cause	Solution
Run not found	Invalid run ID or expired	Unnamed runs expire after 7 days
Log unavailable	Run still in progress	Wait for completion or stream live
Empty dataset	Actor produced no output	Check failedRequestHandler in code
High CU usage	Memory too high or slow execution	Reduce memory, optimize code

Resources

• Actor Run API
• Run Log API
• Apify Support Portal

Next Steps

For rate limit issues, see apify-rate-limits.