clay-load-scale

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Implement Clay load testing, auto-scaling, and capacity planning strategies. Use when running performance tests, configuring horizontal scaling, or planning capacity for Clay integrations. Trigger with phrases like "clay load test", "clay scale", "clay performance test", "clay capacity", "clay k6", "clay benchmark".

Install

mkdir -p .claude/skills/clay-load-scale && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5498" && unzip -o skill.zip -d .claude/skills/clay-load-scale && rm skill.zip

Installs to .claude/skills/clay-load-scale

About this skill

Clay Load & Scale

Overview

Strategies for processing 10K-100K+ leads through Clay monthly. Clay is a hosted platform -- you can't add servers. Scaling focuses on: table partitioning, webhook management, batch submission pacing, credit budgeting at scale, and multi-table architectures.

Prerequisites

  • Clay Growth or Enterprise plan
  • Understanding of Clay's credit model (Data Credits + Actions)
  • Queue infrastructure for batch processing (Redis, SQS, or BullMQ)
  • Monitoring for credit consumption

Instructions

Step 1: Capacity Planning

// src/clay/capacity-planner.ts
interface CapacityPlan {
  monthlyLeads: number;
  creditsPerLead: number;
  totalCreditsNeeded: number;
  planRequired: string;
  estimatedMonthlyCost: number;
  webhooksNeeded: number;        // Each webhook has 50K lifetime limit
  tablesRecommended: number;
}

function planCapacity(monthlyLeads: number, creditsPerLead = 6): CapacityPlan {
  const totalCredits = monthlyLeads * creditsPerLead;

  // Determine plan
  let plan: string, cost: number;
  if (totalCredits <= 2500) {
    plan = 'Launch ($185/mo)';
    cost = 185;
  } else if (totalCredits <= 6000) {
    plan = 'Growth ($495/mo)';
    cost = 495;
  } else {
    plan = `Enterprise (custom pricing for ${totalCredits} credits/mo)`;
    cost = 495 + Math.ceil((totalCredits - 6000) / 1000) * 50; // Rough estimate
  }

  // With own API keys: 0 data credits, only actions consumed
  console.log(`TIP: With own API keys, you need 0 Data Credits.`);
  console.log(`     Only ${monthlyLeads} Actions needed (Growth plan includes 40K).`);

  return {
    monthlyLeads,
    creditsPerLead,
    totalCreditsNeeded: totalCredits,
    planRequired: plan,
    estimatedMonthlyCost: cost,
    webhooksNeeded: Math.ceil(monthlyLeads / 50_000 * 12), // Annual webhooks needed
    tablesRecommended: Math.ceil(monthlyLeads / 10_000), // ~10K rows per table for manageability
  };
}

// Example
const plan = planCapacity(50_000);
console.log(plan);
// Monthly leads: 50,000
// Credits needed: 300,000 (or 0 with own API keys)
// Webhooks needed: 12/year
// Tables recommended: 5

Step 2: Implement Batch Queue Architecture

// src/clay/batch-processor.ts
import { Queue, Worker } from 'bullmq';
import Redis from 'ioredis';

const redis = new Redis(process.env.REDIS_URL!);

// Create a queue for Clay webhook submissions
const clayQueue = new Queue('clay-enrichment', { connection: redis });

interface EnrichmentJob {
  leads: Record<string, unknown>[];
  webhookUrl: string;
  batchId: string;
  priority: 'high' | 'normal' | 'low';
}

// Submit a batch for processing
async function queueBatch(
  leads: Record<string, unknown>[],
  webhookUrl: string,
  priority: 'high' | 'normal' | 'low' = 'normal',
): Promise<string> {
  const batchId = `batch-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;

  // Split into chunks of 100 for manageable processing
  const chunks = [];
  for (let i = 0; i < leads.length; i += 100) {
    chunks.push(leads.slice(i, i + 100));
  }

  for (let i = 0; i < chunks.length; i++) {
    await clayQueue.add(`${batchId}-chunk-${i}`, {
      leads: chunks[i],
      webhookUrl,
      batchId,
      priority,
    }, {
      priority: priority === 'high' ? 1 : priority === 'normal' ? 5 : 10,
      attempts: 3,
      backoff: { type: 'exponential', delay: 5000 },
    });
  }

  console.log(`Queued ${leads.length} leads in ${chunks.length} chunks (batch: ${batchId})`);
  return batchId;
}

// Worker processes queued batches
const worker = new Worker<EnrichmentJob>('clay-enrichment', async (job) => {
  const { leads, webhookUrl } = job.data;
  let sent = 0, failed = 0;

  for (const lead of leads) {
    try {
      const res = await fetch(webhookUrl, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify(lead),
      });

      if (res.status === 429) {
        const retryAfter = parseInt(res.headers.get('Retry-After') || '60');
        console.log(`Rate limited. Waiting ${retryAfter}s...`);
        await new Promise(r => setTimeout(r, retryAfter * 1000));
        // Retry this lead
        const retry = await fetch(webhookUrl, {
          method: 'POST',
          headers: { 'Content-Type': 'application/json' },
          body: JSON.stringify(lead),
        });
        if (retry.ok) sent++; else failed++;
      } else if (res.ok) {
        sent++;
      } else {
        failed++;
      }
    } catch {
      failed++;
    }

    // Pace submissions: 200ms between rows
    await new Promise(r => setTimeout(r, 200));
  }

  return { sent, failed, total: leads.length };
}, { connection: redis, concurrency: 1 });

Step 3: Multi-Table Strategy

For large volumes, split data across multiple Clay tables:

# Large-volume table strategy
tables:
  outbound-leads-tech:
    focus: "Technology companies"
    filter: "industry IN ('Software', 'SaaS', 'Technology')"
    enrichment: Full waterfall + Claygent
    volume: ~5K rows/month

  outbound-leads-finance:
    focus: "Financial services companies"
    filter: "industry IN ('Financial Services', 'Banking', 'Insurance')"
    enrichment: Full waterfall (no Claygent — regulated data)
    volume: ~3K rows/month

  inbound-leads:
    focus: "Website form submissions"
    source: Webhook from web forms
    enrichment: Company lookup + email verification only
    volume: ~2K rows/month
    auto_delete: true  # Stream-through: enrich, push to CRM, delete

  event-attendees:
    focus: "Conference/webinar registrants"
    source: CSV import
    enrichment: Full waterfall + AI personalization
    volume: ~1K rows/month (batch after events)

Step 4: Webhook Rotation for High Volume

// src/clay/webhook-rotation.ts
class WebhookRotator {
  private webhooks: { url: string; count: number; maxCount: number }[];
  private currentIndex = 0;

  constructor(webhookUrls: string[], maxPerWebhook = 45_000) {
    this.webhooks = webhookUrls.map(url => ({
      url,
      count: 0,
      maxCount: maxPerWebhook, // Leave 5K buffer under 50K limit
    }));
  }

  getNextWebhook(): string {
    // Find a webhook with remaining capacity
    for (let i = 0; i < this.webhooks.length; i++) {
      const idx = (this.currentIndex + i) % this.webhooks.length;
      if (this.webhooks[idx].count < this.webhooks[idx].maxCount) {
        this.currentIndex = idx;
        return this.webhooks[idx].url;
      }
    }
    throw new Error('All webhooks exhausted! Create new webhooks in Clay.');
  }

  recordSubmission() {
    this.webhooks[this.currentIndex].count++;
  }

  getStatus() {
    return this.webhooks.map((w, i) => ({
      index: i,
      remaining: w.maxCount - w.count,
      percentUsed: ((w.count / w.maxCount) * 100).toFixed(1),
    }));
  }
}

// Usage: rotate across multiple webhooks for the same table
const rotator = new WebhookRotator([
  process.env.CLAY_WEBHOOK_URL_1!,
  process.env.CLAY_WEBHOOK_URL_2!,
  process.env.CLAY_WEBHOOK_URL_3!,
]);

Step 5: Auto-Delete for Stream-Through Processing

For high-volume use cases where Clay enriches and pushes data onward, enable auto-delete to keep tables lean:

In Clay UI: Table Settings > Auto-delete

When enabled, Clay enriches incoming webhook data, sends results via HTTP API column to your destination, then deletes the rows. This keeps Clay functioning as a streaming enrichment service rather than a database.

Error Handling

IssueCauseSolution
Processing stuck at 400/hrExplorer plan throttleUpgrade to Growth (no throttle)
Webhook exhausted (50K)High volumeRotate to new webhook, implement rotator
Queue backing upWebhook rate limitingReduce concurrency, increase delay
Table too large to manage10K+ rowsSplit into multiple focused tables
Credit overrunUncontrolled batch sizeAdd budget check before queueing

Resources

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For reliability patterns, see clay-reliability-patterns.

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