instantly-performance-tuning

Optimize Instantly.ai API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing high-volume lead operations. Trigger with phrases like "instantly performance", "instantly slow", "instantly caching", "instantly batch", "optimize instantly api".

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instantly-pack Plugin
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instantly-pack

Claude Code skill pack for Instantly (24 skills)

saas packs v1.0.0
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Installation

This skill is included in the instantly-pack plugin:

/plugin install instantly-pack@claude-code-plugins-plus

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Instructions

Instantly Performance Tuning

Overview

Optimize Instantly API v2 integrations for speed and throughput. Key areas: caching analytics data, batching lead operations, concurrent request management, efficient pagination, and connection reuse. The email listing endpoint has a strict 20 req/min limit that requires special handling.

Prerequisites

  • Completed instantly-install-auth setup
  • Working Instantly integration
  • Understanding of async patterns and caching strategies

Instructions

Step 1: Cache Analytics Data

Campaign analytics don't change every second — cache them for 5-15 minutes to avoid redundant API calls.


class InstantlyCache {
  private cache = new Map<string, { data: unknown; expiry: number }>();

  get<T>(key: string): T | null {
    const entry = this.cache.get(key);
    if (!entry || Date.now() > entry.expiry) {
      this.cache.delete(key);
      return null;
    }
    return entry.data as T;
  }

  set(key: string, data: unknown, ttlMs: number) {
    this.cache.set(key, { data, expiry: Date.now() + ttlMs });
  }
}

const cache = new InstantlyCache();

async function getCachedAnalytics(campaignId: string) {
  const cacheKey = `analytics:${campaignId}`;
  const cached = cache.get<CampaignAnalytics>(cacheKey);
  if (cached) return cached;

  const data = await instantly<CampaignAnalytics>(
    `/campaigns/analytics?id=${campaignId}`
  );
  cache.set(cacheKey, data, 5 * 60 * 1000); // 5 min TTL
  return data;
}

// Cache campaign list (changes infrequently)
async function getCachedCampaigns() {
  const cacheKey = "campaigns:all";
  const cached = cache.get<Campaign[]>(cacheKey);
  if (cached) return cached;

  const campaigns = await instantly<Campaign[]>("/campaigns?limit=100");
  cache.set(cacheKey, campaigns, 15 * 60 * 1000); // 15 min TTL
  return campaigns;
}

Step 2: Batch Lead Operations with Controlled Concurrency


interface BatchResult<T> {
  succeeded: T[];
  failed: Array<{ input: unknown; error: string }>;
  duration: number;
}

async function batchAddLeads(
  campaignId: string,
  leads: Array<{ email: string; first_name?: string; company_name?: string }>,
  options = { concurrency: 5, delayMs: 200, retries: 3 }
): Promise<BatchResult<Lead>> {
  const start = Date.now();
  const succeeded: Lead[] = [];
  const failed: Array<{ input: unknown; error: string }> = [];
  let active = 0;

  const addWithRetry = async (lead: typeof leads[0]) => {
    for (let attempt = 0; attempt <= options.retries; attempt++) {
      try {
        const result = await instantly<Lead>("/leads", {
          method: "POST",
          body: JSON.stringify({
            campaign: campaignId,
            email: lead.email,
            first_name: lead.first_name,
            company_name: lead.company_name,
            skip_if_in_workspace: true,
          }),
        });
        succeeded.push(result);
        return;
      } catch (err: any) {
        if (err.status === 429) {
          await new Promise((r) => setTimeout(r, Math.pow(2, attempt) * 1000));
          continue;
        }
        if (attempt === options.retries) {
          failed.push({ input: lead, error: err.message });
        }
      }
    }
  };

  // Process in chunks
  for (let i = 0; i < leads.length; i += options.concurrency) {
    const chunk = leads.slice(i, i + options.concurrency);
    await Promise.allSettled(chunk.map(addWithRetry));

    if (i + options.concurrency < leads.length) {
      await new Promise((r) => setTimeout(r, options.delayMs));
    }

    // Progress report
    const progress = Math.min(i + options.concurrency, leads.length);
    console.log(`Progress: ${progress}/${leads.length} (${succeeded.length} ok, ${failed.length} failed)`);
  }

  return { succeeded, failed, duration: Date.now() - start };
}

Step 3: Efficient Pagination


// Pre-fetch next page while processing current page
async function* prefetchPaginate<T extends { id: string }>(
  path: string,
  pageSize = 100
): AsyncGenerator<T[]> {
  let startingAfter: string | undefined;
  let nextPagePromise: Promise<T[]> | null = null;

  const fetchPage = (after?: string) => {
    const qs = new URLSearchParams({ limit: String(pageSize) });
    if (after) qs.set("starting_after", after);
    return instantly<T[]>(`${path}?${qs}`);
  };

  // Fetch first page
  let currentPage = await fetchPage();

  while (currentPage.length > 0) {
    // Start fetching next page immediately
    if (currentPage.length === pageSize) {
      const lastId = currentPage[currentPage.length - 1].id;
      nextPagePromise = fetchPage(lastId);
    } else {
      nextPagePromise = null;
    }

    yield currentPage;

    if (!nextPagePromise) break;
    currentPage = await nextPagePromise;
  }
}

// Usage — processes next page while current page is being handled
for await (const batch of prefetchPaginate<Lead>("/leads/list")) {
  for (const lead of batch) {
    // Process lead — next page is already loading
  }
}

Step 4: Connection Reuse with Keep-Alive


import { Agent } from "undici";

// Create a persistent connection pool
const dispatcher = new Agent({
  keepAliveTimeout: 30000,     // keep connections alive for 30s
  keepAliveMaxTimeout: 60000,
  connections: 10,             // max 10 concurrent connections
  pipelining: 1,
});

async function instantlyPooled<T>(path: string, options: RequestInit = {}): Promise<T> {
  const url = `https://api.instantly.ai/api/v2${path}`;
  const res = await fetch(url, {
    ...options,
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.INSTANTLY_API_KEY}`,
      ...options.headers,
    },
    // @ts-ignore — undici dispatcher
    dispatcher,
  });

  if (!res.ok) throw new Error(`Instantly ${res.status}: ${await res.text()}`);
  return res.json() as Promise<T>;
}

Step 5: Throttled Email Fetcher (20 req/min limit)


class ThrottledEmailClient {
  private timestamps: number[] = [];
  private readonly maxPerMinute = 18; // leave margin

  private async throttle() {
    const now = Date.now();
    this.timestamps = this.timestamps.filter((t) => now - t < 60000);

    if (this.timestamps.length >= this.maxPerMinute) {
      const wait = 60000 - (now - this.timestamps[0]) + 500;
      await new Promise((r) => setTimeout(r, wait));
    }
    this.timestamps.push(Date.now());
  }

  async listEmails(params: { campaign_id?: string; limit?: number; starting_after?: string }) {
    await this.throttle();
    const qs = new URLSearchParams();
    if (params.campaign_id) qs.set("campaign_id", params.campaign_id);
    if (params.limit) qs.set("limit", String(params.limit));
    if (params.starting_after) qs.set("starting_after", params.starting_after);
    return instantly(`/emails?${qs}`);
  }

  async getUnreadCount() {
    await this.throttle();
    return instantly("/emails/unread/count");
  }
}

Performance Benchmarks

Operation Unoptimized Optimized Improvement
500 lead import ~250s (sequential) ~30s (5 concurrent + batch) 8x
Campaign analytics (10 queries) 10 API calls 1 API call (cached) 10x
All campaigns page load ~2s (no cache) ~50ms (cached) 40x
Lead pagination (10K leads) ~100s (sequential) ~50s (prefetch) 2x

Error Handling

Error Cause Solution
429 during batch import Too many concurrent requests Reduce concurrency, increase delay
429 on email listing >20 req/min Use ThrottledEmailClient
Stale cache data TTL too long Reduce TTL or add cache invalidation
Memory issues Large pagination result set Use async generators, process in chunks

Resources

Next Steps

For cost optimization, see instantly-cost-tuning.

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