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Customer.io Performance Tuning

customerio-performance-tuning

Optimize Customer.io API performance for high throughput.

SKILL.md

Full skill instructions

Customer.io Performance Tuning

Overview

Optimize Customer.io API performance for high-volume integrations: HTTP connection pooling, identify deduplication caching, event batching with flush control, fire-and-forget async tracking, and regional routing.

Prerequisites

  • Working Customer.io integration
  • Understanding of your traffic patterns and volume
  • Monitoring to measure improvement (see customerio-observability)

Performance Targets

OperationBaselineOptimizedTechnique
Single identify~200ms~80msConnection pooling
Single track~200ms~80msConnection pooling
100 events batch~20s serial~500msParallel batching
Duplicate identify~200ms~0msDedup cache
Non-critical trackBlockingNon-blockingFire-and-forget

Instructions

Step 1: HTTP Connection Pooling

// lib/​customerio-pooled.ts
import { TrackClient, RegionUS } from "customerio-node";
import https from "https";

// The customerio-node SDK creates new connections by default.
// Reuse connections with a keep-alive agent.
const agent = new https.Agent({
  keepAlive: true,
  maxSockets: 25,        // Max concurrent connections
  maxFreeSockets: 10,    // Keep idle connections open
  timeout: 30000,        // 30s socket timeout
  keepAliveMsecs: 15000, // TCP keep-alive probe interval
});

// Apply to the SDK by creating a singleton with the agent
// Note: customerio-node doesn't directly accept an agent,
// but we configure Node.js global agent for HTTPS
https.globalAgent = agent;

// Singleton client — one instance = one connection pool
const cio = new TrackClient(
  process.env.CUSTOMERIO_SITE_ID!,
  process.env.CUSTOMERIO_TRACK_API_KEY!,
  { region: RegionUS }
);

export { cio };

Step 2: Identify Deduplication Cache

// lib/​customerio-dedup.ts
// Skip duplicate identify() calls within a time window

class LRUCache<K, V> {
  private map = new Map<K, V>();
  constructor(private maxSize: number) {}

  get(key: K): V | undefined {
    const val = this.map.get(key);
    if (val !== undefined) {
      // Move to end (most recent)
      this.map.delete(key);
      this.map.set(key, val);
    }
    return val;
  }

  set(key: K, val: V): void {
    this.map.delete(key);
    this.map.set(key, val);
    if (this.map.size > this.maxSize) {
      const oldest = this.map.keys().next().value;
      this.map.delete(oldest!);
    }
  }
}

import { createHash } from "crypto";
import { TrackClient, RegionUS } from "customerio-node";

const identifyCache = new LRUCache<string, number>(10_000);
const DEDUP_TTL_MS = 5 * 60 * 1000;  // 5 minutes

const cio = new TrackClient(
  process.env.CUSTOMERIO_SITE_ID!,
  process.env.CUSTOMERIO_TRACK_API_KEY!,
  { region: RegionUS }
);

export async function dedupIdentify(
  userId: string,
  attrs: Record<string, any>
): Promise<void> {
  // Create a hash of userId + attributes
  const hash = createHash("sha256")
    .update(userId + JSON.stringify(attrs))
    .digest("hex")
    .substring(0, 16);

  const cached = identifyCache.get(hash);
  if (cached && Date.now() - cached < DEDUP_TTL_MS) {
    return; // Skip — identical identify() call within TTL window
  }

  await cio.identify(userId, attrs);
  identifyCache.set(hash, Date.now());
}

Step 3: Batch Processor

// lib/​customerio-batch.ts
import { TrackClient, RegionUS } from "customerio-node";

interface BatchItem {
  type: "identify" | "track";
  userId: string;
  data: Record<string, any>;
}

export class CioBatchProcessor {
  private buffer: BatchItem[] = [];
  private timer: NodeJS.Timeout | null = null;
  private client: TrackClient;
  private processing = false;

  constructor(
    private readonly maxBatchSize = 100,
    private readonly flushIntervalMs = 3000,
    private readonly concurrency = 15
  ) {
    this.client = new TrackClient(
      process.env.CUSTOMERIO_SITE_ID!,
      process.env.CUSTOMERIO_TRACK_API_KEY!,
      { region: RegionUS }
    );
    this.startFlushTimer();
  }

  add(item: BatchItem): void {
    this.buffer.push(item);
    if (this.buffer.length >= this.maxBatchSize) {
      this.flush();
    }
  }

  async flush(): Promise<void> {
    if (this.processing || this.buffer.length === 0) return;
    this.processing = true;

    const batch = this.buffer.splice(0, this.maxBatchSize);
    const startMs = Date.now();

    // Process in parallel chunks
    for (let i = 0; i < batch.length; i += this.concurrency) {
      const chunk = batch.slice(i, i + this.concurrency);
      const results = await Promise.allSettled(
        chunk.map((item) =>
          item.type === "identify"
            ? this.client.identify(item.userId, item.data)
            : this.client.track(item.userId, item.data)
        )
      );

      const failed = results.filter((r) => r.status === "rejected").length;
      if (failed > 0) {
        console.warn(`CIO batch: ${failed}/​${chunk.length} failed`);
      }
    }

    const elapsed = Date.now() - startMs;
    console.log(`CIO batch: ${batch.length} items in ${elapsed}ms`);
    this.processing = false;
  }

  private startFlushTimer(): void {
    this.timer = setInterval(() => this.flush(), this.flushIntervalMs);
  }

  async shutdown(): Promise<void> {
    if (this.timer) clearInterval(this.timer);
    await this.flush();
  }
}

Step 4: Fire-and-Forget Async Tracking

// lib/​customerio-async.ts
// For non-critical analytics events — don't block the request path

import { TrackClient, RegionUS } from "customerio-node";

const cio = new TrackClient(
  process.env.CUSTOMERIO_SITE_ID!,
  process.env.CUSTOMERIO_TRACK_API_KEY!,
  { region: RegionUS }
);

export function fireAndForgetTrack(
  userId: string,
  eventName: string,
  data?: Record<string, any>
): void {
  // No await — returns immediately
  cio
    .track(userId, { name: eventName, data })
    .catch((err) => console.error(`CIO async track failed: ${err.message}`));
}

// Usage in Express route — does NOT slow down response
router.get("/​dashboard", async (req, res) => {
  fireAndForgetTrack(req.user.id, "dashboard_viewed", {
    timestamp: Math.floor(Date.now() / 1000),
  });

  const data = await loadDashboardData(req.user.id);
  res.json(data);  // Returns immediately without waiting for CIO
});

Step 5: Regional Routing

// lib/​customerio-region.ts
import { TrackClient, APIClient, RegionUS, RegionEU } from "customerio-node";

// Route to nearest Customer.io region based on configuration
// US accounts: track.customer.io / api.customer.io
// EU accounts: track-eu.customer.io / api-eu.customer.io

interface CioRegionalConfig {
  us: { siteId: string; trackKey: string; appKey: string };
  eu: { siteId: string; trackKey: string; appKey: string };
}

function getClientForUser(
  config: CioRegionalConfig,
  userRegion: "us" | "eu"
): { track: TrackClient; api: APIClient } {
  const creds = config[userRegion];
  const region = userRegion === "eu" ? RegionEU : RegionUS;

  return {
    track: new TrackClient(creds.siteId, creds.trackKey, { region }),
    api: new APIClient(creds.appKey, { region }),
  };
}

Performance Monitoring

// Wrap operations to measure latency
async function timedCioCall<T>(
  operation: string,
  fn: () => Promise<T>
): Promise<T> {
  const start = Date.now();
  try {
    const result = await fn();
    const elapsed = Date.now() - start;
    console.log(`CIO ${operation}: ${elapsed}ms`);
    return result;
  } catch (err) {
    const elapsed = Date.now() - start;
    console.error(`CIO ${operation} FAILED: ${elapsed}ms`);
    throw err;
  }
}

Error Handling

IssueSolution
High p99 latencyEnable connection pooling, check DNS resolution
Timeout errorsIncrease timeout, reduce payload size
Memory growthCap LRU cache size, limit batch buffer
Dedup cache missesIncrease TTL if same identify calls are >5min apart

Resources

Next Steps

After performance tuning, proceed to customerio-cost-tuning for cost optimization.

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