Skill UI

This guide provides comprehensive strategies for scaling Customer.io integrations to handle high volumes of daily events. It covers implementing k6 load tests for performance benchmarking and outlines architectural patterns—from simple Direct APIs to complex Redis/Kafka queue-backed systems—ensuring reliability and managing API rate limits for massive data throughput.

Provides a comprehensive workflow for developing against Customer.io in local or staging environments. It implements environment isolation, dry-run clients, and service mocks to ensure development work does not affect production data, making unit and integration testing safe and reliable.

A comprehensive guide for configuring Customer.io across multiple, isolated environments (dev, staging, prod). This method utilizes typed environment configuration, environment-aware client wrappers, and secure use of environment variables to ensure data integrity and prevent cross-contamination in CI/CD pipelines. Ideal for scalable SaaS applications.

A comprehensive reference architecture guide for implementing enterprise-grade integrations with Customer.io. It details best practices for building robust, scalable, and reliable systems, focusing on event-driven patterns, message queuing (e.g., Redis/Kafka), service layer separation, and idempotency. Ideal for designing complex data pipelines and ensuring high availability in mission-critical applications.

This guide provides technical patterns for building fault-tolerant integrations with Customer.io. Learn to implement critical resilience techniques, including Circuit Breakers to prevent cascading failures, Retry with Jitter for handling transient errors, and Fallback Queues (using Redis) to ensure data continuity during service outages. Essential for robust, production-grade applications.

This guide details production-ready patterns for integrating the Customer.io SDK (customerio-node). It covers best practices including building type-safe clients, implementing robust retry logic with exponential backoff for network stability, performing efficient event batching for high-volume data streams, and managing singleton lifecycles. Use these patterns to build scalable, reliable, and maintainable user behavior tracking systems.

This comprehensive guide details essential security best practices for integrating with Customer.io. It covers secure credential storage using secrets managers, sanitizing Personally Identifiable Information (PII) via hashing, verifying webhook signatures (HMAC-SHA256) to ensure data integrity, and establishing procedures for API key rotation to maintain compliance with GDPR/CCPA regulations.

Guides building bespoke interactive data visualizations with d3.js across vanilla or framework-based JavaScript, covering custom layouts, transitions, and responsive sizing.

Implements best practices for secure audio transcription using Deepgram. This guide covers PII redaction (built-in and custom patterns), secure audio upload to S3 with encryption, managing data retention policies, and ensuring compliance with major regulations like GDPR and HIPAA. It provides a comprehensive pipeline for handling sensitive audio data in enterprise applications.

This advanced workflow executes sophisticated web data gathering tasks. It supports three primary functions: LLM-powered structured data extraction using custom JSON schemas or prompts; efficient batch scraping of multiple known URLs; and rapid site mapping to discover all reachable URLs on a domain. Use this when you require reliable, typed data structures rather than raw markdown content.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

This comprehensive guide covers the entire data lifecycle management for Granola meeting notes. Users learn how to export data using local cache scripts or Enterprise APIs, set customized data retention policies, and handle data subject access requests (SARs). It is essential for maintaining GDPR/CCPA compliance and ensuring data portability.