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enterprise-infrastructure

Build progressive Kailash infrastructure with durable execution, scheduling, and task queuing.

Updated Oct 10, 2025
Search Tags:#checkpointing#idempotency#durable execution#task queue#worker registry#sql dialect portability#scheduler cron
One-click install
npx skills add https://github.com/FFOO6866/lead2cash --skill enterprise-infrastructure-ffoo6866
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: enterprise-infrastructure
Source: https://github.com/FFOO6866/lead2cash/tree/main/.claude/skills/15-enterprise-infrastructure
Command: npx skills add https://github.com/FFOO6866/lead2cash --skill enterprise-infrastructure-ffoo6866

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you design and operate a progressive, enterprise-grade infrastructure layer for Kailash workloads, so your workflows can scale from single-process SQLite to multi-worker PostgreSQL/MySQL while staying reliable through durable execution, checkpoints, scheduling, task queues, and idempotency.

Core Features & Use Cases

  • Progressive Infrastructure Levels (0/1/2): Move from in-process SQLite (Level 0) to shared DB persistence (Level 1) to multi-worker execution with a task queue (Level 2) using environment variables only.
  • Dialect-Portable SQL & Safe Identifier Handling: Use a QueryDialect strategy with canonical ? placeholders and mandatory identifier validation to prevent SQL injection and ensure cross-database compatibility.
  • Durable Execution + Checkpointing: Resume workflows after crashes via ExecutionTracker checkpoints, CheckpointManager tiered persistence, and the DurableRequest state machine, optionally wired through DurableWorkflowServer.
  • Distributed Primitives for Enterprise Ops: Scheduler (cron/interval/one-shot) with persistence, SQL task queue with FOR UPDATE SKIP LOCKED, worker registry with heartbeats and dead-worker reaping, and at-most-once semantics through IdempotentExecutor.

Quick Start

Use the enterprise-infrastructure skill to run a resilient scheduled and durable workflow by setting KAILASH_DATABASE_URL (and optionally KAILASH_QUEUE_URL), then wiring WorkflowScheduler for cron and DurableWorkflowServer for durable execution in your service.

Frequently Asked Questions about enterprise-infrastructure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement durable execution for long-running workflows that resume after crashes?▼

Durable execution persists workflow state through ExecutionTracker checkpoints and a DurableRequest state machine, allowing long-running workflows to safely resume after crashes via tiered checkpoint persistence and resume contracts.

Can I scale task queues across multiple workers using PostgreSQL and MySQL?▼

Yes, distributed task queuing scales across PostgreSQL and MySQL using SQL `FOR UPDATE SKIP LOCKED` for safe claim semantics, a worker registry with heartbeats, and automatic dead-worker reaping for multi-worker dispatch.

What's the best way to write SQL that works across SQLite, PostgreSQL, and MySQL?▼

SQL dialect portability is achieved through a QueryDialect strategy using canonical `?` placeholders with automatic translation and mandatory identifier validation to prevent SQL injection across SQLite, PostgreSQL, and MySQL.

How do I schedule recurring cron jobs and interval executions with crash recovery?▼

A WorkflowScheduler handles cron, interval, and one-shot scheduling with persistence, ensuring recurring executions survive crashes by storing schedule state in the configured database backend for reliable recovery.

How does idempotency work for distributed task execution?▼

Idempotency ensures exactly-once execution semantics through an IdempotentExecutor that enforces claim-execute-store patterns, preventing duplicate task processing across distributed workers even during retries or crashes.

Do I need a separate queue database to move from single-process SQLite to multi-worker execution?▼

No, progressive infrastructure levels let you move from in-process SQLite (Level 0) to shared database persistence (Level 1) to multi-worker task queues (Level 2) using environment variables like KAILASH_DATABASE_URL and optional KAILASH_QUEUE_URL.

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