Titan is a zero-dependency distributed orchestrator, seamlessly bridging static DevOps pipelines with dynamic AI workflows. Built from scratch and designed for small-to-medium scale environments, it offers flexible orchestration, auto-scaling, and capability-based routing, making complex task management straightforward.
DistributedTaskOrchestrator - A Zero-Dependency Distributed Orchestrator
Overview
Titan is a cutting-edge distributed orchestrator crafted from the ground up, designed to seamlessly bridge the divide between Static Job Schedulers (such as Apache Airflow) and Dynamic Agent Runtimes. It functions as a Self-Hosting, Self-Healing Micro-PaaS that consolidates essential orchestration capabilities—managing worker lifecycles, resolving dependencies, and governing resources—into a single binary without external dependencies.
Core Technology
Developed in Java for the core engine and Python for the SDK, Titan is built entirely with raw TCP sockets, eliminating the need for external databases or bulky frameworks.
Key Features
Built to adapt to varying complexities, Titan offers a versatile Capability Spectrum:
-
Distributed Cron: Easily schedule and run Python scripts on remote machines periodically, resembling a lightweight, distributed version of
crontab. -
Service Orchestrator: Keep long-running services alive, ensuring automatic restarts in case of failures, akin to PM2 or HashiCorp Nomad.
-
Agentic AI Runtime: Utilize the SDK to deploy self-modifying execution graphs where AI agents autonomously manage their infrastructures.
Two Distinct Workflows
Titan accommodates different user requirements through two distinct operational paths:
- Static Workflows (DevOps Path): Utilize just the Titan binary and a YAML definition for deterministic Directed Acyclic Graphs (DAGs) that are pre-defined before execution. Suitable for tasks like nightly ETL, database backups, and periodic reports.
- Dynamic Agentic Workflows (AI Path): Leverage the Titan Python SDK to dynamically construct execution graphs that adapt based on runtime decisions or logic, ideal for complex AI tasks, self-healing loops, and recursive web scraping applications.
Advanced Resource Governance
Titan excels in resource management by distinguishing between Permanent and Ephemeral Nodes, enabling precise control over resource allocation and protecting critical nodes from auto-scaling logic. Furthermore, it features Capability-Based Routing, ensuring tasks are assigned to workers with specific skills (e.g., GPU or HIGH_MEM) only.
High-Performance Engineering
Titan stands out with a perfectly engineered infrastructure that includes:
- A custom binary protocol (
TITAN_PROTO) ensuring low-latency communication. - Reactive auto-scaling based on real-time workload analysis, allowing the cluster to maintain efficiency under varying loads.
- Smart task affinity that enhances performance by placing related tasks on the same node to maximize cache utilization.
Use Cases and Scenarios
The system offers end-to-end solutions for various applications, ranging from simple job scheduling to the complex orchestration of machine learning workflows. Demos showcase features like dynamic DAG execution and reactive auto-scaling, reinforcing its capabilities.
Documentation and Resources
Complete documentation details usage patterns, SDK integration, and advanced configurations tailored to diverse user needs. This includes examples to kickstart deployments and integrations with AI workflows, ensuring a smooth onboarding experience.
Conclusion
Titan serves as an innovative distributed orchestration framework that combines the reliability of static scheduling with the flexibility of dynamic execution, catering to the evolving needs of modern infrastructures.
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