Search Results for "task control qr code"

Hatchet replaces difficult to manage legacy queues or pub/sub systems so you can design durable workloads that recover from failure and solve for problems like concurrency, fairness, and rate limiting. Instead of managing your own task queue or pub/sub system, you can use Hatchet to distribute your functions between a set of workers with minimal configuration or infrastructure:

Ansible Semaphore is a modern UI for Ansible. It lets you easily run Ansible playbooks, get notifications about fails, control access to deployment system. If your project has grown and deploying from the terminal is no longer for you then Ansible Semaphore is what you need. Each successful project will ultimately require the use of CI/CD practices. We understand this and therefore are actively developing Ansible Semaphore in this direction. The separation of task into build and deployment allows you to safely update your production environment. ...

Beads is an open-source project providing a distributed, structured memory system for AI coding agents, replacing ad-hoc text plans with a git-backed graph that represents tasks, dependencies, and progress in a persistent, queryable format. Instead of storing plans as unstructured Markdown or ephemeral notes, Beads organizes agent state, task artifacts, and relationships as nodes and edges in a version-controlled graph so that long-horizon projects don’t lose context or coherence as the...

Built on the simple mechanics of resources, tasks, and jobs, Concourse presents a general approach to automation that makes it great for CI/CD. Concourse is designed to be expressive, versatile, and safe, remaining intuitive as the complexity of your project grows. A Concourse pipeline is like a distributed, continuous Makefile. Each job has a build plan declaring the job's input resources and what to run with them when they change. Your pipeline is then visualized in the web UI, taking only...

whatsapp-mcp is an open source Model Context Protocol (MCP) server that enables AI agents to interact directly with a user’s WhatsApp account through a structured interface. It acts as a bridge between WhatsApp and large language models, allowing controlled access to messages, chats, and contacts. whatsapp-mcp is composed of two main components: a Go-based bridge that connects to the WhatsApp Web API and stores data locally, and a Python-based MCP server that exposes tools for AI...