With nearly 3,000 GitHub stars and 14 releases since its June 2025 launch, Kite delivers a lightweight Kubernetes dashboard that replaces the fragmented workflow of switching between kubectl, Lens, and separate monitoring tools with a unified multi-cluster management platform. The dashboard automatically discovers clusters from kubeconfig files and supports independent Prometheus configurations per cluster, providing real-time CPU, memory, and network charts alongside live pod log streaming with filtering and search. A built-in web terminal opens shells directly into pods and nodes without kubectl port-forward, while the Monaco-based YAML editor offers syntax highlighting and validation for in-place resource editing. The integrated AI agent, powered by OpenAI or Anthropic models via native Go SDK integrations, translates natural language into precise client-go API calls — querying cluster health, analyzing pod logs, scaling deployments, patching resources, and cleaning up failed jobs — all operating strictly within the logged-in user's RBAC permissions. Enterprise governance includes OAuth 2.0 single sign-on, multi-factor authentication, FIDO2 passkeys, granular role-based access control with per-namespace permissions, and comprehensive audit logging. Helm chart management enables browsing, installing, and upgrading releases directly from the UI, while the Docker registry integration provides quick image tag selection. Deploy via a single Docker container with SQLite or use the official OCI Helm chart with PostgreSQL or MySQL for production. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

With over 3,700 GitHub stars and growing adoption among teams tired of managing complex orchestration platforms, Dagu delivers a complete workflow engine as a single Go binary that requires no external database, message broker, or framework installation. Define directed acyclic graphs in declarative YAML — specifying dependencies, schedules, retries, timeouts, approvals, and notifications — while keeping existing shell scripts, containers, and tools completely unchanged. The built-in Web UI provides live pipeline visualization, per-step log streaming, run history browsing, artifact previewing, manual retry controls, and workflow YAML editing without SSHing into servers. Execute steps as shell commands, Docker containers, Kubernetes Jobs, SSH remote commands, SQL queries, or HTTP requests, with conditional branching and parallel execution handled natively. The integrated Model Context Protocol server exposes dagu_read, dagu_change, and dagu_execute tools, enabling AI agents like Claude, Codex, and Cursor to inspect workflow state, preview YAML modifications, and control runs through authenticated endpoints. The harness.run executor lets external coding-agent CLIs operate inside DAG steps with full scheduling and approval gate support. Scale beyond a single machine with the distributed worker mode, which dispatches tasks to remote nodes via gRPC with automatic label-based routing and worker selection. Deploy with Docker, the official Helm chart for Kubernetes, or a simple binary download requiring only a Linux, macOS, or Windows host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.