SuperPlane

SuperPlane is an open source control plane for agentic engineering and operations workflows. It gives teams a canvas for event-driven automation where AI agents, CI systems, deployment tools, incident platforms, ticketing systems, observability products, and cloud services can coordinate in one durable workflow graph. The project is written mainly in Go and ships a self-hostable demo container, a cloud beta, documentation, and a large integration surface for teams that want more than a single chat-based agent. The core object is a canvas. A canvas contains triggers and action components arranged as a dependency graph. Incoming events start runs, run items move through the graph, and SuperPlane stores payloads, state, memory, and execution history so failed or delayed steps can resume without every team writing custom retry logic. The README describes memory as app-scoped JSON storage that persists across runs, which lets workflows carry context from one execution to the next. SuperPlane is especially relevant for agentic engineering because it treats agents as operators inside real workflows instead of side chats. The README calls out a built-in per-app agent that can help design workflows and debug runs, plus a CLI and skills for external coding agents. It also lists AI and LLM integrations for Claude, Cursor, OpenAI, and Perplexity alongside CI/CD, cloud, incident, observability, communication, and ticketing integrations. That makes it useful when an agent needs to open an incident, collect recent deploy context, wait for approval, trigger a deploy, post a notification, or coordinate multiple repositories. Example workflows include pull-request preview environments, policy-gated production deploys, progressive delivery, release trains across multiple services, and first-five-minutes incident triage. Those examples show the product’s bias: it is not a generic prompt wrapper. It is built for teams that need event triggers, approvals, durable state, fan-in, fan-out, integration components, and auditable execution around agent work. Builders can try SuperPlane locally by pulling `ghcr.io/superplanehq/superplane-demo:stable` and running it on port 3000 with a Docker volume. The project also points users to app.superplane.com for the cloud beta and to docs.superplane.com for the quick start. Pricing for the open source repository is free under Apache 2.0; cloud usage should be treated as beta or commercial service pricing that depends on SuperPlane’s hosted plan. The strongest fit is platform engineering, release automation, AI operations, and DevOps teams that want agents embedded in workflows with human approvals and operational context. The repository also has enough maturity signals to justify a page: thousands of GitHub stars, hundreds of forks, active pushes in late August 2026, Apache 2.0 licensing, and documented quick-start paths. Teams should still evaluate it as infrastructure. It sits close to deploy and incident flows, so pilots should start with non-production canvases, explicit approvals, and narrow integration scopes before moving into release-critical automation.